diff --git a/data/Making subject data.xlsx b/data/Making subject data.xlsx
deleted file mode 100644
index 96246f3..0000000
Binary files a/data/Making subject data.xlsx and /dev/null differ
diff --git a/data/Subject data.csv b/data/Subject data.csv
deleted file mode 100644
index 2a3dff6..0000000
--- a/data/Subject data.csv	
+++ /dev/null
@@ -1,11197 +0,0 @@
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diff --git a/data/TSR data complete - nonreverse scored.csv b/data/TSR data complete - nonreverse scored.csv
deleted file mode 100644
index 6335503..0000000
--- a/data/TSR data complete - nonreverse scored.csv	
+++ /dev/null
@@ -1,934 +0,0 @@
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-12787012328,1,2,1,1,3,4,4,4,4,3,1,4,1,1,1,4,5,4,5,4,5,5,4,5,4,2,2,3,4,5,5,3,4,4,5,3,4,1,1,1,5,4,,,,3,,5,6,7,,9,10,11,,,,,,,,5,6,7,,9,10,,,,,1,2,,4,5,6,,,9,2,1,,1,,3,1,2,,5,
-12786903663,1,2,1,1,2,3,2,2,4,3,2,0,1,1,1,1,5,5,2,4,5,5,5,5,2,1,2,2,0,0,3,3,0,0,0,0,2,2,1,1,4,5,0,,,,,,,,,,,,,,,,2,,4,5,6,7,8,9,10,11,,13,0,,,,,,,,,,2,1,,1,2,3,1,2,,5,
-12785647917,1,3,2,1,3,4,2,4,3,4,2,5,3,1,3,2,5,2,3,5,4,5,3,5,5,5,5,4,3,4,3,3,3,4,4,3,2,1,2,1,4,5,,,2,,,,6,,8,9,,,,,,,,,,,,7,,9,10,,,,,,2,,4,,,,,9,2,1,,,,3,2,6,,9,
-12785516152,1,2,1,1,5,4,2,5,5,5,5,5,4,3,4,5,2,4,4,5,4,5,5,5,5,1,4,5,4,5,3,4,4,5,5,2,3,1,1,2,1,4,,,,,,,6,7,8,,10,,,,,,,,,5,6,7,,,10,,,,,,,3,,5,6,,,9,2,1,,,,3,3,2,,2,
-12785379410,1,2,2,2,2,4,3,2,4,2,2,3,4,2,2,2,2,4,4,3,2,4,4,4,4,1,1,2,3,3,3,2,3,3,3,3,3,2,1,2,4,4,,,,3,4,5,6,7,,9,10,11,,,,,,3,,5,6,7,,9,10,11,,13,,,,3,4,5,,,,9,2,1,,,,3,1,3,,11,
-12784454137,1,2,2,1,5,3,4,2,5,5,4,1,4,3,3,2,5,3,5,2,5,5,5,1,5,4,5,5,5,1,2,3,5,0,5,2,5,2,1,1,5,5,,1,,3,,,6,7,,,10,,,,,,,3,,,6,7,,,,,,,,,,,4,5,,,,,2,2,,,,,1,14,,5,
-12783696551,1,3,2,1,4,1,3,2,4,4,4,2,2,2,4,4,4,3,2,3,4,4,4,4,4,5,5,3,4,3,3,3,4,4,4,3,4,2,2,3,5,5,,,,,,,6,7,,,,,,,,,,3,,5,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12782710625,1,2,1,2,2,2,2,1,4,5,1,2,1,1,2,2,1,2,1,2,2,2,3,5,4,5,2,4,4,3,3,3,4,4,4,2,3,3,2,2,5,5,,1,,3,,,,7,,,,,12,,,1,,3,,5,6,7,,,,,,,,,2,3,4,,,,,9,2,1,,,,3,2,14,,17,
-12782558062,1,4,3,1,4,2,1,2,2,4,2,4,2,2,2,4,2,1,1,3,2,2,4,4,1,5,4,2,5,3,2,2,5,5,4,3,2,1,1,2,5,5,,,,,,5,6,7,,,10,,,,,,,3,,,6,7,,9,10,,,,,,,3,4,5,,,,9,2,1,,1,,3,2,2,,5,
-12782034206,1,2,1,1,4,2,1,1,4,2,1,2,1,1,3,2,3,2,2,3,3,3,3,3,3,3,3,2,3,1,1,4,4,3,3,1,1,1,1,1,2,1,,1,,3,4,5,6,7,,,,,,,,,,,,5,6,7,,,,,,13,,1,,3,4,5,,,,9,2,1,,,,3,2,6,,5,
-12781823056,1,2,1,1,1,5,4,4,2,1,1,2,2,1,2,2,1,5,2,4,2,2,4,4,5,3,1,2,1,5,5,3,3,3,4,2,5,1,1,2,5,5,,1,,,,5,6,,,9,10,,,,,1,,,,,6,7,,9,10,,,,,,,3,4,,,,,9,2,1,,1,,,1,3,,11,
-12781478999,1,2,1,2,2,4,2,3,3,4,3,4,2,2,2,2,2,4,2,3,3,4,3,3,4,1,1,2,3,3,2,2,4,5,5,3,2,1,1,2,5,5,,,2,,,5,6,7,,9,10,,,13,,,2,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,8,9,2,2,,,,,1,12,,17,
-12781120027,1,2,2,1,2,3,2,2,4,3,3,1,1,2,3,1,1,2,3,2,3,4,1,4,3,4,4,3,2,3,2,4,2,3,3,1,2,3,1,2,3,1,,,2,,4,,6,,,,,,,,,,,3,4,,,,,,,,,13,,,2,,,5,,,8,,3,1,,,2,,1,4,,14,
-12780940666,1,2,2,1,5,4,2,2,4,5,5,3,0,1,2,3,5,5,5,5,5,5,5,5,5,1,2,5,4,3,3,4,5,5,5,3,4,1,1,3,2,1,,,,,,5,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,,,,,,9,2,2,,,,,1,14,,17,
-12780884209,1,3,2,1,5,2,2,2,4,1,2,2,1,1,1,1,5,5,5,5,5,5,5,5,2,5,2,2,4,4,3,5,3,5,5,3,2,1,1,3,2,1,,1,,,,,,,,,,,,,,,,,,,6,,8,,,,,13,,,,,,,,,,9,1,1,0,,,,1,1,,11,
-12780761322,1,3,2,1,5,5,5,1,5,5,3,1,3,1,4,3,5,5,5,2,5,5,5,1,5,5,5,5,5,5,2,2,4,5,4,1,3,1,1,1,5,5,0,,,,,,,,,,,,,,,,,,4,5,6,7,,,,11,,,,,,3,,5,,,,,2,2,,,,,1,14,,2,
-12780737593,1,3,3,1,2,4,3,1,2,2,4,3,1,1,2,4,2,4,2,4,2,2,4,4,3,2,2,5,2,4,1,1,3,3,4,3,3,2,1,3,3,3,,1,,,,5,6,7,,,10,,,,,,,,,5,,7,,,,,,,,,,3,4,,,,8,9,2,2,,,,,1,14,,2,
-12780661815,1,3,2,1,3,2,2,1,2,4,3,3,2,1,2,2,3,4,2,4,4,3,4,3,4,1,2,2,3,2,3,2,4,0,4,2,4,1,1,2,6,4,0,,,,,,,,,,,,,,,1,2,3,4,5,6,7,,9,10,,,13,,,,3,,5,6,7,8,9,2,2,,,,,1,0,Turkish,11,
-12780611980,1,3,2,1,2,2,2,1,2,3,3,1,1,1,3,1,2,2,3,3,3,3,4,4,5,2,4,2,4,2,2,3,2,4,5,2,3,1,1,1,5,5,,,,3,,5,6,7,8,,10,,,,,,,3,,5,6,7,,9,,,,,,,2,3,,,,,,9,2,2,,,,,1,14,,1,
-12780609083,1,3,2,1,2,5,2,2,3,4,2,4,2,1,3,4,5,4,4,4,5,5,5,4,5,2,2,4,4,2,2,2,4,3,2,2,1,1,1,2,5,5,,,,3,,,6,7,,9,,,,,,,,,,5,6,7,,9,,11,,,,,2,3,4,5,,,,9,2,1,,,,3,1,6,,1,
-12780532323,1,2,2,2,2,5,1,2,4,5,2,3,2,2,2,2,5,5,3,3,5,5,5,4,2,5,3,2,5,3,3,1,3,0,3,2,2,1,2,1,6,5,0,,,,,,,,,,,,,,,,,3,4,5,6,7,8,,,11,,,,1,2,3,,5,6,,,9,2,2,,,,,1,14,,1,
-12780479693,1,3,2,1,2,5,5,2,2,2,1,3,3,3,2,2,3,5,5,5,4,2,3,4,5,5,4,2,2,4,4,3,5,3,2,3,4,2,1,1,5,4,,,,3,4,5,6,7,,,,11,,,,,,,4,5,6,7,,,,11,,,,,2,3,4,,6,,,,2,1,,1,,,1,4,,11,
-12780444903,1,3,2,1,3,4,3,2,4,5,2,3,2,2,2,2,3,4,2,3,4,4,4,4,4,2,3,2,3,2,4,3,2,,2,5,3,5,5,4,4,4,,,,,,,,,,,,,,,,,,,4,5,6,7,,,10,11,,,,1,2,3,4,,6,,,,2,2,,,,,1,2,,14,
-12780371030,1,3,2,1,5,5,5,5,5,5,5,5,5,1,1,5,5,5,5,5,5,5,5,5,5,2,2,5,5,4,3,,4,4,4,2,1,1,2,1,5,5,0,,,,,,,,,,,,,,,1,,,,5,6,,,,,,,13,,,,3,,5,,,,9,2,2,,,,,1,14,,1,
-12780230269,1,3,2,1,3,2,3,2,3,4,2,3,1,1,3,3,4,4,4,4,4,4,4,5,3,5,5,5,4,4,3,2,4,4,4,2,2,2,3,2,5,5,,,,,,,6,7,,,10,11,,,,,,,,,6,7,,,,11,,,,1,,3,4,5,6,,8,9,2,1,,1,,,1,14,,2,
-12780052651,1,2,1,3,3,4,2,2,4,5,2,2,2,2,2,2,4,5,4,3,5,5,5,2,5,3,3,3,5,4,3,0,5,5,4,3,2,1,1,3,3,2,,,,,4,,6,7,,,,,,,,1,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,1,14,,17,
-12779624841,1,2,1,1,4,4,1,1,4,5,2,4,1,1,2,4,4,4,2,2,4,4,4,4,4,2,4,2,3,5,2,2,4,5,5,3,1,1,3,2,1,5,,,,,,5,6,7,,,,,,,,,,3,4,,6,7,,,,,,,,,,3,,,,,,9,2,2,,,,,1,14,,17,
-12779482924,1,2,1,1,,4,2,2,2,4,2,2,1,1,1,3,5,5,5,5,5,5,5,5,5,2,5,5,1,1,1,1,1,1,1,1,1,1,1,1,3,4,,,,,,,6,,,,,,,,,,2,,,5,6,,,,,,,,,,,,,,,7,,,,,,,,,4,0,,17,
-12779431369,1,2,1,1,3,4,2,2,4,4,2,3,2,1,1,2,5,5,4,5,5,5,5,4,5,1,1,3,3,4,1,5,5,4,5,3,5,2,1,2,5,3,,,2,,,5,6,,,,,,,,,,,,,5,6,7,,9,,,,,,,,,4,5,,,,9,2,2,,,,,1,4,,11,
-12779414281,1,3,2,1,5,4,3,1,5,5,5,4,5,1,3,5,5,4,5,4,5,5,5,5,5,2,4,3,5,4,5,4,5,3,5,2,3,1,2,1,5,5,,1,,3,,5,,7,,9,10,,,,,,,,,,6,7,,9,,,,,,,,,,,,,,,2,2,,,,,1,14,,2,
-12779340472,1,2,1,1,3,2,1,1,4,4,4,2,1,1,2,1,4,2,1,2,4,4,4,1,4,3,3,2,2,1,1,2,1,3,2,2,2,1,1,2,5,5,,1,2,,4,5,6,,8,9,10,11,,13,,1,2,,4,5,6,7,,,10,11,12,13,,1,2,3,4,5,6,,8,9,2,2,,,,,2,3,,11,
-12779306592,1,3,2,1,4,4,5,5,5,5,4,5,5,2,4,4,5,5,3,5,5,5,5,5,5,3,5,5,2,3,2,3,2,3,3,2,3,1,3,2,3,4,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,9,2,1,,,,3,1,4,,11,
-12779269435,1,2,1,2,2,3,2,2,2,2,2,4,2,2,2,4,2,5,5,5,3,2,3,5,5,2,5,3,4,3,3,3,4,4,4,3,1,1,1,1,5,5,,,,,,,6,7,,,10,,,,,,,3,,5,6,7,,,10,,,,,,,3,4,5,6,,,9,2,1,,1,,,1,5,,2,
-12779159438,1,2,1,2,2,4,2,3,4,5,3,2,1,1,1,2,5,4,3,2,4,4,4,1,1,1,1,2,4,4,1,4,3,4,4,2,2,1,1,1,3,1,,1,2,3,,5,,7,,9,10,,,,,,2,,4,5,6,,,9,,,,,,1,2,3,4,5,6,7,,9,2,2,,,,,1,12,,17,
-12779133518,1,2,1,1,1,4,2,1,1,3,2,1,1,2,4,2,2,4,4,2,3,4,2,1,2,4,4,3,2,5,4,2,4,3,2,3,2,1,1,1,5,5,,,,,,5,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,,,3,4,5,,,,9,1,1,,1,,,1,14,,1,
-12779120180,1,2,1,2,3,3,3,3,3,3,3,3,3,3,2,3,5,5,5,5,4,5,4,5,5,3,2,4,4,4,2,4,4,5,4,5,4,3,1,2,5,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,9,10,,,,0,,,,,,,,,,2,2,,,,,1,14,,8,
-12779117434,1,3,2,1,2,3,2,2,4,5,3,3,2,1,2,2,5,5,5,5,5,5,5,5,5,3,5,4,1,2,2,2,3,3,4,1,2,1,1,1,3,2,0,,,,,,,,,,,,,,,1,2,3,,5,6,7,,9,10,,,,,1,2,,,,6,7,8,9,2,2,,,,,1,14,,2,
-12779061538,1,2,1,2,3,5,5,2,3,5,3,5,2,1,1,5,3,5,5,3,5,5,5,5,5,3,1,5,5,3,2,4,3,5,5,3,3,1,1,2,5,3,,,,,,,,7,,,,,,,,1,,,,5,6,7,8,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,1,14,,1,
-12779037270,1,2,1,2,1,4,4,1,1,3,3,1,1,2,2,2,1,3,3,1,2,5,5,2,1,5,5,1,2,3,4,3,2,5,4,3,1,1,1,1,2,2,,1,2,,,5,6,7,,9,,,,,,,,,4,5,6,7,,9,,,,,,,2,3,4,5,6,,,9,2,1,,,,3,1,17,,2,
-12779030543,1,3,2,2,3,3,3,3,3,3,3,3,3,3,3,3,4,3,2,4,4,4,4,3,3,4,4,3,4,3,3,4,4,4,4,3,3,2,1,2,1,2,,,,,,,6,7,,,,,,,,,,,,5,6,7,8,,,,,,,,2,3,4,5,,,,,2,1,,,,3,1,14,,17,
-12779028742,1,2,1,1,5,4,2,3,4,4,5,4,4,2,2,3,5,5,4,5,5,5,5,3,4,1,2,2,2,1,1,3,3,0,4,1,2,1,1,1,5,5,,,,,,,6,7,,9,,,,,,,,,4,5,,7,,9,10,,,,,,,3,,,,,,9,2,2,,,,,1,4,,11,
-12779026587,1,2,1,1,3,4,1,2,5,5,1,2,1,1,2,2,5,4,1,4,5,5,5,5,5,3,5,2,5,3,1,2,4,4,4,2,2,1,1,2,1,5,,,,,,,6,7,8,9,10,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,9,2,1,,,,3,1,0,Latin American ,5,
-12778964427,1,2,1,1,5,3,1,2,3,5,2,4,1,1,1,2,5,5,3,5,5,5,5,5,4,1,1,2,5,5,2,3,4,5,4,3,2,1,1,2,4,5,,1,,3,,5,6,7,,9,10,11,,13,,,,3,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,1,3,,11,
-12778949909,1,3,2,1,3,3,3,2,3,2,3,3,2,1,2,2,4,4,4,4,4,4,4,4,5,1,2,4,3,3,3,3,4,3,3,2,3,1,1,1,3,2,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,2,1,,,,3,1,6,,5,
-12778930881,1,2,1,1,5,5,3,1,5,5,2,4,2,1,5,4,5,5,5,2,4,4,4,3,3,2,2,4,3,5,4,3,5,5,3,3,5,1,1,2,5,2,,,2,,,5,6,7,8,9,,,,13,,,,3,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,1,15,,5,
-12778923231,1,2,1,1,3,5,5,2,2,5,1,4,2,1,2,5,1,5,2,5,4,5,4,5,5,2,2,5,5,3,1,1,3,3,2,1,2,1,1,1,3,5,,,,,,,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,1,,,1,1,,11,
-12778913188,1,3,2,1,5,5,5,4,5,5,4,5,3,1,5,4,5,5,5,5,5,5,5,5,5,4,4,5,5,4,3,3,5,5,5,4,3,2,1,4,2,1,,,,,4,5,6,7,,,10,11,,,,,,,4,5,6,,,,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,1,14,,2,
-12778904831,1,3,2,1,3,4,2,4,3,3,3,3,2,1,2,5,5,5,5,5,5,5,5,5,5,2,5,5,0,0,0,0,0,0,0,0,0,3,3,0,6,5,,,,,,,6,7,,9,,,,13,,,,,,,,7,,9,,,,,,,,,,,,,8,9,2,2,,,,,1,14,,5,
-12778876672,1,2,1,3,3,4,3,3,4,4,2,4,2,2,2,3,2,4,2,5,4,4,4,5,4,2,2,4,3,3,2,3,4,4,4,3,3,1,1,2,6,5,0,,,,,,,,,,,,,,,,,,4,5,,,,9,10,11,,,,,2,3,,,,,8,9,2,1,,,,3,1,2,,11,
-12778874917,1,3,2,1,5,5,5,3,5,5,3,3,3,1,2,2,5,5,5,5,5,5,5,5,5,3,2,4,5,5,5,5,5,5,5,,4,3,1,2,3,5,,1,,3,,5,6,7,,9,10,,,,,1,,3,,5,,7,,9,10,,,,,1,2,3,4,5,,,,,2,2,,,,,1,11,,5,
-12778867481,1,3,2,1,5,5,5,5,5,5,5,5,5,1,2,4,5,5,5,5,5,5,5,5,5,1,1,5,5,5,5,4,5,4,5,2,4,1,1,2,3,2,,1,,,,5,6,7,8,,,,,,,,,,4,,6,7,,9,10,11,,,,1,,,4,,,,,9,2,2,,,,,1,6,,1,
-12778856982,1,2,2,1,3,3,2,2,4,4,4,2,2,1,1,2,4,5,5,5,4,5,5,4,5,1,1,4,2,3,2,2,3,2,3,1,1,1,1,1,5,5,,,,3,,,6,7,,9,,,,,,,,,,,6,7,,9,10,,,,,1,,3,4,5,,,,,2,1,,,,3,1,14,,5,
-12778851143,1,2,1,1,2,3,2,1,2,5,1,3,1,1,1,2,3,4,4,4,4,4,3,5,4,3,3,2,2,4,2,2,3,4,2,3,2,1,1,1,3,2,,,2,,,,6,,,,,,,,,1,2,,,5,6,7,,9,10,,,,,1,,3,4,5,6,,,9,1,1,,,,3,1,3,,11,
-12778846959,1,2,1,1,4,4,4,2,4,4,4,2,4,2,5,1,2,5,5,2,4,4,4,1,4,3,5,5,3,5,2,1,5,5,5,2,1,1,1,2,3,4,,,2,3,,,,7,,,10,,,,,,,,,,6,7,,9,10,,,,,,,3,4,,,,,9,2,2,,,,,1,3,,11,
-12778838708,1,3,2,2,3,2,1,1,2,5,4,3,4,4,5,4,5,4,1,2,4,5,5,4,5,5,5,5,4,4,2,4,4,5,4,3,3,1,2,2,3,3,,,,3,,,6,7,8,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,1,14,,2,
-12778837811,1,3,2,1,4,2,2,2,4,4,2,1,2,1,2,4,4,4,3,5,2,5,4,2,4,2,4,5,4,3,3,4,4,4,4,2,4,1,1,3,4,2,,,,3,,5,,7,8,9,,,,,,,,3,,5,6,7,8,9,10,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,1,14,,2,
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-12769278181,1,3,3,3,4,2,2,3,4,5,5,,2,2,4,4,2,2,2,2,2,3,4,2,1,2,2,2,5,4,5,4,5,5,5,3,4,2,1,2,6,6,,,,,,,6,7,,,,,,,,,,,4,,,,,,,,,,,,,3,,,,,,9,2,2,,,,,2,14,,17,
-12769260391,1,4,3,1,5,4,3,3,5,5,3,5,3,1,2,2,5,5,4,5,5,3,5,5,5,1,2,3,3,2,2,3,3,3,2,1,3,1,1,2,5,5,,1,,3,,,,,8,9,,,12,,,1,,,,5,6,7,,,,,,,,1,2,3,,,,,,9,2,2,,,,,2,17,,5,
-12769200495,1,3,2,1,4,4,4,4,3,4,3,5,3,2,3,4,4,4,3,5,3,5,5,4,5,2,3,3,4,2,2,4,3,3,4,2,4,1,1,2,4,5,,1,,,,5,,7,,,,11,,13,,,,3,,5,6,,,,,,,,,,2,3,4,5,6,,,,2,1,,,,3,2,14,,2,
-12769185130,1,2,2,3,4,4,3,2,4,5,3,3,2,1,3,2,3,3,2,5,4,4,4,3,5,4,3,2,3,3,2,3,3,3,3,2,3,3,2,2,6,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,,,11,,,0,,,,,,,,,,2,2,,,,,1,7,,5,
-12769156592,1,4,3,1,4,2,4,2,4,4,4,4,1,1,2,4,2,5,5,5,5,5,5,5,4,2,4,5,5,3,3,3,5,5,5,2,3,1,1,1,4,3,,,,,,5,6,,8,9,,,,13,,,2,,,5,6,,8,9,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12769067309,1,3,2,1,3,5,4,2,4,3,3,2,1,1,2,2,2,3,4,4,4,2,5,1,3,2,3,1,5,4,5,3,5,5,4,2,4,1,1,1,1,5,,,,3,,5,6,7,,9,10,,,,,,,,,,,7,,9,,,,,,1,2,3,4,5,6,7,,9,2,2,,,,,2,7,,5,
-12768316286,1,4,2,1,1,2,1,1,4,2,2,2,2,1,1,1,2,2,2,1,3,5,5,1,2,4,4,2,4,2,2,4,4,2,2,2,2,1,1,1,5,5,,1,,3,4,5,6,7,,9,10,,,,,1,,3,,5,6,7,,9,10,,,,,1,2,3,4,5,6,,8,9,2,2,,,,,2,5,,1,
-12768073120,1,4,3,3,4,2,2,2,2,5,2,5,2,1,1,2,5,5,5,5,5,5,5,5,5,5,1,2,4,3,3,3,3,4,3,3,3,1,1,2,5,5,,,,3,,5,6,7,,9,10,,,13,,,2,3,,5,6,7,,9,,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,2,,11,
-12767814574,1,3,2,1,3,3,2,2,1,4,2,2,3,1,1,2,3,4,3,4,3,3,3,3,4,1,1,3,3,3,3,4,4,3,4,1,3,1,1,1,5,5,,,2,3,4,5,6,7,8,,10,,,13,,1,2,3,4,5,6,7,8,,10,,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,6,,4,
-12767785927,1,2,1,1,4,4,4,1,4,5,2,2,1,1,2,3,4,4,4,5,5,0,5,4,5,1,4,4,4,3,3,3,4,0,4,3,1,1,1,1,6,5,0,,,,,,,,,,,,,,,,,,4,5,,7,,9,,11,,13,,,,3,,,,,,9,2,2,,,,,2,9,,0,
-12767651724,1,3,2,2,2,2,1,1,3,5,2,2,2,2,2,1,5,5,2,5,5,5,5,5,5,4,5,3,5,3,3,4,5,5,5,2,2,1,3,1,6,5,,,,,,,6,7,,,,,,,,,,,,5,6,,,,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12767625379,1,4,3,1,2,2,1,2,2,2,2,3,4,3,4,3,2,2,1,4,2,2,2,4,4,5,5,4,2,1,1,2,2,2,2,2,1,2,1,1,3,3,,,,,,5,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,,3,4,5,,,,,2,1,,1,,3,2,14,,1,
-12767608164,1,4,3,1,2,3,2,3,4,5,3,4,1,1,1,3,2,5,4,5,4,3,5,5,4,3,2,4,4,4,3,3,4,4,4,2,3,2,1,1,3,4,,1,,3,,,6,7,,9,,,,,,,2,3,,,6,,,9,10,,,,,1,2,3,,,,,,,2,2,,,,,2,12,,15,
-12767484295,1,4,3,1,3,2,3,2,3,4,3,2,1,2,2,3,4,3,4,4,4,4,4,4,3,4,4,4,4,3,3,3,4,4,4,2,4,2,2,2,5,5,,,,3,,,6,7,,,,,,,,,,3,,,6,7,,,,,,13,,1,,3,4,5,,,,9,2,1,,,,3,2,2,,1,
-12767442506,1,2,2,1,3,4,2,2,3,2,3,3,1,2,4,4,3,2,2,3,2,1,1,2,1,3,5,4,4,4,2,3,3,3,4,2,3,2,1,2,5,5,,,2,,4,5,6,,,,10,11,,,,1,2,3,4,5,6,7,,9,10,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,14,,1,
-12767411842,1,2,1,2,4,5,4,2,5,5,3,4,2,1,5,2,4,5,3,5,4,3,5,5,5,2,2,2,4,3,2,3,3,4,4,1,1,1,1,3,5,5,,,,,4,5,6,7,,,10,,,,,,,,,,6,7,,,10,,,,,1,,3,4,5,,,,9,2,1,,,,3,2,7,,5,
-12767143311,1,4,3,1,4,4,2,1,2,5,2,3,1,1,2,3,5,5,5,5,5,5,5,5,2,5,5,5,4,2,3,2,4,4,4,2,3,2,4,2,5,5,,,,,,,,,,,,,,,,,2,,,5,,7,,,10,,,,,,,,4,,,,,9,2,1,,,,3,2,14,,2,
-12767130560,1,2,1,1,4,4,2,2,5,4,2,2,2,1,2,2,2,4,4,5,4,4,5,4,5,1,1,2,3,3,2,4,3,4,4,2,3,1,1,2,3,3,,,,3,,,6,7,,9,10,,,,,,2,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,,2,1,,,,3,2,14,,2,
-12766939305,1,4,3,1,4,5,3,1,5,4,2,2,2,1,5,4,4,3,2,1,4,4,4,4,5,1,5,4,4,3,2,2,4,5,2,2,1,1,1,1,3,5,,,,3,4,5,6,7,,,,,,,,,,3,,,6,7,,,,,,,,,2,3,4,,,,,9,2,1,,,,3,2,15,,5,
-12766785314,1,2,1,1,3,2,1,1,4,4,1,2,1,1,1,2,3,2,2,3,5,4,5,4,5,4,5,2,5,2,1,3,5,4,3,4,2,1,1,1,5,5,,1,,,,5,6,,,,10,,,,,1,,3,,5,6,7,8,,,,,,,1,2,3,4,5,,,,,2,2,,,,,2,7,,2,
-12766714422,1,3,2,1,2,4,4,2,2,3,2,2,2,1,1,3,3,4,3,3,4,3,3,4,5,1,1,3,3,4,3,2,4,4,4,3,3,2,1,2,3,5,,,,,,5,6,,,9,,,,,,,2,3,,5,6,,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,1,2,,5,
-12766662861,1,2,1,1,4,4,4,2,4,4,2,4,2,1,5,1,5,5,5,5,5,5,5,5,5,5,5,5,4,2,1,2,3,5,3,1,3,3,2,1,3,5,,,,,,,6,,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,1,1,,1,,,2,14,,5,
-12766445272,1,3,2,1,4,4,3,4,4,4,4,4,3,1,3,4,3,5,5,5,5,5,5,5,5,1,4,5,5,3,2,5,4,4,5,3,3,2,1,2,5,5,,1,,,,5,6,,,,,11,,,,,,,4,5,6,7,,,,11,,13,,,,3,4,,,,8,9,2,2,,,,,2,14,,2,
-12766299557,1,4,3,1,4,4,2,2,4,5,3,4,2,2,3,3,5,5,5,5,5,5,5,5,5,4,5,5,0,0,0,0,0,0,0,2,3,1,1,2,6,3,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,2,,,,,2,14,,17,
-12766294471,1,2,1,2,1,4,4,2,2,2,1,1,2,1,2,1,2,4,5,3,3,3,2,4,4,5,4,2,4,4,4,4,4,4,4,2,3,3,1,1,,5,0,,,,,,,,,,,,,,,,,3,4,5,6,7,,,,,,,,,2,3,,5,6,,,9,2,1,,,,3,2,14,,2,
-12766235825,1,4,3,1,3,4,2,2,2,5,4,5,2,1,2,4,2,2,1,2,2,3,5,4,4,1,2,5,3,4,2,2,4,3,4,3,4,1,1,2,3,4,,,2,,,5,6,7,8,9,10,,,,,1,,,4,5,,7,8,9,10,11,,,,,2,3,4,5,6,,,9,2,2,,,,,2,5,,4,
-12766192753,1,4,3,1,5,2,2,1,4,5,5,2,2,2,4,4,5,4,4,3,5,5,5,3,3,5,5,5,5,2,2,1,5,5,5,2,2,1,1,3,1,2,,,,,4,5,6,7,8,9,10,11,,13,,,2,,,5,6,7,,9,10,,,,,1,2,,4,5,6,,,9,2,2,,,,,2,14,,17,
-12766188573,1,4,3,1,2,4,1,3,3,5,2,3,4,2,3,5,4,2,1,5,2,4,3,4,5,3,5,5,4,2,2,4,2,5,5,3,4,1,1,2,5,5,,,,3,,5,6,7,,,10,,,,,,,3,,5,6,7,,,10,,,,,,,,4,5,,,,,2,1,,1,,,2,4,,11,
-12766177234,1,3,2,1,3,2,2,3,3,4,2,4,2,2,2,4,4,4,4,4,4,4,4,4,4,2,4,4,3,4,2,2,4,4,3,4,2,1,1,2,3,3,,,,,,,,7,,9,,,,,,,,3,,5,6,7,,,10,,,,,1,2,3,4,,6,,,,2,1,,,,3,2,0,,11,
-12766113514,1,4,3,1,4,4,2,4,3,4,2,2,1,1,3,4,5,5,4,4,4,5,5,4,4,2,2,2,4,3,2,4,5,5,5,2,2,1,1,1,4,5,,1,,3,,5,6,7,,9,,,,,,,,3,,5,6,7,,9,,,,,,,2,3,4,5,,,,,2,1,,1,,,2,14,,17,
-12766055917,1,2,2,1,2,2,2,2,2,2,2,1,2,5,5,4,4,2,4,3,4,4,5,1,5,5,5,5,5,3,5,5,3,5,5,3,4,1,1,3,3,3,,1,,,,,6,7,,,,,,,,,,,4,5,6,,,,,,,,,,,,4,5,,,,9,2,1,,1,,,1,4,,11,
-12765948691,1,2,1,1,5,3,2,2,4,3,2,2,2,4,4,3,5,5,5,2,5,5,5,2,2,5,5,5,0,4,0,2,0,0,3,1,2,1,2,3,5,5,0,,,,,,,,,,,,,,,1,,,,,6,7,,9,,,,13,0,,,,,,,,,,2,1,,,,3,2,8,,5,
-12765884852,1,4,3,1,2,2,2,2,3,2,2,2,2,2,2,2,2,4,2,2,4,4,4,2,2,4,2,3,3,3,2,3,4,4,4,2,2,1,1,1,5,3,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,2,,5,
-12765686033,1,2,1,2,5,2,2,2,4,4,4,2,2,2,5,4,4,2,1,4,4,5,5,2,1,5,5,5,4,3,3,2,4,4,3,2,1,2,2,1,5,5,,1,,3,4,,6,7,,,,,,,,,,3,,,6,7,,9,,,,,,1,,3,4,5,,,,,2,2,,,,,2,14,,2,
-12765597735,1,2,1,1,5,5,3,2,5,5,5,5,3,2,3,3,5,5,2,3,5,5,5,5,5,2,2,4,4,3,3,3,4,4,4,3,3,2,1,2,5,3,,,,3,,5,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,2,3,,,6,,,9,2,1,,,,3,1,5,,1,
-12765568771,1,2,1,1,2,3,1,2,3,4,3,2,2,2,4,3,4,3,1,3,5,5,4,3,4,5,5,4,3,3,3,2,4,5,3,2,2,2,1,1,1,2,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,1,2,3,4,5,,,,,2,2,,,,,2,5,,5,
-12765460306,1,3,2,2,5,5,5,2,5,5,5,5,5,5,2,5,5,2,2,5,5,5,5,5,5,5,5,5,4,2,2,3,3,3,3,2,4,1,1,2,5,5,,,,,,,6,,,,,,,,,,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,7,,5,
-12765455607,1,4,3,1,4,4,4,4,3,5,3,3,3,1,2,3,4,4,4,4,4,4,4,4,3,1,2,4,3,2,2,3,3,3,3,2,2,1,1,1,3,3,,1,,,4,,,7,,9,10,11,,,,,,,,5,,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,1,,,1,5,,4,
-12765415517,1,3,2,1,2,2,2,2,2,5,2,4,2,4,2,4,5,5,2,5,5,5,5,4,5,5,5,5,3,2,1,2,4,3,3,2,2,2,2,2,4,5,,,,,,,6,7,,9,10,,,,,,,,,5,6,7,,9,,,,,,,,3,4,5,,,,9,1,1,,,,3,2,2,,11,
-12765382154,1,3,2,1,2,2,2,1,4,4,1,3,2,1,5,4,3,4,3,5,3,4,2,4,5,2,5,5,5,,2,3,4,3,4,2,2,2,2,,4,5,,,,,,5,6,7,,9,,,,,,,2,,,5,6,7,,,,,,,,,2,3,4,5,6,,8,,2,1,,,,3,2,14,,5,
-12765335216,1,2,1,1,5,5,4,4,5,5,1,4,1,1,1,3,5,5,4,5,5,5,5,5,5,3,4,5,2,4,3,2,3,3,5,3,2,1,1,1,1,2,,,,3,4,5,6,7,,,10,11,,,,,2,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,5,
-12765331725,1,3,2,1,4,4,4,4,4,4,4,4,2,2,2,2,,,,,,,,,,,2,2,3,5,1,3,5,5,5,3,3,1,1,1,1,5,,1,,3,,,6,7,,,,,,,,1,,3,,,6,,,,,11,,,,1,,3,,5,6,,,9,2,2,,,,,1,12,,5,
-12765242216,1,4,3,2,3,3,2,2,2,3,2,3,1,1,2,2,3,3,4,4,3,3,4,5,5,3,4,3,3,3,,2,3,0,4,3,1,2,3,1,6,5,0,,,,,,,,,,,,,,,,2,,,,,7,8,9,,,,,,,,3,,,,,,9,2,1,,,,3,2,14,,2,
-12765207636,1,2,2,1,3,2,2,4,4,2,3,2,2,1,1,1,2,4,4,5,3,5,5,1,1,1,1,3,3,2,2,4,4,4,5,1,1,1,1,1,5,2,,1,2,3,4,5,6,7,8,9,10,11,12,13,,,,3,4,,6,,,9,10,,,,,1,2,3,4,5,,,,,2,2,,,,,2,2,,14,
-12764999343,1,3,2,1,3,3,3,3,4,5,5,4,1,2,1,2,3,4,4,5,4,4,5,5,2,2,1,2,,3,,4,3,0,4,4,3,2,1,1,6,2,0,,,,,,,,,,,,,,,,2,,,5,6,,,9,10,,,,,,,,,,,,,,2,2,,,,,2,2,,9,
-12764934227,1,4,2,1,3,4,2,2,3,,4,4,2,2,2,2,5,5,2,5,3,5,5,5,2,4,2,2,0,0,3,0,0,0,0,2,3,2,1,1,5,5,,,,3,,5,,7,8,,10,,,,,1,,,4,5,6,7,,9,,,,,,,,,,,,,,9,2,2,,,,,2,6,,11,
-12764398495,1,3,2,2,2,2,1,2,2,4,2,2,2,1,2,2,4,4,2,5,4,5,4,5,4,5,5,5,3,4,2,3,4,4,3,2,2,3,1,1,4,3,,,,3,,,6,7,,9,10,,,,,,,,,5,6,7,,9,,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,14,,15,
-12764391807,1,3,2,1,4,4,4,4,4,4,4,4,4,1,2,4,4,5,5,5,3,5,3,3,5,1,2,4,3,3,3,4,4,4,2,3,4,1,1,1,5,5,,,,,4,5,6,7,,,10,,,,,1,,,4,5,6,7,,9,10,,,13,,1,2,3,4,5,6,7,8,9,2,1,,,,3,1,7,,1,
-12764374470,1,2,1,1,5,5,3,2,0,5,2,5,2,1,1,2,5,5,5,5,5,5,5,5,5,1,5,2,0,3,4,4,5,0,4,2,2,1,1,1,5,5,,,2,,,5,6,7,8,,10,,,13,,1,,,,5,6,7,,9,,,,13,,,,3,4,5,,,,9,2,1,,,,3,2,2,,9,
-12764341691,1,2,3,2,4,4,4,2,4,4,2,2,4,1,1,2,5,5,5,5,5,5,5,5,5,2,2,5,3,3,2,3,4,4,3,3,3,2,1,2,2,2,,1,,,4,5,,7,,,,,,,,1,,3,,5,6,7,,,10,11,,,,,,3,4,5,6,,,,2,2,,,,,2,17,,5,
-12764284385,1,4,3,1,4,1,4,1,2,3,2,1,1,1,3,1,2,2,2,2,5,5,4,1,2,5,5,2,,,,,,,,,,,,,6,4,0,,,,,,,,,,,,,,,1,,3,,5,6,7,,9,,,,,,1,2,,,,6,,,9,2,1,,,,3,2,7,,5,
-12764278104,1,2,2,2,3,2,2,2,3,4,3,2,2,2,2,3,4,3,4,1,4,3,4,3,3,4,4,3,4,4,3,3,4,4,4,3,3,2,1,2,3,5,,,2,3,4,5,6,7,,,10,,,,,,,3,,5,6,7,,,,,,,,1,2,3,4,5,,,,,2,2,,,,,2,14,,15,
-12764152925,1,2,1,1,3,2,1,2,4,4,3,2,2,2,2,1,4,4,1,4,4,4,4,1,4,4,4,2,3,2,1,2,3,2,2,1,2,1,1,2,5,5,,1,,3,4,5,6,7,8,,10,,,13,,1,2,3,4,5,6,7,8,,10,11,12,13,,1,2,3,4,5,6,7,8,9,2,2,,,,,2,3,,11,
-12764104741,1,4,3,1,1,4,1,4,3,3,2,4,2,3,4,4,4,4,3,4,4,4,4,4,4,4,4,4,4,3,3,3,4,3,4,1,4,3,1,3,5,5,,,,,,,6,7,,,,11,12,,,1,,,,,6,7,,,,11,,,,,2,3,4,5,6,,,9,2,1,,1,,,2,0,,11,
-12764004595,1,3,2,1,3,3,3,2,4,4,2,2,3,1,2,2,5,4,4,4,5,4,4,4,5,2,1,4,3,3,2,2,3,3,3,2,4,1,1,2,5,5,,1,,3,,,6,7,,,,11,,,,1,,,4,5,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,17,
-12763995343,1,2,1,2,4,2,5,1,4,5,2,4,1,2,4,1,1,1,2,1,2,3,2,2,2,5,1,1,4,2,2,1,4,3,4,3,3,1,1,1,5,5,,,,3,4,,6,7,,9,,,,,,,,3,4,5,6,7,,9,10,11,,,,,2,3,4,5,,,,9,2,1,,,,3,4,0,,2,
-12763990985,1,3,2,1,1,4,2,1,1,2,1,1,1,4,4,4,2,4,2,1,2,2,2,2,1,4,4,4,4,5,4,3,5,4,4,1,2,2,1,1,5,5,,,2,3,,5,6,7,,,10,11,,,,,,3,4,5,,7,,,10,,,,,1,2,3,,,6,,,,2,1,,1,,,2,14,,1,
-12763946483,1,3,2,1,5,5,1,2,4,4,2,2,2,1,4,4,4,4,2,4,4,4,3,5,4,4,5,4,3,3,1,3,2,3,2,1,2,3,1,1,3,5,,,,,,,6,7,,,,,,,,1,,,4,5,6,7,,,,,,,,,,3,4,5,,,,,2,1,,1,,,2,14,,5,
-12763935995,1,2,1,1,1,3,3,2,2,2,2,3,2,1,2,3,1,4,2,3,3,4,4,4,2,1,3,3,3,2,3,2,3,5,3,2,1,1,1,1,3,5,,,2,,,5,6,7,,9,,,,,,,2,,4,,6,7,,9,10,,,,,1,2,3,4,5,,,8,9,2,1,,,,3,1,17,,8,
-12763854878,1,3,2,1,2,3,2,1,1,2,1,1,,1,3,1,2,5,5,5,5,5,5,5,5,4,3,5,2,3,2,4,4,3,5,4,2,1,1,2,5,5,,1,,,,5,6,7,8,9,10,,,,,,,,,,6,,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,4,0,,0,
-12763844230,1,3,2,1,3,3,1,1,3,3,2,2,1,1,1,2,4,3,1,4,3,4,3,4,2,1,4,4,,3,1,3,3,3,3,2,1,1,1,1,6,6,,1,,3,,,,7,,9,,11,,,,,,,,,,7,,,,,,,,,,3,4,5,6,,,9,2,1,,,,3,2,3,,11,
-12763815497,1,3,3,1,3,5,5,1,4,2,3,3,1,1,5,4,1,5,5,1,4,2,4,2,2,1,3,4,5,4,2,5,5,5,5,3,3,2,1,1,5,5,,,,,4,5,6,7,,9,10,,,,,,,,4,5,6,7,8,9,10,,,,,1,,3,,,,,,9,2,2,,,,,1,3,,11,
-12763805308,1,4,3,1,5,3,2,1,4,5,2,3,1,1,3,3,3,3,3,1,2,3,5,3,3,5,4,4,5,5,3,5,5,5,5,5,5,1,1,3,3,2,,1,2,3,,5,,,,,,,,,,,,3,,5,6,7,,,,,,,,,,3,4,,,,,,2,1,,,,3,2,2,,0,
-12763789958,1,2,3,1,4,2,4,2,4,4,4,2,2,2,3,3,4,2,4,4,4,4,4,2,4,4,5,5,3,2,3,3,3,3,4,2,2,3,1,2,3,2,,,,,,,6,7,,9,10,,,,,,,,,,,7,,9,10,,,,,,,,4,5,,,,9,2,2,,,,,2,17,,2,
-12763760217,1,2,1,1,4,4,4,2,3,2,1,4,1,2,3,3,5,5,5,5,5,5,5,5,2,2,5,5,4,4,3,2,3,3,5,2,2,1,1,2,3,3,,1,,3,,,,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,9,2,1,,,,3,2,17,,5,
-12763721959,1,3,3,1,3,1,3,1,3,3,3,3,3,3,3,1,2,1,2,1,2,3,3,1,4,5,2,1,3,3,2,3,3,3,3,1,3,1,1,1,1,3,,,,,,,6,,8,9,,11,,,,,,,,5,6,7,,9,,,,,,,,3,4,5,,,,9,2,2,,,,,2,17,,5,
-12763719434,1,3,2,2,5,5,5,2,5,5,5,1,2,5,5,1,5,5,5,4,5,5,5,1,2,5,5,1,4,4,4,4,4,4,4,3,2,1,1,1,6,4,,1,,3,4,5,6,7,,9,10,11,,13,,1,,,4,5,6,7,,9,10,11,,,,1,2,3,4,5,,,8,9,2,1,,,,3,2,14,,0,
-12763712915,1,4,3,1,3,3,3,2,4,3,3,3,2,2,2,2,4,5,4,2,4,5,4,3,5,3,3,2,4,4,3,2,4,4,4,2,3,1,1,3,2,2,,,,,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12763702856,1,4,3,1,4,4,4,1,4,4,4,1,2,2,4,3,5,3,3,5,5,5,5,5,5,5,5,5,5,4,2,5,5,4,5,4,3,2,1,1,3,2,,,,,,,,7,8,9,10,,,,,,,,,,6,7,,9,10,,,,,,,3,,,,,,9,2,2,,,,,2,14,,2,
-12763683560,1,2,1,2,5,2,4,4,4,4,5,2,3,5,3,4,5,2,4,4,2,5,5,1,4,2,3,3,5,1,2,2,4,4,5,3,3,1,2,1,3,4,,,,,,5,6,7,,9,10,,,,,,2,,,,6,7,,9,10,,,,,,2,3,4,,,,,,2,2,,,,,1,14,,1,
-12763673795,1,2,1,1,1,1,1,1,3,3,3,3,1,1,1,1,1,4,1,1,5,5,5,5,1,5,5,4,4,3,1,2,5,3,4,1,1,2,1,1,3,2,,,,3,,,6,,8,,10,,,,,,,3,,,6,,8,,,,,,,1,2,,4,5,6,,,,2,2,,,,,2,2,,9,
-12763663431,1,2,1,1,3,1,1,1,3,3,3,2,2,2,2,2,4,1,2,1,2,4,4,2,4,5,3,1,3,1,1,1,2,3,1,2,1,1,1,1,5,5,,1,,3,4,5,6,7,,,,,,13,,,,3,4,5,6,7,,,,11,,,,,2,3,4,5,6,,8,9,2,1,,,,3,2,3,,11,
-12763656564,1,2,1,2,2,2,2,2,3,3,2,3,2,3,1,1,2,2,2,5,3,2,3,4,2,5,2,3,4,3,3,3,4,4,5,4,2,2,2,3,5,5,,1,2,3,4,5,6,7,,9,10,11,,13,,,2,3,,5,6,7,,9,,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12763654307,1,3,3,1,2,2,2,1,2,3,1,2,1,1,4,3,2,5,4,1,5,3,3,5,2,5,5,5,4,2,3,1,4,4,4,4,1,2,2,2,3,3,,,,3,,,6,,,9,,,,,,,,3,,5,6,,,9,,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,1,
-12763652479,1,2,1,1,3,1,2,1,2,4,2,3,2,2,2,3,2,2,2,2,4,4,5,5,5,5,4,2,4,1,1,1,4,3,2,3,1,1,1,1,5,5,,1,,3,4,5,6,7,,,10,11,,,,1,,3,4,,6,7,,9,,,,,,,,3,4,5,6,,,9,2,1,,,,3,2,3,,11,
-12763638808,1,2,1,1,4,3,4,2,4,5,3,3,2,1,5,2,4,3,4,2,4,4,4,4,4,4,4,4,3,2,2,2,2,4,2,3,3,3,1,1,4,4,,,,3,4,,6,7,,,,,,,,1,,,4,5,,7,,,,,,,,,,,,5,6,,,9,2,2,,,,,2,14,,5,
-12763616380,1,4,3,1,4,4,4,2,4,4,4,4,2,1,4,4,2,3,2,2,3,3,4,3,2,1,1,4,5,5,4,3,5,5,5,2,5,1,1,3,2,1,,1,,3,4,5,,7,,,,,,,0,,,,,,,,,,,,,,,1,2,3,,5,6,,,9,2,2,,,,,2,17,,17,
-12763594066,1,4,3,1,2,2,2,2,5,4,4,2,2,3,3,2,3,2,4,2,3,2,2,3,3,5,4,1,3,2,2,3,3,4,3,3,4,1,1,2,3,4,,1,,3,,5,6,7,,,10,11,,,,,,3,4,5,6,7,,,,11,12,,,1,2,3,4,5,6,7,8,9,2,2,,,,,1,0,Kurdish,0,Theist
-12763574889,1,3,2,1,1,4,4,1,1,5,1,4,1,1,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,2,2,3,2,2,3,2,2,1,1,1,5,5,,,,,,,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,,,3,4,5,,,,,2,1,,1,,,2,14,,5,
-12763558079,1,2,1,1,2,2,2,2,1,4,1,1,2,1,1,3,4,5,5,5,5,5,5,2,5,1,1,5,3,2,2,3,2,0,5,1,4,1,1,2,3,5,,1,,3,4,5,6,7,,,10,,,,,,2,,4,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,2,
-12763479209,1,4,3,1,1,2,1,2,2,2,1,2,2,1,2,3,4,4,2,5,5,4,4,5,5,1,4,5,4,3,3,4,3,4,4,1,2,1,1,1,5,5,,,,,4,5,6,7,,9,10,,,,,,,3,4,5,,7,,,10,11,,,,,,3,4,5,,,,9,2,1,,1,,,2,14,,5,
-12763458408,1,4,3,1,2,1,2,1,2,2,2,1,1,1,2,3,3,3,4,4,2,4,2,2,4,5,3,5,4,2,1,2,3,4,4,1,1,1,2,1,5,5,,,,3,,5,6,7,8,9,,,,,,,2,3,,5,6,7,8,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,14,,5,
-12763438868,1,4,3,1,3,3,1,2,2,4,3,2,1,1,2,1,3,3,2,5,3,3,5,5,4,4,5,3,3,4,4,5,3,3,5,3,4,3,2,3,3,5,,,,,,,6,7,,,,,,,,1,,,,5,6,,,,,11,,13,,1,,3,,5,,7,,,2,2,,,,,2,2,,9,
-12763392299,1,2,1,1,5,4,2,1,4,5,2,1,1,2,2,2,4,5,5,2,4,5,4,1,1,4,5,4,4,3,3,1,4,4,3,1,2,1,2,2,3,5,,1,2,3,4,5,6,7,,,,,,,,,,3,4,5,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,5,
-12763367252,1,4,3,1,4,4,1,4,4,4,4,4,4,1,4,4,2,4,1,5,4,5,5,4,5,5,3,4,5,5,3,5,5,5,5,5,5,2,1,3,1,1,,,,3,4,5,6,7,,9,,,,,,,,3,4,5,6,7,,9,10,11,,,,1,2,3,,5,,,,,2,1,,,,3,2,17,,1,
-12763338252,1,2,1,2,2,3,1,2,2,3,2,2,1,4,4,3,3,2,1,2,2,3,4,1,1,4,4,3,3,3,3,3,4,4,4,3,2,2,1,2,3,4,,,,3,,,6,7,,,,,,,,,,,,5,6,7,,9,,,,,,,,3,4,5,,,,9,2,1,,,2,3,1,14,,17,
-12763334960,1,3,3,1,2,5,2,1,5,4,2,2,1,1,2,5,1,4,4,4,4,2,5,5,1,2,5,5,3,3,1,2,3,3,3,3,3,1,1,1,4,4,,1,2,3,4,5,6,7,8,9,10,,,13,,1,2,,,5,6,7,,9,10,11,,13,,1,2,3,4,5,6,,8,9,2,2,,,,,2,14,,5,
-12763314414,1,4,3,1,3,4,2,2,2,5,2,2,5,1,1,2,4,5,5,5,3,5,3,3,5,1,1,2,2,3,3,2,3,3,3,3,1,1,1,3,3,5,,,2,,,5,6,,,,10,,,,,,,,,5,6,7,,,,,,,,,,,4,5,,,,9,2,1,,,,3,2,12,,12,
-12763305224,1,2,1,1,5,5,3,4,5,5,4,5,2,3,5,5,3,3,2,5,4,3,4,4,2,5,5,4,0,0,2,3,4,0,4,3,1,1,3,1,5,5,0,,,,,,,,,,,,,,,,,,,5,6,7,8,,10,,,,,,2,3,4,5,6,,,,2,1,,,,3,2,14,,17,
-12763278605,1,3,2,1,2,2,2,1,2,2,2,2,1,2,2,2,5,5,3,2,5,5,5,5,2,5,5,4,5,4,5,2,5,5,5,5,2,2,1,2,3,1,,1,,,4,,6,7,,,,,,,,,,3,4,,6,7,,,,,,,,1,,3,,5,,,,9,2,1,,,2,,2,14,,17,
-12763278046,1,3,3,1,3,3,2,1,5,5,3,4,2,1,4,2,3,3,1,3,2,4,4,2,3,1,2,2,1,3,1,2,3,4,3,2,1,1,1,1,4,5,,,,3,,5,6,,8,9,10,,,,,,,,,5,,7,8,9,,,,13,,1,2,3,,,6,,,9,2,2,,,,,2,13,,17,
-12763273650,1,3,3,1,3,4,4,1,4,4,2,3,2,2,4,5,3,4,4,3,4,4,4,3,3,4,4,4,4,4,3,3,4,3,3,2,3,2,1,2,4,3,,,2,,4,5,6,,,9,10,,,,,,,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,1,,,,3,1,14,,17,
-12763268597,1,2,1,1,3,3,1,2,5,3,2,3,2,1,3,1,0,2,3,0,5,3,5,0,2,2,5,2,2,4,4,2,4,4,4,3,1,1,1,2,3,3,,,,3,,,6,7,,,10,,,,,,,,,,6,7,,,,,,13,,,,3,4,,6,,,9,2,2,,,,,2,6,,11,
-12763249317,1,3,3,1,3,2,1,1,4,3,2,2,1,1,2,2,2,2,2,1,3,4,3,1,1,2,5,5,5,5,2,3,5,5,5,3,3,1,1,2,5,5,,,,,,,6,7,,,,,,,,,,,,5,6,7,,,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,1,
-12763214157,1,2,1,2,2,4,2,1,2,4,1,2,1,1,2,4,4,4,4,4,4,4,4,4,4,5,5,4,2,3,2,3,3,3,4,1,1,2,1,1,3,3,0,,,,,,,,,,,,,,,,,,4,,6,7,,9,10,11,,,,1,2,,4,5,,,,9,2,1,,,,3,2,7,,15,
-12763205670,1,4,3,1,3,3,3,3,3,3,2,3,2,1,3,1,5,5,5,5,5,5,5,5,5,1,5,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,,1,,,,,6,7,,,10,,,13,,,,,,,6,,8,9,,,,,,,,3,4,5,,,,9,2,1,,,,3,1,14,,0,
-12763169533,1,3,2,2,5,5,4,5,5,5,5,5,5,5,5,5,5,5,2,5,5,5,5,5,5,5,5,5,5,5,4,5,5,5,5,3,5,5,5,5,2,2,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,2,1,,,,3,1,14,,17,
-12763167918,1,3,2,1,3,2,1,1,4,5,2,2,1,1,2,4,3,2,2,5,4,3,3,3,5,4,5,5,4,4,1,1,4,4,1,1,1,1,3,1,3,5,,,,,,5,6,7,,,,,,,,,,3,,5,6,7,,,,11,,,,1,,3,4,5,,,,,2,2,,,,,2,14,,1,
-12763143324,1,3,2,2,3,2,1,3,2,3,2,3,1,5,5,4,4,3,2,4,4,4,4,4,3,5,4,4,3,2,2,1,3,3,3,2,1,1,1,1,5,5,,,,3,,,6,,,,10,11,,,,,2,3,,5,6,,8,9,10,,,,,,,3,4,5,6,,,9,2,1,,1,,,2,14,,2,
-12763131348,1,4,3,2,3,2,1,3,3,4,2,,2,2,5,5,4,4,2,4,4,4,5,4,5,5,5,4,4,3,1,3,3,4,3,2,3,2,1,1,6,5,0,,,,,,,,,,,,,,,,,3,4,5,,7,,,,,,,,,2,3,,,,,,,2,1,,,,3,2,14,,17,
-12763095298,1,2,1,1,2,2,2,2,2,2,2,3,2,2,4,2,1,3,2,4,2,1,1,3,2,5,4,4,4,5,3,4,3,3,4,4,4,2,1,4,5,5,,,2,3,4,5,6,7,8,,10,11,,13,,,2,3,4,5,6,7,8,9,10,11,,13,,1,2,3,4,5,6,,8,9,1,1,,,,3,2,10,,5,
-12763035737,1,4,3,1,3,4,4,2,2,5,3,4,2,1,4,4,1,3,1,1,1,4,3,1,1,1,1,2,3,3,2,3,3,3,3,1,2,2,1,1,5,5,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,,4,5,,,,,2,2,,,,,2,5,,17,
-12763006666,1,4,3,1,4,2,2,2,4,5,2,4,1,1,2,2,5,2,2,4,4,3,5,4,2,4,2,2,4,1,1,3,4,4,4,3,2,2,1,1,5,5,,,,,,,6,7,,,10,,,,,,,,,,,,,,10,,,,,,2,3,,,,,,9,2,2,,,,,2,17,,17,
-12762974565,1,4,3,2,2,2,1,2,2,2,2,3,1,2,4,4,1,5,1,2,1,2,3,3,1,4,5,4,4,5,5,3,4,3,4,3,2,1,1,4,3,4,,1,,,,5,6,7,8,9,10,,,,,1,,3,4,,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,1,,3,2,14,,5,
-12762966135,1,3,2,1,5,3,1,2,5,5,4,4,2,2,2,3,3,2,1,3,3,4,5,3,4,4,4,5,4,3,3,2,3,3,3,2,3,2,1,1,4,3,,,2,3,4,5,6,7,,9,10,11,,,,,,3,4,5,6,7,,9,,11,,,,,2,3,4,5,,,,9,2,2,,,,,3,2,,2,
-12762941389,1,2,1,1,5,5,5,5,1,5,4,5,5,1,1,3,5,5,3,5,5,5,5,4,4,1,2,2,3,3,2,4,3,3,3,4,3,1,1,2,3,2,,1,2,,4,,6,7,,9,10,,,,,,,,,,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,1,,1,2,,2,3,,11,
-12762921608,1,2,1,1,3,3,2,2,3,3,2,3,2,2,2,3,2,2,2,2,2,3,3,2,2,4,3,3,3,3,3,3,3,3,3,3,3,1,1,1,4,4,,,,3,,5,6,7,,,,11,,,,1,,3,,5,6,7,8,,,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,2,,5,
-12762888773,1,2,1,2,2,,1,2,3,2,2,3,2,3,2,4,3,3,1,5,2,3,3,2,1,5,5,5,4,3,1,3,2,2,2,2,2,1,1,3,5,5,0,,,,,,,,,,,,,,,1,,3,4,5,6,7,,9,10,11,,13,,1,2,3,4,5,6,7,,9,2,1,,,,3,2,4,,1,
-12762870081,1,2,1,1,4,2,1,2,5,5,4,4,1,1,4,1,2,2,2,3,2,0,4,1,5,5,5,4,4,4,2,3,5,5,5,2,4,1,1,2,5,5,,,,3,,5,6,7,,9,,,,,,,,3,,5,6,,,9,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,10,,17,
-12762868265,1,2,1,1,5,4,2,4,5,5,5,4,2,5,4,2,5,5,2,5,5,5,5,5,5,5,5,5,5,2,2,4,5,5,5,1,4,2,1,2,4,5,,,,3,4,5,6,7,,,10,11,,,,,,3,4,5,6,7,,,10,11,,13,,1,2,3,4,5,6,,,9,2,2,,,,,2,10,,17,
-12762858013,1,4,3,2,5,5,3,3,4,5,2,3,3,2,3,2,2,5,3,3,4,5,3,5,5,2,3,2,0,2,3,3,0,3,3,1,3,1,1,1,6,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,9,,11,,13,,,2,3,,5,,,,9,2,1,,1,,3,2,3,,11,
-12762819814,1,3,2,1,2,1,1,1,2,3,1,2,1,4,4,3,1,1,4,1,1,1,1,2,4,4,4,4,4,3,4,3,3,3,3,4,3,2,2,2,5,5,,1,,3,,5,6,7,,,,,,,,,2,3,4,5,6,7,,9,,11,12,13,,,2,3,4,5,,,,9,2,2,,,,,2,10,,15,
-12762770519,1,3,2,3,2,3,2,2,2,4,2,1,2,2,2,1,5,5,5,5,5,5,5,2,5,5,5,2,3,4,3,4,4,5,4,3,3,2,1,2,5,5,,1,,,,5,,7,8,9,10,,,13,,1,,,,5,6,7,,9,10,,,,,,,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12762761109,1,2,2,1,4,5,2,3,4,5,3,5,4,2,4,4,5,5,4,4,5,5,5,5,5,5,5,5,3,3,2,3,4,3,4,2,3,2,1,1,5,5,0,,,,,,,,,,,,,,,,,,,,6,7,,9,,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,5,
-12762758514,1,3,3,2,1,3,3,3,1,1,1,2,1,3,2,1,1,4,4,1,1,1,1,4,1,5,4,1,1,1,1,1,1,1,1,1,1,1,1,1,5,5,,,,,,5,6,7,,9,,11,,,,,,,4,5,6,7,,9,,11,,,,1,2,3,4,5,6,,,9,1,1,,1,,,2,3,,11,
-12762743083,1,2,1,1,2,4,1,4,1,2,2,4,1,2,4,4,2,3,2,5,2,2,2,2,1,4,4,4,4,2,2,3,4,4,4,1,3,1,1,3,4,4,,,,,,5,6,7,,,10,11,,13,,,,3,,5,6,7,,,10,,,,,1,2,3,4,5,6,,,9,2,1,,1,,,2,2,,2,
-12762732125,1,4,3,1,3,3,2,2,3,3,4,3,2,2,2,4,2,2,2,2,2,4,4,2,3,4,4,4,4,1,1,3,4,4,3,4,4,1,1,2,4,3,,,,,,5,6,7,8,,10,,,,,,,,4,5,6,7,8,,10,,,,,1,2,3,4,5,6,7,,9,2,2,,,,,2,14,,17,
-12762725067,1,4,3,1,5,4,4,3,4,4,2,3,2,1,3,2,2,4,2,4,3,3,2,2,4,1,2,1,4,4,2,3,3,4,3,1,1,1,1,2,5,5,,1,2,3,4,5,6,7,,,10,11,,13,,,,3,4,5,6,7,,,,11,,13,,1,2,3,4,5,,,8,9,2,1,,1,,,2,14,,5,
-12762697201,1,4,3,1,3,3,2,2,3,3,2,2,2,1,1,1,4,5,4,4,4,3,5,2,5,1,2,1,3,2,1,4,3,5,4,2,3,1,1,2,2,2,,,,,,5,6,7,,9,,,,,,1,,3,4,5,6,7,,9,,,,,,1,2,3,4,,,,,9,2,2,,,,,1,14,,17,
-12762689225,1,4,3,1,2,4,2,2,3,5,2,2,2,2,3,5,4,3,2,3,4,3,4,5,2,4,5,4,4,4,3,3,4,5,4,4,3,2,2,3,5,5,,1,2,,4,5,,7,,,,11,,,,1,,3,4,5,6,7,,,10,,,,,1,2,3,4,5,,,8,9,2,1,,,,3,2,14,,17,
-12762677035,1,3,2,1,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,1,2,5,5,5,1,3,1,1,1,3,3,,,,,,5,6,,,,10,,,,,,,,,,,7,,9,,,,,,,,,4,,,,,,2,2,,,,,2,2,,16,
-12762663007,1,3,2,2,3,1,1,1,3,0,4,3,2,1,2,4,2,4,1,1,2,3,5,1,4,0,2,4,5,3,2,4,4,3,4,2,3,1,2,1,6,4,,,2,3,,5,6,7,,9,10,11,,,,,2,3,4,,6,7,,9,10,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,1,7,,0,Apatheistic 
-12762649984,1,3,2,1,1,2,2,1,1,1,1,2,1,3,2,3,2,5,4,2,2,3,2,3,1,5,5,5,2,3,2,2,2,2,2,2,2,1,1,1,4,4,,,2,,,5,6,7,,9,10,,,,,,2,,,5,6,7,,,10,,,,,1,2,3,4,5,,,,,1,1,,1,,,2,14,,2,
-12762636233,1,4,3,1,0,0,0,2,5,4,4,5,3,1,1,0,5,4,4,2,5,4,0,5,5,1,1,3,4,5,3,4,5,5,5,3,4,1,1,2,4,4,,1,,3,,5,6,7,,,10,,,,,,,3,4,,6,7,,,,,12,,,1,2,3,4,5,6,,,,2,1,,,,3,1,6,,5,
-12762627245,1,3,2,2,4,4,4,4,4,4,4,2,4,2,4,3,5,4,3,5,4,4,5,2,5,3,5,2,3,2,2,4,4,4,3,2,4,2,1,2,5,5,,,2,3,,5,6,7,,9,10,,,,,,,,,5,,7,,,10,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12762626831,1,2,1,1,1,4,1,1,3,1,1,2,1,1,1,2,2,3,2,2,3,2,3,3,1,1,1,3,2,3,1,3,3,3,3,2,1,1,1,1,4,4,,,2,,,5,6,7,,9,10,,,,,,,3,,5,6,7,,9,10,,,13,,1,2,3,,5,6,,,9,2,2,,,,,2,4,,11,
-12762626575,1,2,1,1,2,3,1,1,5,2,2,4,2,2,3,4,5,4,2,1,5,4,4,3,5,5,5,5,3,2,3,4,3,3,4,2,1,1,1,1,5,5,,,,,,,6,7,,,10,,,,,,,,,5,6,7,,,,11,,,,,,3,,5,,,,9,2,1,,,,3,2,14,,5,
-12762624198,1,3,2,1,2,2,2,2,2,4,4,2,4,2,5,5,2,2,4,5,5,4,4,5,5,5,5,5,4,3,2,4,3,,4,3,3,1,1,2,3,4,,,,,,5,6,,8,9,10,,,,,,,,,5,6,7,,9,10,,,,,1,,3,,5,6,,,9,2,2,,,,,1,15,,5,
-12762622168,1,3,2,1,3,2,2,2,3,3,2,4,3,2,4,1,4,4,3,4,3,4,4,4,5,3,3,1,4,3,1,3,4,4,3,1,3,1,1,1,4,5,,,,,,5,6,7,8,9,10,,,,,1,,3,4,5,6,7,8,9,10,11,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,3,,11,
-12762611787,1,4,3,2,4,4,2,2,4,5,2,4,1,1,4,1,2,4,4,4,4,5,5,4,2,4,5,1,5,4,3,5,4,3,4,2,2,1,1,1,2,2,,1,,3,,5,6,7,,,,11,,,,,,3,4,5,6,7,,9,,11,,,,,,3,4,5,,,,9,2,1,,,,3,2,14,,5,
-12762608631,1,4,3,1,4,2,1,2,4,4,2,4,2,2,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,3,1,5,4,5,5,2,5,3,2,1,5,5,,,2,,,5,6,7,8,9,10,,,,,,,,4,5,,7,,9,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12762607888,1,4,3,1,2,4,2,2,2,2,2,2,1,2,1,2,5,5,5,5,5,5,5,5,1,5,4,5,3,3,2,3,3,3,3,3,3,2,1,2,5,5,,,,,,5,6,7,,9,10,,,13,,,2,,4,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12762600982,1,4,3,1,1,2,1,1,2,1,1,2,1,1,3,2,2,3,2,2,3,2,2,4,1,5,5,5,5,2,1,3,5,3,4,3,4,2,2,1,4,5,,,2,,,5,6,7,,9,10,,,,,,2,3,4,5,6,7,8,9,10,,,13,,1,2,3,4,5,,,,9,2,1,,1,,3,2,14,,1,
-12762595696,1,2,1,2,1,2,1,2,4,3,3,3,1,5,5,3,4,1,1,4,3,3,3,3,1,5,5,2,3,2,1,2,3,3,3,1,1,1,1,1,5,5,,1,2,3,,5,6,7,8,9,10,,,,,1,2,3,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,2,,7,
-12762583762,1,4,3,1,2,4,3,1,3,2,1,1,1,1,1,1,2,3,4,4,3,5,4,3,5,4,1,3,5,4,3,4,5,5,5,4,3,2,1,1,3,5,,,,,,,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,2,3,,,,,,,2,1,,1,,,3,14,,1,
-12762573322,1,2,1,2,2,2,2,3,2,3,2,3,2,1,3,2,3,3,3,4,4,4,4,4,4,2,5,3,4,3,3,3,3,3,4,3,2,1,1,1,4,3,,,,3,,,6,7,,,10,11,,,,1,,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,0,Believe in something - not sure what - governed by morals.
-12762523668,1,4,3,1,4,4,2,2,4,5,4,5,1,2,5,4,2,2,2,2,5,5,5,5,1,5,5,2,4,3,2,3,4,4,4,4,3,3,3,1,6,4,,1,,,,5,6,7,,9,10,11,,,,,,3,,5,6,7,,9,10,,,,,,2,3,4,5,6,,,9,2,2,,,,,1,14,,2,
-12762507409,1,2,1,1,4,4,2,2,4,4,1,2,1,1,2,4,4,4,2,4,4,4,4,2,4,2,4,2,3,3,1,4,3,4,4,3,3,1,1,1,3,5,,,,,,5,,7,,9,10,,,,,,,,,,6,7,,9,,,,,,,,3,4,,,,,9,2,1,,,,3,2,3,,11,
-12762503403,1,3,3,1,4,1,1,2,4,2,1,1,2,3,1,3,4,1,1,3,3,3,1,5,3,5,5,2,3,1,1,3,5,4,3,2,2,4,1,1,6,6,,,,3,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,2,3,,,,,,9,2,2,,,,,2,1,,11,
-12762496023,1,2,1,2,2,1,1,1,3,2,2,1,2,2,4,2,5,5,1,5,4,3,5,5,2,5,5,3,5,3,2,3,5,4,4,2,2,1,1,1,5,5,,,,,,5,,7,,9,,,,,,,,,,5,6,7,,9,,,,13,,1,,3,4,5,6,,,9,2,2,,,,,2,10,,15,
-12762495697,1,3,2,1,3,3,5,2,4,4,5,4,2,5,5,4,4,4,5,1,5,5,5,5,1,5,5,4,4,4,3,3,4,5,5,2,4,3,2,2,5,5,,1,,,4,,6,,,,10,11,,,,,,3,,,6,7,,,,,,,,1,,3,4,,,,,,2,1,,,,3,2,15,,0,Roman Catholic
-12762487558,1,4,3,1,3,2,1,1,3,3,2,3,1,1,3,3,5,5,2,5,5,5,5,5,0,5,5,5,4,3,2,3,4,3,4,4,3,3,4,4,5,5,,,,,,5,6,,,,,,,,,1,2,3,4,5,6,7,8,9,10,11,12,13,,,,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12762483790,1,2,2,2,3,4,4,2,4,5,3,2,2,2,2,2,5,2,5,4,5,5,5,4,2,5,2,2,4,3,3,2,4,3,3,2,2,2,2,1,6,5,0,,,,,,,,,,,,,,,,,3,,,6,7,,,10,,,,,,,3,,5,6,,,,2,2,,,,,1,14,,1,
-12762480206,1,4,3,1,2,3,3,4,4,2,1,5,2,1,1,3,2,4,3,5,3,1,2,5,4,1,1,3,3,3,1,3,3,3,4,2,3,1,1,2,5,5,,,,,,,6,7,,,,,,13,,1,,3,,,6,7,,,,11,,,,,2,3,,,,,8,9,2,1,,,,3,1,2,,5,
-12762478446,1,3,2,1,4,2,2,2,4,3,2,3,2,2,2,3,5,5,5,5,5,5,5,5,5,5,5,5,3,2,2,3,0,3,2,2,2,2,2,2,6,6,,,,,4,5,6,,,,,11,,13,,,,,,5,,,,9,,11,,13,0,,,,,,,,,,2,1,,,,3,2,7,,11,
-12762470102,1,2,1,3,4,1,4,2,4,4,4,4,1,2,4,2,5,2,5,5,5,5,5,5,5,5,5,5,5,2,3,5,3,5,5,1,4,1,1,3,3,5,0,,,,,,,,,,,,,,,,,,,,6,7,,,,,,,0,,,,,,,,,,2,2,,,,,1,14,,2,
-12762464135,1,2,1,1,3,4,3,2,4,5,4,3,2,1,1,2,4,5,3,4,4,0,5,3,5,1,1,3,4,3,2,4,4,0,4,2,2,2,1,2,1,1,,1,,3,,,6,7,,,,,,,,,,3,,5,6,7,,,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,1,14,,2,
-12762438768,1,4,3,2,2,4,2,2,4,3,2,4,2,2,2,2,2,3,2,5,5,5,5,5,5,5,5,5,4,0,2,3,3,3,3,3,3,2,1,3,6,5,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,2,,,,,2,14,,2,
-12762437190,1,4,3,1,2,5,1,1,2,5,4,2,1,1,5,1,2,5,5,5,3,5,3,5,5,5,5,5,4,4,3,4,5,5,4,4,3,1,1,1,5,5,,,,3,,,6,7,,,,,,,,,,,,5,6,7,,,,,,,,1,,3,4,5,,,,,2,1,,,,3,2,14,,2,
-12762425823,1,4,3,1,4,1,1,2,3,5,2,4,2,2,4,2,5,2,1,5,5,5,5,5,5,5,5,3,4,2,2,4,4,4,4,3,4,2,2,1,3,5,,,2,,,,6,7,8,,10,,,,,1,,3,,5,6,7,,,,,,,,,2,3,4,5,,,,,2,2,,,,,2,14,,17,
-12762421352,1,4,3,2,4,3,3,1,4,5,4,2,1,5,4,4,4,3,4,2,4,4,4,2,4,5,5,5,4,3,2,3,4,4,3,2,4,1,1,1,,3,,,2,3,4,5,6,7,8,9,,,,,,,,,,5,6,7,,9,,,,,,1,2,3,4,5,6,,,,2,2,,,,,2,14,,17,
-12762415790,1,2,2,1,2,3,2,2,2,4,3,3,2,2,3,3,5,5,5,5,5,5,5,5,5,5,5,5,3,3,,3,3,3,3,3,2,1,1,2,4,3,,,,3,,,6,7,,9,,,,,,,,3,4,,6,7,,9,10,,,,,1,2,3,4,5,6,,,,2,2,,,,,2,14,,1,
-12762400338,1,4,3,1,2,2,1,1,2,2,2,2,1,1,1,2,1,3,2,1,3,3,4,2,1,1,1,2,3,2,1,2,3,4,4,1,3,1,1,1,3,2,,,2,,4,,6,7,,,10,11,,,,,,,4,5,6,7,,,,11,,,,1,2,3,4,,6,,8,9,2,2,,,,,2,14,,2,
-12762379768,1,4,3,1,2,2,2,1,2,3,3,2,1,2,4,4,2,4,3,2,2,2,4,2,2,3,5,3,2,3,2,2,2,4,4,2,2,1,1,3,5,5,,,2,,4,5,6,,,,,,,,,,,3,,5,6,7,,,10,,,,,1,,3,4,5,,,,9,2,2,,,,,1,17,,1,
-12762376635,1,3,3,1,2,4,1,3,2,5,2,4,2,1,1,3,2,1,1,5,3,3,2,2,3,1,1,1,4,3,2,4,3,3,4,2,3,2,1,1,4,3,,1,,3,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,7,,9,10,11,,13,,,2,3,,,6,,,9,2,2,,,,,2,2,,11,
-12762375533,1,2,1,1,3,2,2,1,2,4,2,1,2,1,2,2,2,2,2,1,2,5,4,1,4,4,4,4,4,2,2,3,3,5,4,2,4,2,1,2,4,4,,1,,,,5,6,,8,9,,,,,,,2,3,4,5,6,,,9,,,,,,1,2,3,,,,,,9,2,2,,,,,1,10,,2,
-12762373950,1,4,3,2,1,3,2,1,1,1,1,4,1,2,3,3,5,4,2,1,2,2,2,4,4,4,5,4,4,3,1,2,3,4,4,2,2,1,1,1,4,5,,,,3,,5,6,7,,9,,,,,,,,3,,5,6,7,,9,,,,,,,2,,4,5,,,,9,1,1,,1,,3,1,17,,1,
-12762364170,1,2,3,1,2,5,5,1,2,2,2,4,1,1,1,4,3,4,4,2,3,4,4,2,4,1,1,1,2,3,2,4,4,4,5,1,3,1,1,1,4,2,,,2,3,4,,6,7,,9,10,,,,,,,3,4,5,6,7,,9,,,,,,1,2,3,,,,,,9,2,2,,,,,1,14,,0,
-12762362301,1,3,2,1,3,4,1,1,3,4,2,4,2,2,4,4,5,2,1,2,5,5,5,5,5,5,5,5,4,2,1,3,4,4,4,2,4,2,1,1,3,5,,,,,,,6,,,,,,,,,,,,,,6,7,,,,,,,,,,,4,,,,,,2,1,,1,,,2,14,,17,
-12762349550,1,2,1,2,2,2,1,4,3,0,2,5,1,4,5,2,2,2,1,5,2,3,3,4,4,4,5,5,3,2,2,3,4,4,4,2,3,3,2,2,3,5,,,,,4,,6,7,8,,,,,13,,,,,4,5,6,7,8,,,11,,13,,1,2,,4,5,,,,9,1,1,,1,,,2,3,,11,
-12762341196,1,4,3,1,3,5,2,2,2,5,5,2,1,2,4,2,5,5,2,5,3,5,5,3,5,2,5,5,5,4,2,3,5,5,5,1,3,1,1,1,,1,,,,,,5,,,8,,,,,,,,,,,,6,,,9,,,,,,1,2,3,,5,,,,9,2,2,,,,,2,14,,2,
-12762339457,1,4,3,1,2,3,2,2,2,3,2,2,2,2,3,1,5,5,5,5,5,5,5,5,5,5,5,1,0,0,0,0,0,0,0,0,0,0,0,2,4,3,,,2,3,4,5,6,7,,9,10,11,,13,,1,,,,5,6,7,,,10,11,,,,,2,3,4,5,6,,,,2,2,,,,,2,7,,5,
-12762324391,1,3,2,1,1,2,1,1,1,5,1,1,1,1,1,1,2,2,1,1,,,4,1,1,5,,4,3,3,1,1,5,4,5,1,1,1,1,2,3,2,0,,,,,,,,,,,,,,,,,,,,6,7,,9,10,,,,,,2,3,,5,,,,,2,1,,,,3,2,7,,15,
-12762316234,1,3,2,3,3,4,2,1,2,4,2,2,2,1,4,3,4,4,4,2,4,4,4,4,4,1,4,4,3,3,3,2,3,4,4,2,2,1,1,1,5,5,,,,,,5,6,7,8,,,,,,,,,3,4,,,7,,,,,,,,,2,,4,,,,,9,2,2,,,,,2,14,,2,
-12762314056,1,2,1,1,4,4,3,2,5,4,4,3,2,2,2,2,5,5,4,5,5,5,5,5,5,4,3,2,5,5,3,5,5,5,4,2,3,2,1,1,2,3,,,,,,5,6,7,8,,10,,,,,,2,3,,5,6,7,8,9,10,,,,,,,3,4,,,,,9,2,2,,,,,2,2,,9,
-12762310881,1,4,3,1,2,2,2,1,2,2,2,1,2,2,3,2,2,2,2,2,2,2,4,1,3,3,5,2,4,1,1,1,4,3,4,1,3,2,1,1,5,5,,,2,,,5,,7,,9,10,,,,,,,,,5,6,7,,,,,,,,1,2,3,4,5,,,,9,2,1,,1,2,3,2,7,,5,
-12762306599,1,3,3,1,3,2,2,2,4,3,3,3,2,2,2,2,4,4,4,4,4,4,5,5,4,5,4,3,4,3,2,3,4,4,4,2,2,3,1,1,4,3,,,,,,5,6,7,,,,,,,,1,,,,5,,7,,9,10,,,,,,2,3,4,5,,,,,2,1,,,,3,2,14,,2,
-12762305610,1,4,2,1,1,1,2,1,1,1,1,1,1,1,2,2,1,1,3,1,1,1,1,1,1,4,4,4,2,3,1,1,3,2,2,2,3,2,1,2,5,5,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,1,1,,1,,,2,14,,1,
-12762304191,1,4,3,1,4,4,4,4,3,3,3,4,3,2,3,2,5,5,5,5,5,5,5,5,5,4,4,2,0,0,0,0,0,0,0,0,0,1,0,1,6,6,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,1,,,,3,1,7,,5,
-12762291487,1,3,2,1,5,4,1,5,4,4,4,4,4,4,4,2,4,4,2,5,4,4,4,4,4,5,4,2,5,3,1,2,3,0,4,1,3,1,1,1,4,4,,,2,,,5,6,7,8,,,,,,,1,,,,5,6,7,,,10,,,,,,2,3,4,5,,,,9,2,2,,,,,2,7,,5,
-12762289221,1,3,2,1,2,3,2,2,2,3,2,3,2,1,1,1,2,4,2,4,3,4,3,3,4,1,1,2,3,3,2,3,4,3,3,1,2,2,1,1,6,5,,,2,3,,,6,7,,,,11,,,,,,,,5,6,,,9,10,,,,,,,3,4,,6,,,,2,2,,,,,2,7,,5,
-12762279072,1,3,2,1,3,5,4,2,4,2,2,4,2,1,4,5,4,4,4,4,5,5,5,4,5,2,4,4,2,4,3,1,2,3,3,1,1,1,1,1,4,4,,1,,,,,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,,3,4,5,,,,9,2,1,,,,3,1,6,,1,
-12762274505,1,3,2,1,4,4,1,2,4,1,2,3,2,4,3,4,3,4,2,2,4,2,2,4,4,4,4,2,3,3,1,3,3,1,2,2,3,2,2,2,5,5,,,2,,,,6,7,,9,10,,,,,,2,,,5,6,7,,9,10,,,,,,2,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12762269137,1,3,2,1,4,2,1,2,4,4,3,2,1,2,4,1,5,4,1,5,5,5,5,5,2,5,5,2,3,2,1,2,3,3,3,1,3,1,1,1,4,3,,1,2,3,4,5,6,7,8,,10,11,,13,,1,,,4,5,6,,8,,10,11,,,,1,2,,4,5,6,,,,2,2,,,,,2,14,,5,
-12762247233,1,2,1,2,4,2,2,2,3,4,2,2,2,2,3,2,4,3,3,4,4,4,4,3,4,4,4,4,3,1,2,2,2,2,2,1,2,1,1,1,3,3,,1,,3,,,,7,,,,,12,,,,,,4,5,,7,,,,11,,,0,,,,,,,,,,2,2,,,,,2,3,,11,
-12762233631,1,3,2,1,4,5,1,2,4,5,2,4,1,2,5,5,5,5,2,5,5,5,5,5,1,5,5,5,4,4,1,3,4,5,5,1,1,1,1,2,5,5,,1,,3,4,,6,7,,,,,,,,,,,,5,,7,,9,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,17,
-12762231310,1,4,3,1,5,5,4,1,5,5,4,5,4,2,4,2,5,5,5,5,5,5,5,5,5,5,5,1,5,4,3,5,5,5,5,3,3,2,2,1,5,5,,,,,4,5,,7,,,,,,,,,,,,5,6,,,,,,,,,,,3,4,,,,,9,2,1,,,,3,2,14,,5,
-12762224298,1,3,3,2,2,2,3,3,1,1,1,4,3,2,5,3,2,2,2,4,2,3,3,4,5,5,5,5,2,2,2,3,4,4,4,3,2,2,4,4,5,5,,,,,,,6,7,,9,,,,,,,,,,,6,7,,9,10,,,,,,,3,4,5,,,,,1,1,,,,3,2,14,,5,
-12762217827,1,2,1,1,5,3,2,1,5,5,5,3,2,1,1,1,5,5,5,5,5,5,5,4,5,1,3,1,5,3,2,3,5,5,4,2,4,2,1,1,3,2,,,,,,,6,7,,9,10,,,,,,,3,4,,6,7,,,,,,,,1,,3,,5,,,,9,2,1,,,,3,1,14,,1,
-12762215287,1,4,3,1,3,2,1,4,4,5,3,4,1,1,3,4,3,3,2,5,4,3,5,4,4,3,4,4,3,2,1,4,3,3,5,2,2,1,1,1,3,1,,1,,3,,,6,,8,,,,,,,,,,,5,,,,9,10,,,,,,2,,,,,,,,2,1,,,,3,2,14,,2,
-12762210428,1,4,3,1,2,2,2,3,5,4,2,2,2,1,3,2,5,5,5,5,5,5,5,5,5,2,5,5,4,4,3,4,4,4,4,4,3,1,2,1,4,3,,1,,,4,,6,7,8,,10,,,,,,,3,,5,,,,,,11,,13,,1,,3,4,,,7,,,2,2,,,,,2,8,,17,
-12762205732,1,5,3,1,1,1,1,1,1,1,1,1,1,1,0,1,4,1,1,4,4,4,4,4,1,4,4,4,1,1,1,1,3,2,1,1,1,1,2,1,6,6,0,,,,,,,,,,,,,,,1,,,,,6,7,,,,,,,,1,,,,,,,8,9,2,1,,,,3,3,14,,5,
-12762205703,1,3,2,3,1,1,4,2,2,2,2,2,1,2,4,4,1,2,4,2,2,2,2,4,1,4,4,5,2,2,2,3,4,4,4,3,2,3,4,3,3,5,,,,,,5,6,,,9,10,,,,,,,,,5,,7,,,10,,,,,,2,3,,5,,,,9,2,1,,1,,,2,10,,17,
-12762204308,1,4,3,1,2,2,2,2,2,2,4,2,2,2,2,2,5,5,5,2,5,5,5,5,2,5,5,2,4,4,1,2,4,4,4,3,3,2,1,1,3,3,,,2,,,5,6,7,8,9,10,,,,,1,2,3,4,5,6,7,8,9,10,,,,,,2,3,4,,,,,9,2,2,,,,,2,17,,15,
-12762203493,1,2,2,1,2,1,2,1,2,3,2,2,2,1,4,4,3,4,1,4,3,5,5,3,5,4,5,3,5,5,1,4,5,3,5,2,3,2,3,1,2,1,,,,,,5,6,,,9,,11,,,,,2,,,5,6,7,,,,11,,,,1,,3,4,5,6,,,9,2,1,,,,3,2,14,,1,
-12762196321,1,3,2,2,0,0,0,0,0,0,0,2,2,2,0,0,5,5,5,5,5,5,5,5,5,3,5,5,4,2,1,1,1,3,5,1,3,1,1,1,5,5,,,,3,,5,6,,8,,,,,,,1,,3,,5,6,7,,,,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,3,,11,
-12762183754,1,3,3,1,2,2,2,1,1,2,1,1,1,1,2,1,5,5,5,4,4,5,5,5,4,5,5,5,5,5,5,1,5,5,5,2,1,1,1,1,5,5,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,,9,2,1,,1,,,2,14,,15,
-12762175478,1,2,1,1,4,5,1,4,5,5,4,3,2,1,2,1,5,5,3,5,5,5,5,5,5,2,1,4,4,4,2,2,4,4,4,2,3,1,1,2,5,5,,,,3,,,6,7,,9,10,,,,,,,3,,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,1,3,,11,
-12762175408,1,3,2,1,3,2,2,1,2,2,1,2,1,1,5,1,4,2,2,1,4,4,3,4,1,3,5,2,2,2,1,1,2,3,2,1,1,1,1,1,4,5,,,,,,,6,7,,,,,,,,,,,,5,6,7,,,10,,,,,,2,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12762171454,1,2,2,1,2,4,2,2,2,4,2,2,2,2,3,2,5,5,5,5,5,5,5,3,5,5,5,5,3,4,1,3,2,3,3,2,3,3,1,1,5,5,,1,,,,,6,7,,,,,,,,1,2,3,4,5,6,7,,,,,,,,,,3,4,,,,,,2,1,,,,3,2,14,,2,
-12762168429,1,3,2,1,5,5,4,5,5,5,5,5,5,1,4,2,5,5,2,5,5,5,5,5,5,1,2,4,5,4,4,4,4,4,4,3,4,1,1,1,2,5,,,,3,4,,6,7,,9,,,,,,,,,4,,,7,,9,10,,,,,,2,3,,,,,,9,2,2,,,,,1,6,,9,
-12762147580,1,2,1,1,3,2,3,2,3,3,2,3,2,5,2,4,5,3,4,3,5,5,5,5,5,1,1,3,4,4,3,4,4,5,5,3,4,2,1,3,4,5,,1,,3,4,,,7,,,,,,,,,,,,5,6,7,,,10,,,,,,2,,4,5,,,,,2,1,,,,3,2,0,,,
-12762140472,1,3,2,1,2,2,2,2,2,2,2,1,2,2,2,4,3,3,4,1,4,4,4,2,4,5,5,4,,3,2,2,3,3,3,3,3,1,2,2,3,5,,,,3,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,1,
-12762128684,1,3,2,3,1,5,5,2,1,1,1,5,4,2,5,1,5,5,5,5,5,5,5,5,5,5,5,5,3,,1,1,4,4,4,2,2,1,1,1,1,1,0,,,,,,,,,,,,,,,,,,,,6,7,,,10,,,,,,2,3,4,5,6,,,9,1,1,,1,,,2,7,,5,
-12762093317,1,4,3,1,5,2,1,1,5,5,5,1,1,2,1,1,2,2,1,5,5,5,5,2,2,2,1,1,5,4,2,5,5,5,5,3,2,1,1,2,2,1,,1,,3,,5,6,7,,,10,,,,,1,,3,,5,6,7,,,10,,,,,,,3,4,5,,,,9,2,2,,,,,2,0,Nepali,1,
-12762071855,1,2,1,1,4,5,4,1,5,2,2,4,2,1,4,1,5,5,2,5,5,5,5,1,4,1,1,1,4,4,2,2,4,4,4,2,1,1,1,1,5,5,,,,,,5,6,7,,,,,,,,,,3,,5,6,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,2,6,,11,
-12762045645,1,2,3,1,2,2,3,1,2,1,1,2,2,1,1,2,1,3,2,2,4,2,2,2,3,1,1,4,2,3,3,3,3,3,3,2,3,1,1,3,5,5,,,,3,4,5,6,7,8,9,10,,,,,,,3,4,5,6,7,8,9,10,,,,,1,2,3,,,,,8,9,2,2,,,,,1,2,,9,
-12762039186,1,4,3,1,4,4,4,4,4,4,4,4,4,1,4,2,4,4,4,4,4,4,4,4,5,1,2,2,5,4,4,4,4,5,5,3,3,1,1,1,5,5,,,,,,,6,7,,,,,,,,1,,3,4,5,6,7,,,,,,13,,,,3,4,5,,,,9,2,1,,,,3,2,14,,5,
-12762017994,1,3,3,1,4,4,2,2,4,4,4,2,3,1,1,1,5,4,2,5,5,4,4,3,5,1,2,1,5,2,1,2,5,4,4,2,3,1,1,1,5,5,,,,,,,6,7,,,10,,,,,1,,,,5,6,7,,,,,,,,1,,3,,5,,,,9,2,1,,,,3,1,17,,1,
-12762006895,1,3,2,1,2,1,3,4,3,4,4,4,3,1,3,1,2,5,3,2,4,4,5,1,3,1,1,1,4,5,3,4,5,4,5,3,5,1,1,1,4,2,,,,,,,6,,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,1,6,,11,
-12761896746,1,2,1,1,3,3,3,3,3,3,3,3,2,2,3,3,3,4,4,4,4,3,3,3,1,1,4,3,2,2,1,1,2,3,3,1,2,2,1,2,3,4,,,2,,,5,6,7,,9,10,,,,,,2,,,5,6,7,,9,10,,,,,1,,3,4,5,,,,9,2,2,,,,,1,2,,9,
-12761853502,1,4,3,3,4,2,2,2,4,5,2,3,3,4,2,2,2,2,1,3,3,3,4,5,5,4,5,4,4,3,2,3,4,0,4,3,5,1,1,1,5,4,,1,2,3,4,5,6,7,8,9,10,11,,,,,2,,,5,6,7,,,10,,,,,,2,3,4,5,,,,9,2,2,,,,,2,12,,1,
-12761746251,1,4,3,1,3,2,1,2,2,4,2,3,2,1,3,3,3,3,3,4,3,3,4,4,3,1,2,5,4,3,2,3,4,4,4,3,3,1,1,3,5,5,,,,,,5,6,7,,9,,,,,,,,,4,5,6,7,,9,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,17,,1,
-12761676310,1,3,2,1,2,3,2,2,4,5,2,4,2,2,2,3,1,2,2,2,2,3,2,2,2,5,2,3,2,2,1,1,2,3,3,2,1,2,1,1,5,5,,,2,,,5,6,,8,,10,11,,,,,,3,,5,6,7,8,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,1,14,,15,
-12761659106,1,2,1,1,2,4,2,4,2,4,1,4,3,2,4,4,4,4,2,5,4,4,4,4,4,4,5,4,5,3,2,5,4,4,3,2,3,1,1,1,3,3,,,,,,,6,7,,9,,,,,,,,,4,5,6,7,,9,,,,,,,,3,4,5,6,,,9,2,1,,1,2,,2,4,,11,
-12761648892,1,4,3,1,4,4,4,4,4,4,2,5,2,2,4,5,2,4,3,4,4,4,4,5,4,1,1,4,1,5,3,5,4,0,4,2,4,2,1,3,3,3,0,,,,,,,,,,,,,,,1,2,3,4,5,6,7,8,9,10,11,,13,,1,2,3,4,5,6,,8,9,2,1,,,,3,2,7,,5,
-12761638084,1,4,3,1,2,3,2,2,3,3,3,2,2,1,2,3,3,3,2,4,5,5,5,3,3,1,2,3,3,2,2,3,3,4,4,2,2,2,1,2,1,5,,,,3,,,6,7,,9,10,11,,,,,,,,5,6,7,,9,10,11,,13,,1,2,3,4,5,6,,,9,2,2,,,,,1,14,,2,
-12761624514,1,3,2,1,3,2,2,5,5,5,5,5,3,2,4,5,4,3,3,5,5,5,5,5,3,3,5,5,4,5,2,5,5,5,5,3,2,1,1,1,5,3,,,,,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,0,Asian- Chinese,5,
-12761563764,1,2,1,3,3,3,3,2,3,3,2,3,2,2,3,2,3,3,3,2,3,3,3,3,3,4,5,3,3,3,2,3,3,3,4,1,1,1,1,1,5,5,,1,,,,,6,,,,,,,,,,,,,,,7,,,,,,,,,,,4,,,,,,2,1,,,,3,2,14,,2,
-12761544808,1,3,3,1,1,1,2,1,4,4,1,2,1,1,1,2,5,5,2,4,2,3,4,4,1,5,5,5,5,3,1,3,5,4,3,3,1,1,2,3,5,5,,,,3,,5,6,7,,,10,,,,,,,3,4,5,6,7,,9,10,,,,,,2,3,4,5,,,,,2,2,,,,,2,14,,17,
-12761537499,1,4,3,1,3,4,3,2,3,5,4,5,2,1,1,3,5,5,5,5,5,5,5,5,5,2,1,5,4,4,2,3,4,4,4,3,2,1,1,2,6,3,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,2,,,,,1,14,,2,
-12761502957,1,2,1,1,3,4,4,2,5,5,3,5,3,1,1,3,5,5,5,4,5,5,5,4,5,1,1,4,4,5,3,4,5,3,4,1,2,1,1,1,5,5,,1,,3,,,6,7,,9,,11,,13,,,,,4,5,6,7,,9,10,,,,,1,,3,4,,,,8,9,2,2,,,,,1,2,,9,
-12761487525,1,4,3,1,3,1,1,2,5,4,2,2,2,2,3,2,5,1,4,5,5,5,5,3,5,5,5,4,5,1,2,3,4,5,5,1,2,1,1,1,3,5,,,,,,5,6,7,8,9,,,,,,,,,,,6,7,8,9,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,2,
-12761486723,1,4,3,1,2,4,5,5,2,5,4,4,2,1,1,5,2,2,4,5,2,3,5,4,5,1,2,5,4,3,1,3,3,4,5,3,2,1,1,2,5,5,,,,,,,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,,3,4,,,,,9,2,1,,,,3,2,14,,1,
-12761480320,1,2,1,1,2,2,2,1,2,2,2,1,1,1,2,1,4,4,2,2,5,5,5,1,5,5,5,2,3,2,2,2,4,4,3,1,2,1,1,1,5,5,,1,,,,,6,7,,9,,,,13,,1,,,,,6,7,,,,,,13,,,,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12761458339,1,4,3,1,1,1,2,2,1,2,2,2,2,3,5,4,1,2,5,5,2,5,5,5,3,5,5,5,3,2,3,3,3,4,4,3,2,1,1,1,5,5,,,,,,5,6,7,,9,,,,,,,,,,5,6,7,,9,10,,,,,,,3,,,,,,,2,2,,,,,2,17,,2,
-12761448948,1,3,2,1,4,4,1,2,2,4,1,3,1,2,2,3,3,3,2,3,3,3,4,5,3,4,5,3,4,3,1,3,4,4,3,3,1,2,2,3,3,2,,1,,3,4,,6,7,,,,11,,13,,,,,,5,6,7,,,,11,,,,,2,3,4,5,,,,9,2,1,,,,3,2,14,,0,
-12761420563,1,3,2,1,2,2,1,1,2,4,2,2,2,2,2,2,3,2,2,2,4,4,4,5,5,5,5,4,2,2,3,3,3,3,3,2,2,3,3,3,5,5,,1,2,3,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,2,,4,,,,,9,2,2,,,,,2,2,,2,
-12761419064,1,2,1,1,3,5,3,1,3,5,4,3,2,1,4,2,2,2,2,4,2,4,3,3,3,2,3,4,1,3,3,3,1,4,5,2,1,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,5,6,7,,,,,,13,,,2,3,,5,,,,9,2,2,,,,,2,14,,8,
-12761414458,1,4,3,1,2,3,1,4,3,4,3,4,2,2,2,3,3,2,1,5,3,5,5,5,5,2,4,2,3,3,2,4,3,4,5,3,3,1,1,2,2,2,,,,,,,6,7,,9,,,,,,,,,,,6,7,8,9,,,,,,,,3,4,5,,,8,9,2,2,,,,,2,2,,9,
-12761409341,1,3,2,1,1,1,1,1,1,1,1,1,1,1,1,1,5,5,5,5,5,5,5,5,5,1,2,5,3,1,1,2,4,3,4,1,2,1,1,1,1,1,,,,,4,5,6,7,,,,,,,,,,,,5,6,7,,9,,,,,,1,2,3,4,,,,8,9,2,2,,,,,3,14,,2,
-12761408577,1,2,1,1,2,5,5,2,5,5,5,2,2,2,1,4,2,4,4,2,4,3,5,2,1,4,1,2,5,3,3,3,5,5,5,2,4,1,1,1,3,3,,,,3,,,6,7,,9,,,,,,,,,,,6,7,,,,,,,,1,2,3,4,5,,,,9,2,1,,,,3,1,3,,17,
-12761392173,1,4,3,1,3,4,3,3,4,5,2,3,2,1,3,3,3,4,2,5,4,3,5,4,5,5,5,3,3,3,3,4,3,4,4,,3,2,2,2,6,3,0,,,,,,,,,,,,,,,,,,4,5,,,,,10,,,,0,,,,,,,,,,2,1,,,,3,2,5,,0,
-12761385437,1,4,3,1,3,3,2,2,3,2,2,2,2,2,2,2,4,4,4,3,4,5,4,4,4,5,4,4,4,3,2,2,3,2,4,3,3,2,2,3,2,3,,,,,,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,1,2,,4,,,,,9,2,2,,,,,2,14,,5,
-12761365235,1,3,3,1,2,2,2,3,4,5,2,3,2,,1,4,3,4,2,4,3,4,4,4,5,5,1,4,2,3,2,3,4,0,4,4,3,1,1,2,2,5,0,,,,,,,,,,,,,,,,,,4,5,6,7,,,,,,,,1,2,3,,5,,7,,9,2,1,,,,3,2,3,,2,
-12761354177,1,4,3,1,1,3,2,2,1,1,1,2,1,2,4,3,2,4,2,4,2,4,4,2,1,4,5,1,3,3,3,3,3,2,1,3,1,3,5,3,5,4,,,,,,5,6,7,8,9,10,,,,,,,,,5,6,7,8,9,10,,,,,,2,3,4,5,6,,,9,2,2,,,,,2,17,,8,
-12761353411,1,3,3,1,5,3,3,2,4,5,2,3,2,2,3,2,5,5,4,5,5,5,5,4,5,5,5,5,4,4,2,3,5,2,4,2,3,1,1,2,2,1,,1,,3,4,5,6,7,,9,10,,,,,,,3,4,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,1,14,,1,
-12761351027,1,4,3,1,2,2,1,1,2,4,4,2,2,2,5,4,5,2,1,2,4,4,4,2,5,5,5,4,4,5,3,4,4,4,5,3,2,1,1,1,5,5,,1,,3,,,6,7,,,,,,,,,,,4,5,6,7,,,,11,,13,,1,2,3,4,5,6,,,,2,1,,,,3,2,14,,2,
-12761333356,1,3,3,2,5,2,2,2,5,4,4,2,2,2,2,2,2,2,2,5,5,5,5,5,5,5,2,5,3,3,3,4,4,3,3,2,3,1,1,1,5,5,,,,,4,5,6,7,,9,10,,,,,,,3,4,5,6,7,8,9,10,,,13,,1,2,3,4,5,,,,9,2,1,,,,3,2,4,,11,
-12761324890,1,4,3,1,4,3,1,2,5,4,5,5,1,2,2,4,4,2,2,2,3,4,4,3,2,2,3,4,4,3,2,4,5,4,4,2,2,1,1,2,5,5,,,,3,,,6,7,,9,,,,,,,,3,4,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,17,,5,
-12761323391,1,2,1,1,4,5,5,1,5,5,3,3,3,2,5,5,2,5,5,2,3,5,5,3,3,3,5,5,3,5,5,3,5,5,5,4,4,3,3,4,5,5,,,2,,4,5,6,7,,9,10,11,,,,,,,,5,6,7,,9,10,11,,,,,,3,4,5,6,,8,,2,2,,,,,2,3,,11,
-12761312976,1,3,3,1,5,2,4,4,4,4,4,3,3,3,5,5,5,5,3,5,5,5,5,3,5,5,5,5,2,4,2,2,2,3,4,2,2,1,2,1,5,5,,1,,,4,5,6,7,,,10,11,,,,,,3,4,5,6,7,,9,,,,,,,,,,,6,7,8,9,2,2,,,,,2,14,,15,
-12761310336,1,4,3,1,3,2,2,2,4,4,3,2,2,2,2,2,5,5,4,5,5,5,5,4,5,5,5,5,4,4,2,3,4,4,4,1,2,1,1,1,5,5,,,,,,5,6,7,,,,,,,,,,,4,5,6,7,,,10,,,,,1,,3,4,5,,,,9,2,2,,,,,2,3,,11,
-12761310233,1,3,2,2,5,4,4,5,4,5,5,3,4,1,2,2,5,3,3,5,5,5,5,5,5,2,1,1,4,2,2,5,4,4,4,3,1,2,1,1,5,5,,,,,,5,6,7,,9,,,,,,,,,,5,,,,9,,,,,,,2,3,4,5,,,,,2,2,,,,,1,3,,11,
-12761305749,1,3,2,1,2,5,2,2,2,2,2,4,2,2,5,4,3,3,1,5,2,2,2,2,4,2,5,5,5,4,5,4,3,4,5,3,3,1,1,2,5,5,,1,2,,4,,6,,,9,10,11,12,,,,2,,4,5,6,7,,9,10,11,12,,,,,3,4,5,6,,8,9,2,1,,,,3,2,15,,2,
-12761300029,1,4,3,2,4,4,4,2,5,5,2,4,2,1,2,2,3,3,3,3,3,3,3,3,3,3,1,1,3,3,3,3,3,5,3,3,3,1,1,1,5,5,,1,,3,,,6,,8,9,10,,,,,1,,3,,,6,,8,,,,,,,1,2,3,4,5,,,,,2,1,,,,3,1,3,,11,
-12761295026,1,2,1,1,1,2,2,4,2,2,2,5,4,2,5,5,3,4,3,5,4,3,3,5,5,5,5,5,5,5,4,4,5,3,4,3,4,1,1,2,2,5,,,,3,,5,6,7,8,,,,,13,,,,3,,5,6,7,,,,,,,,1,,3,4,5,,,,9,1,1,,,,3,2,14,,5,
-12761292828,1,4,3,2,4,4,4,2,4,5,1,4,2,1,1,2,4,2,2,3,3,5,3,3,4,3,2,2,4,3,3,3,3,4,5,3,4,1,1,1,5,5,,1,,3,4,,6,7,8,,10,,12,,,1,,3,4,,6,7,8,9,10,,,,,1,,,4,,,,,,2,1,,,,3,1,3,,0,J
-12761290274,1,3,2,1,2,,,2,2,,2,2,1,1,2,2,5,5,5,5,5,5,5,5,5,2,5,5,4,4,3,4,4,3,4,3,2,1,1,3,5,5,,,,,,,6,7,,,10,,,13,,1,,3,4,,6,7,,,10,,,13,,1,2,3,4,5,6,,,9,2,1,,1,,,2,0,,0,
-12761284821,1,4,3,1,4,4,3,2,4,4,2,2,3,1,2,2,4,4,3,3,5,4,4,3,5,3,5,3,2,3,4,2,3,4,3,2,3,1,1,3,5,5,,,,3,,,6,7,,9,,11,,,,,,,,5,6,7,,9,10,11,,,,,2,3,4,5,6,,,9,2,2,,,,,1,2,,9,
-12761279918,1,4,3,1,4,4,4,2,4,4,2,4,1,2,4,4,4,3,1,4,3,4,4,4,3,5,5,4,0,2,2,3,0,3,3,0,2,1,1,2,5,5,,,,3,,5,6,7,8,9,,,,,,,2,,,5,6,7,8,9,,,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,15,,2,
-12761277300,1,2,2,1,3,1,2,1,3,5,2,3,1,5,5,2,2,2,2,3,4,3,5,2,3,5,5,4,3,3,3,3,2,4,3,1,2,3,3,1,5,5,,,,,,,,7,,,10,,,13,,,,,,5,,7,,,,,,13,,,,3,,,,,,9,2,1,,,,3,2,7,,5,
-12761275940,1,4,3,2,4,4,4,2,4,4,4,3,3,2,2,2,3,5,3,3,4,4,4,2,4,4,4,4,2,4,4,2,4,3,3,1,3,1,1,3,5,5,,,2,,4,5,6,7,8,9,,11,,,,,,,,5,6,,8,9,10,,,,,,2,3,4,,6,,,9,2,2,,,,,1,2,,9,
-12761274471,1,3,2,3,1,5,2,3,2,1,2,3,4,1,2,5,2,5,4,5,3,1,1,4,5,4,4,4,2,2,4,2,3,3,5,2,3,1,1,3,5,5,,,2,,,5,6,,,,,,,,,,,,,5,,,,9,10,,,,,,2,3,4,5,,,,,2,1,,1,,,1,14,,5,
-12761273259,1,2,1,2,5,5,4,1,5,5,3,4,4,1,2,1,5,5,5,5,5,5,5,5,5,1,2,5,4,3,2,2,4,4,4,2,3,1,1,1,2,4,,1,,3,,,6,7,,9,,,,,,,,3,,5,6,7,,9,,,,,,1,2,3,4,5,,,,,2,2,,,,,2,14,,2,
-12761270783,1,4,3,1,4,3,3,2,3,5,2,3,2,2,3,3,3,3,2,5,4,3,4,4,2,5,3,4,0,1,2,2,3,0,3,2,1,2,3,1,3,3,,,,,,,6,7,8,9,10,,,,,,,,,5,,7,,9,10,,,,,1,,3,4,5,,,,9,2,1,,,,3,2,14,,17,
-12761267205,1,3,2,2,5,5,3,5,5,5,5,5,2,1,4,2,3,1,1,2,4,5,1,1,2,5,3,1,5,5,2,5,5,5,5,5,3,1,1,1,5,5,,,,3,,,6,7,,,10,,,,,,,,,5,6,7,,9,10,,,,,1,,3,4,5,6,,,9,2,1,,1,,3,2,0,,5,
-12761262234,1,3,2,1,3,3,3,3,3,3,3,3,3,2,3,2,5,5,5,5,5,5,5,5,5,2,3,3,4,4,3,4,4,4,4,2,4,1,1,2,1,3,,,,,,,6,7,,,,11,,,,,,3,,5,6,7,,9,10,,,,,,2,,4,,6,,,,2,2,,,,,2,12,,5,
-12761256854,1,3,3,1,1,1,2,2,1,2,1,2,2,2,4,3,5,1,2,4,5,3,3,3,3,5,5,3,5,3,2,3,5,3,3,2,3,1,1,3,5,5,,,,3,4,,6,7,,,,,,,,,,3,4,,6,7,,,,,,,,,2,3,4,5,,,,,1,1,,,,3,2,4,,11,
-12761251276,1,3,2,2,4,3,2,4,4,4,4,4,4,4,4,4,4,3,2,4,5,5,5,4,4,5,4,5,5,3,2,3,5,5,5,2,3,2,1,1,3,2,,,,,,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,,2,3,,5,,,,9,2,2,,,,,1,14,,17,
-12761250171,1,2,1,1,3,3,2,2,2,3,2,3,2,1,3,2,2,2,3,2,2,3,2,3,3,1,3,2,0,0,0,0,0,0,0,3,4,2,1,4,6,3,,,,,,,6,7,,,,,,,,,,,4,5,,,,,,,,13,0,,,,,,,,,,2,1,,1,,,2,14,,0,
-12761249385,1,3,2,1,2,2,3,5,1,2,1,4,1,1,5,5,2,5,5,5,2,3,4,5,2,2,5,5,4,3,4,4,3,3,3,3,2,1,1,3,5,5,,1,,3,,,6,7,,,,,,,,,,3,,,6,7,,9,,,,,0,,,,,,,,,,2,1,,1,,,2,2,,11,
-12761247412,1,4,3,1,2,1,1,1,2,1,4,2,2,1,1,2,5,5,2,5,5,5,5,,5,4,2,5,5,4,3,2,3,5,5,3,5,1,1,4,1,1,,,,,,,6,7,,,,,,,,,,,,,6,,,,,,,,,,,3,,,,,,,2,2,,,,,2,14,,15,
-12761246546,1,3,3,1,4,4,4,2,2,2,2,2,1,2,4,4,4,5,5,4,5,5,5,2,5,2,2,5,4,5,5,3,5,5,5,3,5,1,1,4,5,4,,,,,,5,6,7,,,10,11,,,,,,3,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,1,14,,1,
-12761241548,1,2,1,1,5,2,2,2,4,4,4,4,1,2,5,4,5,2,5,5,5,3,5,5,1,5,5,5,3,2,1,3,3,3,3,1,1,1,2,1,5,5,,1,,3,,5,6,,,,,,,,,,,3,,,,7,,,10,,,,,,2,3,,5,,,,,2,2,,,,,2,7,,5,
-12761241378,1,2,1,1,2,3,2,2,2,2,1,3,2,1,2,3,2,2,2,5,2,2,4,5,4,5,5,3,5,3,3,3,5,5,4,2,1,1,1,1,5,5,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,1,1,,1,,,2,14,,2,
-12761240352,1,3,2,1,2,3,2,3,2,3,3,2,2,2,2,3,2,4,2,4,4,4,4,4,4,4,3,4,3,1,2,1,2,4,4,1,1,1,1,1,3,2,,1,2,3,,5,6,,,,10,,,13,,1,2,3,,5,6,7,,,10,11,,13,,1,2,3,4,5,,,8,9,2,2,,,,,2,3,,11,
-12761223889,1,2,1,1,1,2,2,1,1,1,1,2,1,2,2,3,1,4,2,1,2,1,1,2,2,4,3,4,2,3,2,2,2,3,2,2,2,3,1,2,5,5,,,,,,5,6,7,,9,10,,,,,1,2,3,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,,8,9,1,1,,1,,,2,14,,2,
-12761218716,1,3,1,1,1,1,2,1,1,2,2,1,1,1,2,1,1,1,3,2,2,3,3,1,1,1,4,1,1,2,2,4,2,4,4,2,1,1,3,2,5,5,,,,,,,6,,,9,,11,,,,,,3,,5,6,,,9,,11,,,,1,2,3,,5,6,,,9,2,2,,,,,2,7,,17,
-12761217728,1,2,2,1,2,3,4,3,2,4,4,3,4,2,4,3,4,4,4,4,4,4,4,4,4,2,4,4,3,3,4,2,3,3,3,1,3,1,2,2,2,5,,,,,,5,6,7,,,10,,,,,1,,,,,6,7,,,,,,,,1,2,3,4,,,,,9,2,2,,,,,2,17,,5,
-12761207232,1,3,2,1,1,2,1,2,1,1,2,3,2,1,2,4,5,5,5,5,5,5,5,5,5,5,5,5,4,3,3,3,4,4,4,4,2,1,1,3,5,5,,1,,3,4,5,6,7,,,10,,,,,1,2,3,4,5,6,7,8,9,10,11,,13,,1,2,3,4,5,6,,,9,2,1,,1,,3,2,14,,0,Non practicing agnostic Catholic 
-12761206903,1,4,2,1,3,2,3,3,4,5,3,4,2,3,4,4,5,4,2,5,5,5,5,5,4,5,5,5,4,4,3,3,5,0,5,4,3,2,2,2,5,5,,,,,,,6,7,,9,10,,,13,,,,,,,6,7,,9,10,11,,13,,1,2,3,4,5,6,7,,9,2,1,,,,3,2,17,,1,
-12761204649,1,4,3,1,4,5,2,2,2,2,2,3,2,1,1,3,4,5,4,4,4,4,4,5,2,4,4,4,3,5,3,3,5,4,4,2,3,1,1,2,3,1,,1,,3,,,6,7,,,,,,,,,2,,,,,,,9,10,,,,,,,,,,,,8,9,2,1,,,,3,2,7,,5,
-12761202422,1,2,1,1,2,4,1,4,3,5,1,3,1,1,2,3,4,3,1,4,3,5,4,3,5,5,4,1,5,2,1,4,5,3,5,1,2,2,1,1,3,5,,,,,4,,,7,,,,11,,,,,,3,4,,6,7,,,,11,,,,1,,3,4,5,6,,,9,2,1,,,,3,2,17,,5,
-12761197158,1,2,1,1,4,4,3,2,3,5,3,4,1,1,1,4,5,4,4,2,5,4,5,5,2,2,2,4,4,3,2,2,4,5,4,3,3,1,1,2,3,3,0,,,,,,,,,,,,,,,,,3,,5,,7,,9,10,11,,,,1,2,3,,,6,,,,2,2,,,,,3,14,,12,
-12761193917,1,3,2,3,3,2,1,1,3,4,1,2,1,1,2,1,2,2,2,4,2,3,4,3,3,5,3,4,3,2,2,3,3,0,3,2,1,1,2,2,6,4,,1,,3,4,5,6,7,,,,11,12,13,,1,,3,4,5,6,7,,,,,,,,,2,3,4,,6,,,9,2,1,,,,3,2,14,,0,I’m not sure.
-12761193586,1,3,2,1,2,1,1,1,2,3,1,2,1,2,2,2,4,4,3,3,4,5,5,5,4,5,5,5,4,4,3,2,4,4,5,3,3,1,1,3,5,4,,,,,,5,6,7,,,10,,,,,,,,,5,,7,,,10,11,,,,1,2,3,,5,,,,,2,2,,,,,2,7,,11,
-12761188306,1,4,3,1,1,1,1,1,1,1,1,1,2,1,1,1,1,5,2,1,1,2,3,1,5,1,2,5,5,3,3,3,5,5,5,2,3,1,1,2,3,3,,,,,,5,6,7,,9,10,11,,,,,,,,5,6,7,,9,10,11,,,,1,2,3,4,5,,,,9,2,2,,,,,1,4,,11,
-12761181648,1,2,1,2,5,1,4,2,4,5,4,5,1,2,5,5,5,2,5,5,3,5,5,5,1,5,5,5,5,4,1,3,5,4,5,3,2,2,2,3,5,5,,,,,4,5,6,7,,9,,11,,,,,,,,,6,7,,,,,,,,,,3,,5,,,,,2,2,,,,,2,14,,17,
-12761179370,1,3,2,1,2,3,2,2,3,2,2,1,1,1,3,2,5,5,5,5,5,5,5,1,3,2,5,5,3,3,3,2,3,3,4,1,2,1,2,1,4,3,,1,,3,,5,6,7,,9,,11,,,,,,,,5,6,7,,9,,,,,,,,3,4,5,6,,,9,2,2,,,,,1,14,,2,
-12761177527,1,4,3,1,2,2,4,2,1,1,1,2,2,4,4,4,1,4,4,1,1,1,1,2,4,5,5,4,4,5,4,4,4,3,4,3,3,5,2,2,4,4,,,,,,,6,7,,,,,,,,,,,4,,6,7,,9,,,,,,,,3,4,,,,,,1,1,,1,,,2,14,,5,
-12761174012,1,3,2,1,4,2,2,2,2,4,2,2,2,4,4,2,2,2,2,2,2,2,2,3,4,4,5,2,5,4,4,3,4,4,4,2,3,1,2,3,5,5,,1,,3,,5,6,7,,,10,,,13,,,,3,4,5,6,7,,,10,,,13,,1,2,3,4,5,6,,,9,2,2,,,,,2,10,,2,
-12761167193,1,4,3,1,3,3,4,1,3,3,3,3,1,2,5,4,3,2,2,2,2,5,4,2,3,5,5,3,4,4,3,1,5,5,3,1,1,1,1,1,3,3,,,,3,4,,6,7,,,10,,,,,,,3,4,5,6,7,,,,,,,,,2,3,4,5,,,,,2,2,,,,,2,7,,5,
-12761163615,1,2,1,1,3,3,2,2,4,5,2,2,1,1,1,3,4,3,1,3,4,4,4,2,4,2,1,2,4,4,2,3,4,4,4,1,2,2,1,1,5,5,,,,,,5,6,7,,,10,,,,,,,,,5,6,,,,,,,,,,,,,5,,,,,2,1,,,,3,2,11,,1,
-12761154735,1,4,3,1,4,1,2,1,2,3,3,4,2,5,5,5,4,1,3,2,2,3,2,4,4,5,5,5,3,2,2,3,4,3,3,4,3,4,2,1,3,5,,1,,3,4,5,6,7,,,10,,,13,,1,,3,4,5,6,7,,,10,,,,,1,2,3,4,5,,,,,2,1,,1,,,2,14,,17,
-12761141179,1,4,3,1,1,3,5,1,2,5,2,1,1,2,1,2,1,5,5,3,5,5,5,2,5,2,4,5,4,3,3,,,4,5,4,3,1,1,5,5,4,,,,,,5,6,7,,9,,,,13,,,,,,5,6,7,,9,,,,13,,,2,3,4,5,6,,8,9,2,2,,,,,1,4,,1,
-12761137579,1,3,3,1,2,3,2,2,3,4,1,2,1,1,4,1,3,3,2,5,3,3,5,5,5,5,4,3,3,3,2,4,3,3,3,1,2,3,3,1,3,5,,,,,,,6,7,,,,,,,,1,,,,,6,7,,9,10,,,,,,,3,4,,,,,,2,2,,,,,2,14,,17,
-12761133280,1,2,1,1,3,2,2,1,3,2,1,2,1,1,2,2,4,2,2,4,4,3,3,4,1,4,4,4,3,3,2,2,3,3,3,1,1,1,1,1,2,1,,1,,3,,5,6,7,,,10,11,,,,1,,3,4,,6,7,,,,,,,,1,2,3,,,6,,,,2,1,,1,,,2,14,,5,
-12761132188,1,2,1,1,4,3,2,1,5,4,2,4,2,1,3,2,4,3,2,1,2,4,3,4,2,3,5,5,4,2,2,4,3,4,3,1,1,1,2,1,3,5,,1,,3,,5,6,7,,9,,,,,,1,,,4,5,6,7,,9,,,,,,,,3,4,,,,,9,2,1,,,,3,2,2,,11,
-12761131522,1,4,3,1,4,3,1,2,3,5,3,3,1,1,4,3,5,3,1,5,5,5,5,5,5,5,5,5,3,2,1,1,3,3,3,2,1,1,2,2,5,5,,,,,4,5,,7,,,10,,,,,1,2,,4,5,,7,,,10,,,,,,2,,,5,6,,,,2,2,,,,,2,12,,17,
-12761130526,1,2,1,3,3,1,3,1,2,3,2,4,2,4,5,3,3,2,3,1,2,3,2,5,2,4,5,4,3,2,3,5,2,4,4,3,1,1,4,1,4,5,0,,,,,,,,,,,,,,,1,,3,,5,,7,,,,,,,,1,2,3,,5,,,,,2,1,,1,,,2,14,,2,
-12761129523,1,3,2,1,4,2,2,2,3,3,2,3,2,1,1,1,1,4,3,2,5,3,5,4,5,1,3,5,3,3,1,3,4,3,4,2,2,1,1,1,5,5,,,2,3,,5,6,7,8,9,10,,,,,,2,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,7,,5,
-12761123869,1,3,2,1,3,4,4,3,3,4,4,4,3,1,2,3,3,4,3,4,4,5,5,5,5,2,3,4,3,3,3,3,3,4,4,2,3,1,1,2,5,5,,,,,4,5,,7,,9,10,,,,,,,,4,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,1,14,,1,
-12761120017,1,2,1,1,2,2,4,2,4,4,1,,1,1,3,3,5,2,2,5,5,5,5,5,5,2,5,5,2,2,4,4,3,4,5,4,3,1,1,1,5,5,,,2,,4,,,7,,,,11,,,,1,2,3,4,,,7,,,,,,,,1,2,3,,5,,,,9,2,1,,,,3,2,14,,0,Roman Catholic 
-12761117803,1,4,3,1,4,4,2,2,2,4,4,1,2,2,5,1,4,4,2,2,3,4,4,1,4,4,4,1,4,4,3,3,5,5,5,4,4,1,1,2,4,4,,,,,,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,,,3,,,,,,,2,2,,,,,2,14,,17,
-12761115670,1,3,2,1,4,3,1,4,4,4,2,4,4,3,4,2,4,4,3,0,4,4,4,4,4,4,4,4,3,2,2,2,4,4,3,1,3,2,1,2,3,3,,,,3,4,5,6,7,,,10,11,,,,1,,3,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,,8,9,2,1,,1,,3,2,15,,5,
-12761115090,1,2,1,1,5,5,3,2,4,5,4,4,2,2,1,1,5,4,2,5,2,5,4,2,5,2,1,5,4,5,3,2,5,4,4,2,1,1,1,1,5,5,,,,,,5,6,7,,,,,,,,1,,,,5,6,,,,,,,13,,,2,,4,,,,,9,2,2,,,,,2,3,,2,
-12761114080,1,4,3,1,2,2,2,2,2,4,1,2,1,1,1,1,3,2,2,2,3,2,3,3,4,3,4,1,4,3,3,4,4,3,4,2,4,2,2,2,5,5,,1,,3,,,,,,,,,,,,,,,,5,6,7,,,,,,,,,,3,,5,,,,,2,1,,,,3,2,17,,5,
-12761113833,1,2,1,2,4,2,2,5,3,5,2,4,1,2,3,2,4,3,3,5,5,5,5,4,4,5,5,5,4,3,3,5,1,4,5,1,1,1,1,1,6,6,,1,,,,,6,7,,,,,,,,1,,,4,5,6,7,,,10,11,,13,,1,,3,4,5,6,,,,2,1,,,,3,2,4,,11,
-12761110743,1,2,2,3,5,5,5,4,5,5,5,5,4,2,4,4,4,5,4,5,4,4,5,5,5,2,3,5,3,2,3,3,4,4,4,2,3,1,1,1,3,1,,,,,,5,6,,8,,10,,,,,,,,,5,,7,,,,11,,,,1,,3,,,,7,,9,2,1,,,,3,2,5,,17,
-12761101815,1,2,3,1,5,4,4,2,3,3,2,4,1,1,4,1,5,5,5,5,5,5,5,5,5,2,2,3,0,5,2,5,5,0,5,4,3,1,1,3,6,1,0,,,,,,,,,,,,,,,1,,3,,,,7,,,,,,,,,,3,,5,,,,9,2,2,,,,,1,3,,11,
-12761100891,1,3,3,1,4,4,4,3,4,4,4,4,3,3,4,4,4,4,3,3,4,4,4,5,5,4,5,4,4,4,3,3,4,4,4,4,3,4,3,2,3,5,,,,,,,,,,9,10,,,,,,,,,,,,,9,,,,,,,,,,5,,,,9,2,2,,,,,2,14,,5,
-12761099388,1,4,3,1,2,2,2,4,2,2,2,3,2,3,4,3,3,2,2,4,3,3,3,3,4,4,5,4,3,2,2,3,3,3,3,3,2,2,1,1,5,5,,,,,,,6,7,,,10,,,,,,,,,,6,7,,9,10,,,,,,2,3,4,5,,,,,2,1,,1,,,2,3,,11,
-12761093887,1,3,2,1,4,4,2,2,4,4,2,2,2,2,2,2,3,2,2,5,5,5,5,5,1,5,4,5,5,4,2,3,5,5,4,4,2,1,1,1,3,5,,,,,,,6,,,,,,,,,,,,,,6,7,,,,,,,,1,,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12761092217,1,2,1,1,4,4,2,5,4,2,2,4,2,2,4,2,3,5,3,5,3,4,4,5,4,5,5,5,3,3,1,3,3,3,2,1,1,1,2,1,5,4,,,,,,,6,7,,9,,,,,,,,,,5,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,6,,11,
-12761090900,1,4,3,1,3,3,1,2,3,4,2,2,2,3,5,1,5,5,2,5,5,5,5,5,5,5,5,1,4,3,2,3,4,4,5,1,3,3,1,1,5,5,,,2,,,,6,,,,10,,,,,,2,,,5,6,7,8,,,,,13,,1,2,3,4,5,,,,9,2,1,,,,3,2,13,,5,
-12761087505,1,2,1,1,1,3,2,1,1,1,2,1,1,1,2,1,1,2,2,1,1,2,2,1,2,1,5,2,1,2,1,2,1,3,3,2,1,1,1,2,4,4,,,2,3,,5,6,7,,9,10,,,13,,,,,4,5,6,7,8,9,10,,,,,1,2,3,4,5,6,7,8,9,2,2,,,,,1,0,,1,
-12761087008,1,3,2,2,5,2,5,3,5,5,5,5,3,5,5,2,3,2,3,3,3,3,3,1,3,3,3,1,5,2,1,5,5,,5,1,1,1,1,1,6,3,0,,,,,,,,,,,,,,,1,,3,4,,6,7,,,,,12,,0,,,,,,,,,,2,1,,1,,,2,7,,11,
-12761085590,1,3,2,3,3,3,1,1,3,3,2,3,2,2,3,2,4,3,1,4,4,4,4,5,4,4,5,5,3,3,2,2,3,3,3,2,1,1,1,1,5,5,,,2,,4,5,6,,,,10,11,,,,,2,,4,5,,,,,10,,12,,,1,2,,4,5,6,,,,2,1,,,,3,3,14,,17,
-12761083865,1,2,1,1,5,3,4,5,5,5,5,5,2,4,5,2,5,1,3,2,5,5,5,5,2,5,5,2,5,1,1,3,5,5,5,3,1,1,2,1,3,5,,,,,,,,,,,10,,,,,1,,3,4,,,,,,,11,,,,1,,3,,5,,7,8,,1,2,,,,,2,9,,5,
-12761082417,1,3,2,1,3,3,3,3,3,3,3,3,3,1,3,3,5,5,5,5,5,5,5,5,5,2,2,3,3,2,3,2,3,3,3,2,2,1,2,2,3,6,0,,,,,,,,,,,,,,,,,,,,,,,9,10,,,,0,,,,,,,,,,2,1,,,,3,1,2,,9,
-12761073632,1,3,2,1,3,1,2,1,4,5,2,4,1,3,4,3,5,4,5,1,5,5,5,5,1,5,5,5,5,3,2,2,5,0,4,1,1,2,2,1,6,5,0,,,,,,,,,,,,,,,,2,3,4,5,6,7,8,9,10,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,14,,2,
-12761073256,1,4,3,1,5,3,3,5,5,5,5,5,3,3,5,3,5,3,5,5,5,5,5,5,3,5,5,5,5,3,5,5,5,5,3,3,3,1,1,5,3,3,,,,,,5,6,7,8,,,,,,,1,,,,,6,7,8,9,,,,13,,,2,3,4,5,,,,9,2,2,,,,,1,17,,17,
-12761071527,1,2,1,1,4,5,4,2,5,5,1,4,2,2,4,5,4,4,1,4,4,5,2,5,4,2,4,4,3,3,1,4,,4,2,4,3,2,4,3,4,4,,,,,4,,6,7,8,9,10,,,,,,,,,,,7,8,9,,11,,,,1,,3,4,5,6,,,9,2,1,,1,,,2,1,,11,
-12761071489,1,4,3,1,4,2,1,1,4,2,1,4,1,2,2,2,2,1,2,5,4,2,5,5,2,5,5,5,4,3,3,3,2,4,3,2,3,1,1,2,5,5,,,,,,5,6,,,9,,,,,,,2,3,,5,,,,9,10,,,,,,,,,,,,,9,2,2,,,,,2,12,,1,
-12761071297,1,4,3,1,4,5,4,1,4,5,2,4,2,1,3,2,4,4,2,4,2,3,5,5,5,2,4,1,3,3,2,2,4,4,4,3,2,1,1,1,3,1,,1,,,,,,7,,,10,,,13,,,,,4,5,6,7,,9,,,,,,1,2,3,,5,,,,9,2,1,,,,3,2,14,,17,
-12761070514,1,2,1,1,5,5,2,2,4,4,2,5,1,2,1,2,3,4,4,5,4,5,5,4,4,2,2,2,2,0,3,2,4,5,5,2,1,1,2,2,2,1,,,,,,5,,7,,,,,,,,,,,,5,,,,,,,,,,1,2,3,4,5,6,,,9,2,2,,,,,1,14,,0,
-12761070011,1,2,1,1,2,3,3,3,3,5,4,4,3,2,1,1,5,5,5,5,5,5,5,5,5,3,1,5,2,4,3,3,4,3,3,2,5,1,1,2,5,1,0,,,,,,,,,,,,,,,,,,,,6,7,,,10,,,,,,,3,,,,,,,2,1,,,,3,1,3,,11,
-12761067690,1,4,3,1,2,2,2,1,4,2,2,4,1,2,4,1,4,4,1,4,4,4,4,4,1,5,4,4,2,3,1,4,5,5,3,1,3,1,1,1,5,5,,1,,,,,6,,,,,,,13,,1,,3,,,,7,,,,,,,,,,,4,,,,,,2,1,,,,3,2,7,,5,
-12761063827,1,4,3,1,2,5,2,4,2,2,1,4,2,1,5,5,2,5,5,5,2,2,2,2,2,5,5,5,2,5,2,5,5,3,5,2,3,1,1,1,2,5,,1,2,3,4,5,6,7,,,10,,,13,,1,2,3,,,6,7,,,10,,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,5,
-12761062925,1,2,1,2,2,3,2,2,4,5,2,2,3,4,4,4,2,2,2,2,2,3,2,4,4,4,3,2,3,3,3,3,3,3,3,3,3,3,3,3,5,5,,,2,,,,6,7,,,10,,,,,,,3,4,5,6,7,,,,,,,,,2,3,4,5,,,,9,1,1,,1,,,2,14,,1,
-12761061445,1,3,3,1,4,4,2,2,3,4,3,2,2,2,4,3,3,3,2,2,4,4,4,4,3,3,4,4,3,2,1,2,3,3,3,2,2,1,2,1,3,3,0,,,,,,,,,,,,,,,,,,4,5,6,7,8,9,10,,12,13,,,2,3,4,5,,,,,2,2,,,,,2,14,,17,
-12761060664,1,2,1,1,2,2,2,1,2,3,2,2,2,2,2,2,5,4,3,4,3,5,5,5,5,5,5,5,5,1,1,3,3,3,4,2,4,1,1,1,5,5,,,,3,4,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,11,,,,1,2,3,4,5,6,7,,9,2,2,,,,,2,2,,14,
-12761058676,1,4,3,1,2,3,2,2,4,4,2,2,2,1,1,3,3,4,3,5,3,3,4,4,5,1,1,4,4,4,3,4,3,3,3,3,3,3,2,4,6,2,0,,,,,,,,,,,,,,,,,,,,6,,,,,,,,,,,,,,,,,9,2,2,,,,,2,6,,11,
-12761058421,1,2,1,1,2,5,3,2,2,4,2,2,2,3,2,2,3,5,,2,2,5,3,2,2,,3,2,4,5,5,2,4,3,,3,2,1,1,1,5,5,,,,,,5,6,,,9,,,,,,,,,,,6,7,,,,,,,,,2,3,4,5,,,,,1,2,,,,,2,4,,11,
-12761055021,1,4,3,1,3,3,4,2,3,2,3,2,5,2,1,1,5,5,5,2,5,5,5,5,5,4,2,1,3,4,4,4,4,4,,3,4,2,1,1,5,4,,,,3,4,,6,7,,9,,,,,,,,3,4,5,,7,,,,,,,,,2,3,4,5,,,,,2,2,,,,,1,14,,17,
-12761043820,1,3,3,1,3,5,5,5,2,2,2,5,5,2,5,5,5,5,5,5,5,5,5,5,5,4,5,5,3,3,1,4,3,4,3,2,2,1,2,2,4,4,,,,,,,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,,,4,,,,,,2,1,,,,3,2,4,,11,
-12761035861,1,2,2,1,3,4,3,2,4,4,4,2,2,2,2,3,5,5,5,5,5,5,5,5,5,2,4,5,4,2,2,2,4,4,3,2,4,1,1,1,4,3,,,,3,,,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,17,,8,
-12761033563,1,2,2,2,3,4,4,4,4,3,4,2,3,2,3,1,4,4,4,4,4,4,4,2,4,4,4,1,5,3,3,5,4,4,5,3,4,2,1,1,2,1,,1,,3,,,,7,,9,,,,,,1,,3,,5,,7,,9,,,,,,,,3,4,,,,,9,2,2,,,,,1,2,,9,
-12761028059,1,3,2,2,2,2,1,5,3,5,2,5,2,3,5,1,3,2,1,5,3,5,2,2,2,5,5,1,3,1,1,3,3,3,3,1,1,3,3,1,5,5,0,,,,,,,,,,,,,,,,,3,,,6,,,,,,,,,,,,4,5,6,,,9,2,1,,,,3,2,4,,11,
-12761024859,1,4,3,1,2,5,2,1,2,2,2,2,1,1,2,1,2,5,2,1,2,4,2,2,1,1,2,1,4,3,4,4,5,5,4,1,3,1,2,2,3,2,,,,3,4,5,6,7,,9,10,,,,,,,3,4,5,6,7,,,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,14,,17,
-12761023691,1,3,2,1,4,2,1,1,2,4,2,3,1,2,2,2,4,2,1,4,3,3,3,5,2,5,4,3,3,3,3,1,2,3,3,4,1,1,2,1,3,3,,,,,,5,6,7,,9,10,11,,,,,2,,4,5,6,7,,9,10,11,,,,,2,3,,5,,,,9,2,2,,,,,2,14,,2,
-12761022717,1,2,2,2,2,1,2,2,2,5,2,4,2,1,3,3,5,5,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,1,1,1,3,1,3,1,,,,,,5,6,,,,,,,13,,,,,,,6,7,,,,,,13,,,,3,,5,,,,,2,1,,,,3,2,9,,5,
-12761022670,1,4,3,1,4,3,3,2,4,4,2,4,2,2,4,2,4,4,4,2,4,4,4,4,4,2,4,2,3,3,2,3,3,3,3,3,2,2,2,2,3,5,,,,,,5,6,7,,9,10,,,13,,,,,,5,6,7,8,9,10,,,13,,1,,3,4,5,,,,9,2,1,0,,,,2,14,,17,
-12761018413,1,4,3,1,2,3,2,2,2,4,2,2,4,2,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,2,1,4,5,0,3,3,4,2,2,2,6,5,0,,,,,,,,,,,,,,,,,,,,6,7,,,,,,,,1,,3,4,,,,,,2,2,,,,,2,2,,14,
-12761014097,1,4,3,1,3,3,2,1,3,3,2,2,1,1,2,3,5,4,4,4,4,4,4,5,3,3,5,5,3,3,1,3,3,4,3,2,3,1,1,1,5,5,,,,,,5,6,7,8,9,10,,,,,,,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,9,,5,
-12761013546,1,4,3,1,2,2,2,2,2,2,2,2,2,2,2,2,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,,,,,4,5,6,7,,,,,,13,,,,,4,,6,7,,9,,11,,13,,1,2,3,,,6,,,,1,1,,,,3,2,14,,17,
-12761010664,1,3,2,1,3,3,3,2,2,3,2,2,2,1,1,2,3,5,5,4,3,4,4,4,5,2,2,4,4,3,3,4,4,4,5,1,3,2,1,2,3,3,,1,,3,,5,6,7,,,,,,,,1,,3,,5,6,7,8,,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,4,0,,2,
-12761009843,1,3,2,3,3,2,1,2,4,4,3,2,1,4,5,3,5,3,2,2,4,5,5,2,2,5,4,5,4,3,1,4,5,4,4,1,3,1,1,1,5,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,,10,,,,0,,,,,,,,,,2,2,,,,,2,14,,1,
-12761008759,1,2,1,1,5,4,2,1,3,2,1,4,3,1,2,4,4,4,4,5,5,4,4,5,5,2,2,4,3,3,2,2,3,3,2,1,2,1,1,2,5,5,,,,,4,5,,7,,9,10,11,,,,,,,4,5,6,7,,9,,11,,,,1,2,3,4,5,6,,,9,2,1,,1,,,2,7,,5,
-12761007915,1,3,2,1,2,2,1,1,4,2,1,1,1,2,5,5,1,1,1,2,1,2,4,1,5,5,5,5,4,3,4,1,2,4,4,2,5,2,1,5,5,5,,,,3,,5,6,7,,9,10,11,,,,,2,3,,,6,7,,,10,,,,,1,2,3,4,5,6,7,8,9,2,1,,,,3,2,4,,17,
-12761006498,1,2,1,1,4,4,2,2,,4,2,3,2,4,2,4,5,5,2,2,5,5,5,5,5,5,5,5,4,4,2,4,5,3,4,3,2,2,1,3,5,5,,1,,,,,,7,,,,,,,,,,3,,,6,7,,,,,,,,,,3,,5,,,,,2,1,,1,,,2,14,,1,
-12761005521,1,4,3,1,4,5,1,2,3,4,3,2,3,1,3,4,5,5,3,5,5,5,5,5,5,2,5,5,3,3,3,3,4,4,3,2,3,2,1,3,2,2,,1,,,,5,6,,,9,,,,,,,,,,5,6,,,9,,,,,,,2,3,4,5,,,,,2,2,,,,,2,14,,17,
-12761002443,1,4,3,1,2,4,2,1,2,2,2,3,1,5,5,2,2,5,4,1,5,4,5,2,1,5,5,5,2,4,3,1,3,3,3,2,1,1,1,3,4,4,,1,,3,,5,6,7,,9,10,,,,,,,3,4,5,6,7,,9,10,11,,,,,2,3,4,5,,,,9,2,1,,1,,3,2,14,,1,
-12761002177,1,2,1,3,5,5,5,5,5,3,2,5,2,2,2,4,3,4,3,5,4,4,4,5,4,2,2,4,4,3,2,2,4,0,4,3,2,1,1,1,5,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,9,10,,,,,,,3,,5,,,8,9,2,1,,1,,3,1,2,,11,
-12760999532,1,3,2,1,2,2,1,2,2,5,2,4,1,2,4,2,5,2,2,5,5,5,5,5,2,5,5,5,3,1,1,3,3,0,4,2,2,3,1,1,6,4,0,,,,,,,,,,,,,,,,2,3,4,5,6,7,,9,10,11,,,,1,2,3,,5,6,,,9,2,2,,,,,3,14,,2,
-12760997890,1,4,3,1,3,3,3,2,2,3,2,3,2,2,3,2,4,,5,5,5,5,5,5,5,5,5,3,4,3,3,3,3,3,3,3,3,1,1,1,4,1,,,,,,,6,7,8,,10,,,,,,,,,,6,7,8,9,,,,,,1,,3,4,,6,,,,2,2,,,,,2,6,,5,
-12760996543,1,3,3,1,2,4,2,1,4,5,5,2,1,1,1,1,5,5,5,5,5,5,5,2,5,1,1,5,3,3,3,4,3,5,5,2,3,1,1,1,1,1,,,,,,5,,,,9,,,,,,,,,,,,,,9,,,,,,1,2,3,,5,6,,,9,2,2,,,,,1,14,,2,
-12760995905,1,2,1,1,2,2,1,1,1,1,1,3,1,1,1,1,4,5,4,4,5,5,5,3,5,2,3,2,4,,5,4,3,4,4,3,3,1,1,2,3,4,,,,,,,6,7,,,,,,,,,,,,,6,,,,,,,,,,,3,4,5,6,,,9,2,2,,,,,2,6,,4,
-12760991947,1,2,2,1,,,,,,,,,,1,,,,,,,,,,,,3,,,2,2,1,2,3,2,3,1,3,1,1,1,5,5,,1,,3,4,5,6,7,,,,11,12,,,,2,3,,5,6,7,,,10,11,,13,,1,2,3,4,5,6,7,8,9,2,1,,1,,,2,3,,11,
-12760984728,1,4,3,2,4,5,2,4,4,5,5,4,2,1,5,4,3,3,3,5,3,4,4,4,4,3,5,5,4,3,2,4,3,4,5,3,3,4,2,2,5,4,,,,3,,5,6,7,,,10,,,,,,,3,4,5,6,7,,,10,11,,,,,2,3,4,5,6,,,,2,1,,,,3,2,14,,5,
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-12760976105,1,2,1,1,4,2,2,2,4,4,2,4,2,,5,2,4,1,1,4,4,4,4,2,1,5,5,4,4,4,3,2,3,5,3,1,1,2,2,1,5,5,,1,,3,4,,,7,,,10,,,13,,,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,17,
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-12760964033,1,4,3,1,4,4,2,2,4,4,2,4,2,2,4,3,4,4,1,4,4,4,4,4,4,4,2,3,3,3,2,1,3,5,4,2,1,2,1,1,5,3,,,2,,,5,,7,8,,10,,,,,,,,,5,6,7,,9,10,,,13,,1,2,3,,5,6,,,,2,1,,,,3,2,3,,11,
-12760962746,1,4,3,1,4,4,2,4,3,4,2,4,4,2,4,4,5,5,3,5,4,5,4,4,5,3,5,5,4,3,3,3,4,3,3,3,3,1,2,2,3,5,,,,3,4,,6,,,9,10,11,,13,,,,,,,6,7,,9,,11,,,,,,,4,5,6,,,9,2,1,,1,,,2,3,,11,
-12760958261,1,3,2,1,2,1,1,1,2,5,2,2,1,1,5,5,5,1,1,5,5,5,5,5,5,5,5,5,2,1,1,2,2,2,3,1,1,1,1,1,5,5,,,,,4,,6,7,,,,11,,,,,,,,,6,7,,,,,,,,,,3,4,5,6,,,9,2,1,,,,3,2,4,,11,
-12760955290,1,4,3,1,1,2,4,2,1,2,2,2,1,2,5,2,1,2,3,4,1,2,2,4,1,4,5,5,4,3,1,2,4,4,4,2,2,1,1,1,5,5,,,,3,,5,6,7,,,,11,,,,,,3,,5,6,7,,,,11,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,5,
-12760952466,1,4,3,1,3,0,3,2,2,3,3,3,3,1,3,1,5,5,2,4,2,5,5,4,5,5,5,3,1,1,3,3,3,1,5,1,4,1,1,1,5,5,,,2,,,,,,,,,,,,,,,,,5,6,7,,,10,,,,,,,3,,,,,,9,2,1,,,,3,2,6,,9,
-12760949596,1,2,1,2,4,4,3,1,5,5,4,4,2,2,5,1,5,3,3,2,4,4,5,3,5,5,5,3,4,4,2,1,1,5,4,1,4,1,1,2,5,3,0,,,,,,,,,,,,,,,,,,,5,6,7,8,9,10,,,,,,2,3,4,5,,,,,2,2,,,,,2,7,,5,
-12760949117,1,3,2,1,4,3,3,4,4,4,4,4,3,4,4,3,4,3,3,4,4,4,4,4,4,4,4,3,2,2,1,2,2,3,2,1,2,1,1,1,3,4,,,,,,,6,7,,,,,,,,,,,,5,6,7,,,,11,,,,,,3,4,,,,,,2,1,,,,3,2,13,,5,
-12760948816,1,4,3,1,2,4,3,2,2,4,4,4,4,2,1,3,1,2,2,2,1,5,5,2,4,2,1,2,4,2,2,3,3,4,3,1,1,1,1,1,2,2,,,,,,5,6,7,8,9,10,,,,,,,,,5,6,7,8,9,10,,,,,,2,3,4,5,6,,8,9,2,2,,,,,2,0,,1,
-12760944908,1,4,3,1,2,2,2,2,5,5,2,2,2,2,2,2,5,2,2,5,5,5,5,5,2,5,5,5,2,,5,3,2,,3,5,3,5,5,4,6,5,0,,,,,,,,,,,,,,,,2,3,4,5,6,7,,,10,11,,,,,2,3,4,5,,,,,2,2,,,,,2,1,,5,
-12760943188,1,3,2,2,4,4,2,2,4,5,2,2,2,2,2,1,4,4,4,2,4,4,4,4,4,4,5,1,4,4,3,2,4,4,4,3,2,2,1,3,5,5,,1,2,,,,6,,,9,10,,,,,,,,,5,,,,,,,,,,1,2,,4,5,,,,,2,2,,,,,2,4,,11,
-12760942810,1,3,2,1,4,1,2,4,1,2,1,2,1,1,4,4,5,2,2,5,2,4,4,5,4,1,4,3,4,2,4,5,4,4,5,3,4,2,1,1,5,5,,,,,4,5,6,7,,,10,,,,,,,,,,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,1,,1,,,2,2,,14,
-12760938725,1,2,2,1,2,3,2,2,5,4,4,2,2,2,5,3,5,5,2,2,2,5,5,1,5,5,3,5,4,4,2,1,,4,4,,2,1,1,1,5,5,,,2,,4,,6,7,,,,,,13,,,2,,,5,,7,,,10,,,13,,,2,3,4,5,,,,9,2,1,,,,3,2,4,,11,
-12760937111,1,2,1,1,5,5,4,2,3,4,2,,2,2,3,3,4,4,4,4,5,4,4,4,5,4,5,4,3,1,,1,2,4,1,3,2,1,2,1,1,2,,1,,,,,6,7,,,,,,,,1,,3,4,5,6,7,8,9,,,,,,,,3,4,5,6,,,,2,2,,,,,2,14,,2,
-12760934098,1,4,3,1,2,4,2,1,4,2,2,2,1,1,2,4,4,3,3,1,4,4,4,3,2,4,5,4,4,3,3,3,4,4,4,2,4,2,2,1,4,4,,,,,,,6,,,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12760933214,1,3,2,1,3,5,5,5,5,5,5,5,3,1,1,2,5,5,5,5,5,5,5,5,5,1,2,3,4,3,4,3,5,4,4,3,4,1,1,3,5,5,,1,,3,4,,6,,,,10,11,,,,,,3,,5,6,7,,,10,,,,,1,2,,4,,,,,9,2,1,,,,3,1,4,,11,
-12760931465,1,4,3,1,3,4,2,2,4,4,2,2,2,1,3,1,2,2,2,2,4,3,4,4,5,5,5,2,4,4,3,3,4,4,4,3,3,1,1,1,5,5,,1,,,,5,6,7,8,9,10,,,,,,,3,,5,6,7,8,9,10,,,,,1,2,3,4,5,6,,,9,2,1,,1,,,2,6,,9,
-12760930725,1,2,1,1,2,2,2,3,3,5,2,1,1,1,4,3,3,3,1,5,2,3,5,1,4,1,5,4,5,3,1,4,4,3,4,2,3,2,2,3,6,5,0,,,,,,,,,,,,,,,1,,,4,5,,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,3,14,,2,
-12760930448,1,4,3,2,1,2,2,2,5,3,2,1,2,2,5,4,1,5,5,4,4,4,4,1,4,4,5,5,4,3,1,2,4,4,4,2,2,1,1,3,1,5,,,,,,5,6,7,,9,10,,,,,,,,,,6,7,,9,,,,,,,,3,,5,,,,9,2,2,,,,,1,14,,1,
-12760930444,1,4,3,1,4,1,1,3,4,5,3,3,2,2,4,2,5,5,2,3,5,5,5,5,2,4,5,5,3,4,2,2,4,4,3,2,1,1,1,1,3,3,,,,,,,6,7,,,,,,,,1,,3,4,5,6,7,,,,11,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760929969,1,3,2,1,4,3,2,3,4,5,4,5,3,2,3,4,4,5,4,5,5,5,5,5,5,1,4,5,2,4,4,2,4,3,3,3,2,1,1,2,5,5,,,,3,4,5,6,7,,,,11,,,,,,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,5,
-12760928970,1,3,2,1,5,3,3,2,4,4,5,4,2,1,3,3,4,4,4,1,3,3,4,4,4,1,4,4,5,3,3,2,5,5,5,2,2,1,1,4,6,3,,,,,,,,7,,,10,,12,,,1,2,3,4,5,6,7,8,9,10,11,12,13,,,,3,4,5,6,,,9,2,2,,,,,2,2,,9,
-12760928525,1,4,3,1,2,4,5,1,4,2,2,2,1,5,5,1,5,4,2,4,5,5,5,1,2,5,5,5,4,3,3,3,5,5,5,2,2,1,1,3,5,5,,1,,3,,,,7,,,,,,,,1,,,4,,6,,,,,,,,,,,3,4,,,,,,2,2,,,,,2,2,,9,
-12760926489,1,2,1,1,4,2,4,1,4,4,4,1,4,5,5,5,4,4,5,1,4,5,5,2,5,5,5,5,4,5,4,4,5,5,4,4,4,2,1,1,5,5,0,,,,,,,,,,,,,,,,,3,4,5,6,7,,,,,,,,1,2,3,4,5,6,,,,2,1,,,,3,1,14,,2,
-12760921675,1,2,1,1,4,4,3,2,3,4,2,4,1,1,1,4,5,5,3,4,5,5,5,5,2,1,2,5,3,2,4,2,3,3,3,2,2,1,1,1,3,4,0,,,,,,,,,,,,,,,,,,,5,6,7,,,10,11,,,,,,3,,5,6,,,9,1,1,,,,3,2,5,,1,
-12760918365,1,2,1,1,2,4,1,3,2,5,1,2,2,2,4,2,1,3,5,4,2,3,3,1,1,5,5,3,2,4,3,3,2,4,5,3,1,1,1,1,3,5,,1,,,,,6,7,,,,,,13,,,,3,4,5,6,7,,9,,11,,,,,,3,4,5,,,,9,2,1,,1,,,2,17,,5,
-12760916564,1,4,3,1,2,2,2,1,3,4,3,2,1,1,2,2,4,2,2,4,4,4,5,4,3,3,4,4,3,3,3,2,4,4,4,3,1,1,2,3,3,1,,,,,4,5,6,7,,9,10,11,,,,,,,,,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,17,
-12760913735,1,2,2,1,4,2,4,3,4,4,2,2,2,2,4,1,4,3,3,4,4,4,4,3,3,5,5,4,3,2,1,2,4,4,2,1,1,1,2,1,5,5,,1,,,,5,6,7,,,10,,,,,,,,,5,6,7,,,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,14,,5,
-12760913499,1,2,1,1,2,4,4,3,2,1,1,2,3,3,5,4,2,5,4,3,2,2,1,3,3,5,5,4,3,4,3,2,3,3,2,2,2,2,1,3,5,5,,,,,4,5,6,7,,,,,,,,,,,4,5,6,7,,,,,,,,1,,3,4,,6,,,,1,1,,1,,3,2,14,,5,
-12760911797,1,4,3,1,3,2,1,2,2,3,2,2,2,2,4,4,4,2,1,2,3,4,4,2,2,5,4,5,3,3,3,3,3,3,3,3,3,3,3,3,5,5,,,,3,4,,6,7,,,10,11,,,,,,,,5,6,7,8,,10,,,,,,2,3,4,5,,,,,2,2,,,,,2,14,,12,
-12760911303,1,2,2,1,5,5,3,5,5,2,5,5,4,1,5,5,5,5,5,5,5,5,5,5,4,3,4,5,5,2,1,2,5,5,5,2,5,1,3,1,5,5,,1,2,3,4,5,6,7,8,,10,11,,,,1,2,3,,5,6,7,,,10,11,,,,1,2,3,4,5,6,7,,9,3,3,,,,,4,0,,0,
-12760909433,1,4,3,1,4,4,1,4,4,5,5,4,2,4,4,2,2,2,1,5,3,5,4,4,2,5,5,5,3,2,3,3,4,3,4,4,4,2,4,2,4,5,,,,3,,,6,7,,,,,,,,1,,,4,5,6,,8,,,11,,13,,,,,,5,6,7,,9,2,2,,,,,2,14,,1,
-12760909054,1,2,1,1,3,3,1,2,2,5,1,1,2,1,1,2,4,4,2,4,3,5,5,1,5,1,1,4,5,3,4,3,3,4,4,2,2,1,1,3,6,5,,1,,,,,6,7,,9,,11,,,,,,,4,5,6,7,,9,,11,,,,,,3,4,5,,,,9,2,1,,1,,,1,5,,2,
-12760908935,1,4,3,1,5,2,1,2,4,5,4,5,4,1,2,4,3,2,1,4,4,3,5,4,4,2,4,5,3,2,3,3,3,3,3,2,2,1,1,1,6,5,,,,,,5,6,7,,,,,,,,,,,4,5,6,,,9,,,,,,1,2,3,,5,,,,9,2,2,,,,,2,5,,1,
-12760908087,1,3,2,1,5,3,1,2,5,5,4,4,1,2,5,4,5,5,3,5,5,5,5,5,4,5,5,5,5,3,2,4,4,5,5,1,3,1,2,1,5,5,,,2,,,5,,7,,,10,,,,,,,3,,5,6,7,,,,,,,,1,2,,,,6,,,,2,1,,,,3,2,1,,5,
-12760906649,1,4,3,1,5,5,5,5,5,5,5,5,5,3,2,4,5,5,5,5,5,5,5,5,5,5,2,5,5,5,4,5,5,5,5,5,5,2,1,4,5,5,,,,,,,6,,,,,,,,,,,,,,,,,9,,,,,,,,,,,,,,,2,1,,,,3,2,2,,9,
-12760902488,1,3,3,1,2,1,1,2,2,5,2,1,2,2,4,2,1,1,2,4,2,2,4,1,4,5,5,4,5,3,1,2,3,4,5,2,2,1,1,1,5,4,,1,,3,4,,6,7,,,,11,,,,,,3,4,5,6,7,,,,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,17,
-12760899532,1,3,2,1,4,4,2,3,4,4,3,3,2,2,4,4,4,4,4,4,4,4,4,4,2,4,4,4,4,2,2,3,4,5,4,3,2,2,2,2,2,3,,,,,,5,6,,,,,,,,,1,2,,,5,,7,,,10,11,,,,,,3,4,5,6,,,9,2,1,,,,3,2,14,,17,
-12760898908,1,2,1,1,2,4,2,4,4,5,5,2,2,2,5,3,1,2,1,5,4,3,4,1,1,5,5,4,2,1,1,2,2,3,4,3,2,3,2,2,3,4,,,,3,4,,6,7,,9,,,,,,,2,,4,5,6,7,8,9,10,11,,,,,,,4,5,6,,,,2,2,,,,,2,14,,15,
-12760898449,1,2,1,2,3,2,1,4,3,4,2,1,1,3,5,2,2,2,2,5,4,4,3,2,5,4,5,2,,2,1,3,4,3,3,,2,1,1,1,5,4,,,,3,4,,6,7,,,,11,,13,,,,,,5,6,7,,,,11,,,,,2,3,4,5,6,,8,9,2,2,,,,,2,6,,11,
-12760898258,1,2,1,1,3,2,1,1,2,4,2,2,2,1,2,2,4,4,3,4,5,4,5,4,5,2,3,4,4,2,2,3,4,4,4,2,2,1,1,1,5,3,,,,,,,6,,,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,,,,,,2,1,,,,3,2,14,,5,
-12760894735,1,2,1,2,5,2,2,2,5,4,3,4,1,4,4,4,3,2,4,4,3,3,3,3,2,5,5,3,5,4,4,4,5,5,5,3,4,2,1,3,5,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,,,11,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12760892337,1,4,3,1,3,4,3,3,2,4,2,3,3,1,4,1,2,4,3,4,3,3,3,4,4,3,4,2,3,3,3,2,3,3,3,2,3,1,1,1,5,5,,1,2,3,4,5,6,7,8,9,10,11,,,,1,,3,4,5,6,7,,9,,11,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,2,,9,
-12760892112,1,4,3,1,2,1,2,2,2,2,2,1,2,2,2,1,2,2,3,3,4,4,5,2,3,3,4,1,2,3,1,3,3,3,4,2,2,1,1,1,2,2,,1,2,3,,5,6,7,8,9,10,,,,,,2,3,4,5,6,7,8,9,,,12,13,,1,2,3,4,5,6,7,8,9,2,1,,,,3,2,17,,5,
-12760891642,1,3,2,1,3,4,2,1,2,5,1,1,2,1,1,1,2,4,4,5,2,3,5,1,5,4,5,2,2,3,1,2,2,5,3,1,2,1,1,1,3,3,0,,,,,,,,,,,,,,,,,3,,,6,7,,,,,,,,1,,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12760891564,1,4,2,1,5,5,1,5,4,4,5,5,2,2,5,3,4,4,3,4,4,4,4,2,4,1,2,2,1,4,4,3,4,4,4,1,1,1,1,1,5,5,,,,3,4,,6,,,,,11,12,,,,2,3,4,5,6,7,,,10,11,,,,1,2,,,5,6,,,9,2,1,,,,3,2,2,,9,
-12760890871,1,3,2,1,1,4,1,2,1,1,2,1,5,4,5,2,1,4,1,1,1,2,2,1,3,5,5,3,2,3,3,4,,3,3,3,2,1,1,2,5,3,,,,,,5,6,7,,9,,,,,,,,,,5,6,7,8,,,,,,,,2,3,4,5,,,,9,1,2,,,,,2,7,,5,
-12760890731,1,3,3,1,2,4,2,2,2,2,2,1,2,2,1,1,5,5,5,4,5,5,5,4,5,2,2,2,5,2,3,2,5,5,4,2,5,2,1,2,5,5,,,2,,,,6,7,,9,10,,,,,,2,,,5,6,7,,9,,11,,,,1,,3,4,5,6,7,,9,2,1,,,,3,1,15,,1,
-12760888236,1,2,2,1,4,2,1,5,5,5,5,5,2,3,5,4,4,3,1,5,5,4,5,5,4,5,5,5,4,3,2,3,4,4,4,3,3,2,3,2,4,4,,,,,,5,6,7,8,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12760886432,1,2,3,1,1,2,1,2,4,4,3,1,1,3,3,3,2,2,2,3,5,5,4,1,2,5,4,5,4,5,3,5,4,5,5,3,2,3,2,4,3,5,,,,,,,6,,,,,,,,,,,,,,6,,,,,,,,,1,,,4,5,,,,,2,2,,,,,2,17,,1,
-12760885313,1,3,2,1,2,,2,2,3,5,2,2,1,1,5,5,4,5,4,5,4,5,,4,5,5,5,5,5,5,2,5,5,5,5,1,4,2,2,1,5,3,,1,,3,4,,6,7,,,,11,,,,1,2,3,,5,6,7,,,10,11,,13,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760884151,1,4,3,1,1,3,2,1,2,2,1,2,1,2,2,2,2,3,4,3,2,2,2,3,1,4,5,5,3,3,2,1,3,3,3,2,1,1,1,2,5,5,,,2,3,,5,6,7,,9,,,,,,,2,3,,,6,7,,,,,,,,,2,3,4,5,,,,9,1,1,,1,,,2,14,,2,
-12760881169,1,2,1,1,2,2,2,1,2,3,2,2,1,1,1,2,3,3,3,1,3,3,3,3,2,4,4,4,4,3,3,2,4,4,4,4,1,1,2,2,2,2,,,,3,,5,6,,,,,,,,,,2,3,4,5,6,7,,,10,,,,,,2,3,4,5,,,,,2,2,,,,,1,17,,12,
-12760880751,1,3,2,1,2,4,2,2,2,2,2,2,2,2,2,2,3,4,4,4,4,4,4,2,4,4,4,2,4,5,1,1,5,5,3,2,3,1,1,1,6,4,,1,,3,,,,,,,,,,,,,,3,,,6,,,,10,,,,,,2,,,,,,,,2,2,,,,,1,17,,5,
-12760878755,1,4,3,1,5,2,2,5,5,5,2,4,2,3,5,3,4,4,3,5,4,5,3,5,2,5,5,5,3,4,5,3,5,5,3,2,2,4,5,2,1,5,,,,3,,5,6,,,,10,,,,,,2,,,5,6,7,8,9,,,,,,,2,,4,5,,,,9,2,1,,,,3,2,14,,5,
-12760876584,1,3,2,1,3,2,1,2,2,5,3,2,2,2,3,3,5,3,2,5,3,5,5,3,5,4,5,3,5,2,1,5,3,4,5,2,3,2,3,1,5,1,,,,,4,,6,,,,,11,,13,,,,,4,5,,,,,,,,,,,2,,,,,,,9,2,,,,,,2,14,,17,
-12760875351,1,3,2,1,3,2,2,2,4,4,2,3,2,3,4,2,4,3,2,5,5,4,4,5,5,3,4,1,4,3,2,3,3,4,4,1,2,2,3,1,5,5,,,,,,,6,,,,,,,,,,,,,,6,7,,,,,,,,,,,,5,,,,,2,1,,1,,,2,7,,17,
-12760875327,1,3,2,1,4,4,3,2,4,4,3,4,2,2,2,2,4,4,4,4,4,4,4,4,4,4,4,4,0,0,0,0,0,0,0,0,0,0,0,0,3,5,,,,3,,,6,7,,9,,,,,,,,,4,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,2,,5,
-12760874330,1,3,2,3,5,5,5,5,5,5,4,5,3,1,3,2,5,5,5,5,5,5,5,5,5,2,5,5,4,4,4,3,5,5,5,3,2,1,1,2,3,3,,1,,,4,5,,7,,,,,,,,,2,,,5,,7,,,,,12,,,,,,4,5,,,,9,2,2,,,,,1,6,,4,
-12760873025,1,4,3,1,5,5,3,1,1,3,1,2,1,1,2,4,5,5,5,4,5,5,4,5,5,1,5,3,5,4,3,4,5,5,3,4,4,1,1,1,2,1,,,,,,,6,7,,9,10,,,,,,,,,,6,7,,9,,,,,,,,3,4,5,,,,9,2,1,,,,3,2,15,,5,
-12760872202,1,4,2,1,1,1,1,4,2,4,1,3,1,4,5,2,2,2,1,5,2,5,3,4,5,5,5,5,4,1,1,4,2,3,3,4,3,2,1,4,3,4,,,2,,,5,6,,8,9,,,,,,,,,,,6,7,,9,,,,,,,2,,4,5,,,,,2,1,,,,3,2,6,,5,
-12760871287,1,2,1,2,2,1,2,1,1,4,2,2,1,1,3,1,5,2,5,5,5,5,5,4,2,5,5,3,5,5,5,2,5,0,5,3,2,1,2,1,5,5,,,,,4,5,6,7,8,,,,,,,,,3,,5,,7,8,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,14,,17,
-12760869016,1,4,3,2,4,3,2,2,5,5,4,4,1,3,5,2,4,4,5,3,4,4,4,3,2,4,4,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,,,,,,5,,,,,,11,,,,,,3,,5,6,7,8,,10,11,,,,,2,,4,5,6,,,9,2,2,,,,,2,15,,17,
-12760867380,1,3,2,1,4,5,2,2,5,5,2,3,4,1,2,4,5,5,5,5,5,5,5,5,5,2,2,5,4,5,4,4,4,4,4,3,3,3,1,3,3,3,,,,3,,5,6,7,,,,,,,,,,,4,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,1,,,2,14,,1,
-12760866227,1,4,3,1,1,1,1,1,1,1,1,1,1,1,2,2,1,2,2,1,1,1,1,1,2,5,5,4,1,2,1,1,3,2,1,2,3,2,3,2,5,5,,,,,,,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,,,3,4,5,,,,9,2,1,,,,3,1,14,,5,
-12760865476,1,2,1,1,1,2,2,1,1,3,1,3,1,1,4,4,1,2,1,2,1,1,2,2,1,4,4,4,3,3,1,3,4,3,3,2,1,1,1,1,5,5,,1,2,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,7,8,,10,11,,,,,2,3,4,5,,,,9,2,1,,1,,3,2,17,,0,
-12760864022,1,4,3,1,1,4,4,2,2,1,1,2,2,2,4,5,2,5,5,1,2,1,1,1,4,5,5,5,2,5,3,3,3,5,4,4,,1,1,4,5,5,,,2,3,4,5,6,7,8,9,10,11,,,,,,3,4,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,1,1,,1,,,2,14,,5,
-12760862184,1,4,3,1,3,3,3,2,4,5,2,2,2,1,4,2,4,4,4,2,3,4,5,3,5,3,5,3,4,3,3,3,3,5,4,3,5,1,2,2,3,5,,1,2,3,,5,6,7,8,9,10,,,13,,,,3,4,5,,7,8,9,,,,,,1,2,3,4,5,6,7,8,9,2,1,,,,3,1,14,,,
-12760862054,1,4,3,1,3,3,2,3,4,3,2,2,2,1,3,,4,2,1,4,1,4,3,2,2,1,1,4,3,2,3,3,2,3,3,2,3,2,2,1,5,5,,1,,3,,,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,1,17,,5,
-12760860580,1,2,1,1,2,4,2,2,2,2,2,2,1,1,2,3,2,3,4,1,2,2,2,3,1,4,5,4,3,3,2,3,3,3,3,3,3,2,2,2,2,2,,,2,3,4,5,6,7,,9,10,,,,,1,,3,4,,6,7,,9,10,,,,,,2,3,4,5,,,,9,1,1,,1,,,2,14,,5,
-12760858723,1,4,3,1,2,2,1,1,3,5,2,2,2,1,2,3,1,1,1,1,3,4,2,3,1,4,4,1,0,2,3,4,0,0,0,2,3,3,1,1,5,5,,,,,4,,6,,8,9,10,11,,13,,,,,,,,7,,9,,11,,,,,,3,4,5,,,,9,2,2,,,,,2,3,,11,
-12760857904,1,3,2,1,5,5,2,2,4,5,2,4,2,2,1,2,4,4,2,5,4,5,4,4,4,4,4,2,4,3,3,4,5,5,3,2,3,1,1,2,5,5,,,,,4,5,6,7,,9,10,11,,13,,,,,4,5,6,7,,9,,11,,13,,1,2,3,4,5,6,7,,9,2,1,,,,3,2,2,,9,
-12760856790,1,2,1,1,1,2,2,1,1,5,2,1,2,1,3,5,1,1,3,1,1,2,1,1,5,5,5,5,3,4,2,3,4,5,5,2,2,1,1,3,5,5,,,,,,,6,7,,,,,,,,,,3,4,5,6,7,,,,,,13,,,2,3,4,5,,,,9,2,1,,,,3,2,4,,11,
-12760855445,1,3,2,1,3,2,3,2,2,5,2,4,3,3,3,1,3,2,2,3,4,4,4,4,5,3,3,2,4,3,2,3,4,3,4,1,3,2,1,1,3,5,,1,,3,,5,6,7,8,9,10,,,,,1,,3,,5,6,7,,9,,,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,3,,11,
-12760854158,1,4,3,1,2,2,2,2,2,4,2,2,2,4,4,4,2,2,2,2,4,4,2,1,4,5,5,2,2,3,2,2,3,3,4,3,2,1,1,2,5,5,,1,,,4,,6,7,,9,10,,,,,1,,3,4,5,6,7,,9,10,11,,13,,1,2,3,4,5,,,,9,2,2,,,,,2,6,,9,
-12760852427,1,2,1,1,3,3,3,2,2,5,2,3,2,1,1,2,5,5,5,4,5,5,5,5,2,3,2,5,4,5,4,3,5,0,4,3,3,1,1,2,5,4,,,,,,,,7,,,,,,,,,,3,,,6,7,,,,,,,,,,3,,5,,,,,2,2,,,,,1,2,,9,
-12760852033,1,4,3,1,1,1,3,2,1,1,2,4,2,2,4,4,1,1,1,3,1,2,2,2,2,4,4,3,4,1,3,2,4,3,3,1,1,2,2,1,5,5,,,,,4,,6,7,,9,,11,,,,1,,3,4,,6,7,,,,,,,,,2,3,4,5,6,,8,9,2,2,,,,,2,5,,1,
-12760850793,1,3,3,1,3,3,1,1,3,4,3,3,1,2,2,4,4,3,2,3,4,4,4,3,4,4,3,4,5,4,1,3,4,5,4,3,3,2,2,1,5,5,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,11,,,,,,3,4,5,6,,,,2,2,,,,,2,14,,1,
-12760850536,1,3,2,2,4,2,4,4,3,4,2,2,3,2,4,2,3,2,4,4,4,4,4,3,4,3,4,2,4,3,2,3,4,4,4,2,3,2,4,2,5,5,,,,,,5,6,7,,9,10,,,,,,,,,5,6,,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,3,,11,
-12760850265,1,3,2,1,4,2,2,2,5,5,3,3,3,1,2,2,3,2,2,4,4,4,3,2,4,1,2,2,3,4,4,3,2,0,2,5,3,5,5,5,4,5,,,,,,5,6,7,,9,10,,,,,,,,4,5,,7,,9,10,11,,,,,2,3,,,6,7,,9,2,2,,,,,1,2,,14,
-12760849631,1,2,2,1,2,4,2,1,2,4,1,2,1,1,1,4,3,3,5,5,2,2,5,5,4,1,2,5,5,3,2,2,4,4,5,2,2,1,2,1,4,1,,,,,,,,7,,,10,,,,,,,,,5,,7,,9,10,,,,,,,3,,5,6,,,9,2,1,,,,3,2,14,,0,
-12760847694,1,3,2,1,3,3,1,1,2,4,1,3,1,1,4,1,2,3,1,2,2,5,3,3,3,5,5,4,2,3,1,2,2,3,2,2,2,4,4,3,4,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,,,,,,,,2,,,5,,,,9,2,1,,1,,,2,14,,5,
-12760847658,1,3,2,1,4,4,3,2,3,5,5,3,4,2,2,3,5,4,4,4,4,4,4,4,4,2,2,5,4,2,3,3,4,5,4,3,3,1,1,1,3,1,,,2,,,,6,7,,9,10,,,13,,,2,,,,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,0,,5,
-12760846871,1,2,1,1,2,5,2,1,4,5,1,4,1,1,4,4,4,2,2,5,4,5,4,5,2,5,5,5,5,3,4,3,5,5,5,1,4,1,4,2,2,3,,1,,3,4,,6,7,,,,,,,,,,,,,6,,,,,,,,,,2,3,4,5,6,,,,2,1,,,,3,2,14,,1,
-12760846103,1,3,2,1,4,4,3,4,3,4,4,4,4,3,3,2,4,4,3,4,4,4,4,4,3,4,5,1,4,1,3,3,2,2,3,3,3,2,3,3,3,2,,1,,,,,,,,,10,,,13,,,,,,,,,,,10,11,,,,,,,,5,,,,,1,3,,,,,2,2,,5,
-12760844588,1,2,1,3,3,2,2,2,3,5,3,4,1,1,3,4,2,5,1,5,4,5,5,4,1,1,4,4,4,2,2,2,3,2,3,3,1,1,1,1,3,3,,1,,3,,5,6,7,8,,10,,,13,,,,3,,5,6,,8,,,,,,,,2,3,4,5,,,,9,2,2,,,,,4,14,,2,
-12760844587,1,3,2,1,5,5,5,3,5,4,3,5,2,2,5,4,5,5,5,5,5,5,5,5,5,5,5,5,2,3,4,2,3,3,3,1,1,1,2,1,3,3,,,,,,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,1,2,3,4,5,,,,9,2,1,,1,,,1,6,,5,
-12760843316,1,2,1,1,2,4,2,2,2,2,4,3,2,2,1,3,3,4,2,5,3,4,4,4,3,2,1,2,3,3,3,3,3,3,4,3,1,2,1,2,2,3,,,,3,,,6,,,,10,,,,,,,,,5,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,5,
-12760841281,1,3,2,1,4,2,1,1,4,4,3,3,2,2,4,1,4,2,2,1,4,4,4,4,3,2,4,4,3,2,2,2,3,3,3,3,2,1,3,1,3,2,,,,,,,6,7,8,,10,,,,,,,,4,,6,7,8,,,,,,,1,,3,4,5,,,,,2,2,,,,,2,14,,17,
-12760840646,1,4,3,1,4,4,3,3,4,4,2,4,2,1,3,3,4,5,5,5,4,4,4,5,5,1,5,5,3,3,3,3,3,3,3,3,2,1,1,2,3,3,,,,,,,6,7,8,,,,,,,1,,,,5,6,7,,,,,,13,,,2,3,4,5,,,,,2,1,,,,3,2,14,,1,
-12760840189,1,2,2,1,2,1,2,2,2,5,2,3,2,2,4,4,5,5,5,5,5,5,5,5,5,5,5,5,3,3,1,3,3,5,3,3,3,2,3,3,5,5,,1,,3,,,6,7,8,9,,,,13,,1,,,,,6,7,8,9,,,,13,,,2,3,4,5,6,,,9,2,1,,1,,3,2,8,,11,
-12760840013,1,3,2,1,2,4,1,2,4,2,2,3,1,1,3,2,4,3,2,4,4,2,3,5,2,1,5,4,5,2,2,4,5,5,5,3,4,1,1,2,4,5,,,,,4,5,6,7,,9,10,,,13,,,2,,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760839886,1,3,2,2,4,4,1,2,4,4,4,4,2,2,4,4,5,5,4,5,5,5,5,5,2,5,5,2,5,2,2,4,5,5,4,2,3,3,1,1,2,1,,1,,3,,5,6,,,,,,,,,,,,,5,6,7,,,10,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,14,,0,Catholic 
-12760839333,1,3,2,2,3,3,3,2,3,2,3,3,2,2,3,3,3,3,3,3,3,3,3,4,3,5,5,3,4,4,3,3,4,4,5,3,2,3,1,1,2,1,,,2,,,5,6,7,,,10,,,13,,,2,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12760838749,1,3,2,2,4,2,4,2,2,4,2,2,2,2,4,2,4,3,3,4,4,4,4,3,4,3,4,2,3,3,2,3,3,3,3,2,4,2,2,3,5,5,,,,,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,3,,11,
-12760837465,1,4,3,1,2,3,2,1,2,1,1,1,2,1,1,1,3,4,4,1,4,3,3,1,5,5,3,4,3,4,2,1,4,3,3,1,3,1,1,2,2,3,,,,3,4,5,6,7,,9,10,11,,,,,,3,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,,,9,2,1,,1,,,1,14,,2,
-12760837314,1,3,3,1,4,5,3,1,4,5,2,4,4,1,1,4,5,5,2,2,5,5,5,3,2,1,2,5,5,5,5,3,5,5,3,4,1,1,1,1,5,5,,,,,,,,,,9,,,,,,,,,4,5,,7,,,,11,,,,,,3,4,5,,,,,2,1,,,,3,2,3,,11,
-12760836888,1,3,3,1,2,2,1,2,2,3,2,3,1,2,4,3,3,1,2,4,3,4,2,5,2,5,5,4,3,3,3,3,3,4,3,1,2,2,1,1,5,5,,,,,,,6,7,,9,,,,,,,,3,,5,6,7,,,,,,,,1,2,3,4,5,6,,,,2,1,,,,3,2,14,,5,
-12760836755,1,2,2,1,2,1,1,2,2,2,2,2,1,2,3,2,2,1,1,2,2,2,2,2,1,2,4,4,4,2,1,3,4,4,4,2,1,2,3,2,5,5,,1,2,3,,5,6,7,8,9,10,,,,,1,2,3,,5,6,7,8,9,10,,,,,,2,3,4,5,,,,,2,2,,,,,2,17,,4,
-12760833630,1,3,3,1,5,4,2,1,3,5,3,4,2,1,2,3,5,2,4,2,3,3,5,3,4,4,1,3,4,2,2,3,2,3,3,1,2,1,1,1,5,5,0,,,,,,,,,,,,,,,,,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,17,
-12760833404,1,4,3,1,4,4,1,4,4,5,2,1,2,2,3,1,5,5,5,5,5,5,5,5,4,5,5,2,0,0,1,0,3,0,0,3,1,1,0,1,6,5,,1,,3,4,,6,,,,,,12,,,,2,,4,5,6,7,,,10,,,,,,2,,4,5,6,,,,2,2,,,,,2,14,,2,
-12760832128,1,3,2,1,5,4,2,5,4,5,4,4,4,3,5,5,4,4,1,4,4,4,4,4,4,4,4,4,3,3,1,3,3,3,3,1,2,3,3,2,2,2,,,,,,5,6,7,,9,,11,,,,1,,,,5,6,7,,9,,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,12,,17,
-12760831792,1,4,3,1,5,4,4,1,5,5,3,4,2,1,4,5,5,5,5,5,5,5,5,5,5,2,5,5,5,4,2,4,5,5,5,4,4,1,1,1,5,5,,1,,3,,,6,7,,,10,,,,,,,,,5,6,7,,9,,,,,,,2,3,,5,,,,,2,2,,,,,2,14,,2,
-12760830782,1,3,2,1,4,2,1,2,4,5,2,4,1,1,5,4,5,5,2,5,5,5,5,5,5,5,5,5,4,3,2,4,3,4,4,2,2,1,2,1,3,5,,,2,,,5,,7,,,10,,,,,,,,,5,,7,,,,,,,,,,3,,,,,,9,2,1,,,,3,2,14,,2,
-12760828691,1,3,2,1,3,3,3,2,4,4,3,4,3,2,5,4,5,5,4,5,5,5,5,5,5,4,5,5,4,3,1,4,3,3,4,3,3,1,2,2,5,5,,,,3,,,6,7,,,,,,,,,,3,,,6,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12760828272,1,3,3,1,4,3,2,3,3,4,2,3,2,3,3,3,4,3,2,4,4,4,3,4,2,5,5,4,4,2,4,3,4,3,3,4,2,2,2,3,5,4,,1,,,,5,6,7,8,9,,11,,13,,,,3,4,,6,7,,9,10,,,,,,2,3,4,5,6,7,,9,2,1,,,,3,2,3,,11,
-12760824328,1,4,3,1,4,5,2,2,5,4,4,2,1,2,3,2,5,5,2,2,5,4,4,5,4,5,5,4,3,4,2,3,4,3,3,4,5,4,2,3,5,4,,,,,,5,6,7,,,10,,,,,,2,3,,5,6,7,,,10,,,,,,,3,4,5,6,,,,2,1,,,,3,2,14,,1,
-12760821467,1,3,2,2,2,4,1,2,3,3,2,3,2,1,3,3,2,2,1,4,2,4,4,4,2,2,5,4,2,2,2,2,2,2,2,1,2,1,1,1,3,3,,,,3,,,6,7,,9,10,,,,,,,3,,,6,7,,,10,,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,14,,1,
-12760820029,1,4,3,1,2,1,1,1,3,2,2,2,1,2,4,2,2,2,2,1,4,3,4,1,2,5,4,4,4,4,3,4,4,5,4,3,3,1,2,2,4,3,,,2,3,4,5,6,7,8,,10,11,,,,,2,3,4,5,6,7,8,,10,11,12,,,1,2,3,4,5,6,7,8,9,2,2,,,,,2,2,,0,Raised Catholic but don’t believe in organised religion 
-12760818859,1,3,3,1,3,4,3,3,4,4,2,1,1,1,4,2,4,4,4,4,4,5,5,2,4,2,5,1,4,4,3,4,5,4,5,2,4,1,2,1,1,1,,,2,3,4,5,6,7,,,10,11,,,,,,3,,5,6,7,8,,,,,,,,,,,5,,,8,9,2,1,,,,3,1,14,,5,
-12760818756,1,3,2,1,4,3,2,3,2,4,3,3,3,5,4,4,2,3,2,4,3,3,3,4,5,,5,4,3,3,2,2,3,3,3,1,2,2,1,1,4,4,,1,2,3,4,5,6,7,8,9,10,11,12,,,1,2,3,,5,6,7,8,9,10,,,,,1,2,3,4,5,6,7,,9,2,2,,,,,2,5,,0,
-12760814436,1,2,1,2,2,3,2,1,4,5,3,2,1,,4,1,3,4,2,5,5,5,5,5,2,5,5,3,3,4,2,3,4,4,5,2,1,1,1,1,5,5,,1,,3,,5,6,7,,9,,,,,,,,3,,5,6,7,8,9,,,,,,,2,3,4,,6,,,9,2,2,,,,,2,2,,1,
-12760814270,1,4,3,1,4,3,2,2,3,4,3,4,2,1,5,4,5,2,2,5,5,5,5,5,4,2,5,5,5,,2,4,3,5,4,3,3,1,1,1,5,5,,,,,,5,6,7,,,10,,,,,1,,3,4,,6,7,,,10,11,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12760813744,1,3,2,1,4,3,1,1,3,2,1,2,1,1,3,2,3,2,4,1,2,2,2,1,2,4,5,3,,3,2,1,3,2,3,2,2,1,1,2,5,5,,,2,3,,5,6,7,8,9,10,,,,,,,3,,5,6,7,8,9,10,,,,,,2,3,4,5,6,,,9,2,1,,1,,3,2,15,,5,
-12760813560,1,2,2,1,3,4,2,2,2,5,2,2,2,2,2,4,5,5,2,5,5,5,5,5,5,5,5,5,4,4,2,4,4,4,4,2,2,4,3,2,5,5,,,,3,,,,,,,10,11,,,,,,,,,6,,,,10,,,,,,,,,5,,,,9,2,2,,,,,2,14,,17,
-12760813363,1,3,3,1,2,1,1,1,1,4,1,1,1,1,1,1,5,5,4,4,4,4,5,5,4,5,5,5,3,2,5,2,4,3,3,1,1,1,1,2,3,5,,,2,,,,,7,,,10,,,13,,,,,,5,6,7,,9,10,,,,,1,2,3,,,,,,,2,2,,,,,2,14,,17,
-12760812565,1,2,1,2,2,3,2,4,3,3,3,4,4,1,3,3,2,4,3,5,3,5,4,5,5,1,3,5,4,3,2,3,0,0,4,0,4,1,1,2,2,3,,1,,3,,5,,,,9,10,,,,,1,2,3,,5,6,7,,,10,,,,,,2,3,4,5,,,,9,2,1,,1,,,2,14,,2,
-12760809233,1,4,3,1,3,4,2,2,3,4,2,3,2,2,4,3,2,3,2,3,2,2,3,2,3,3,2,1,0,0,0,0,0,0,0,0,0,0,0,0,5,5,0,,,,,,,,,,,,,,,,,3,,5,,7,,,,,,,0,,,,,,,,,,2,1,,,,3,4,0,,0,
-12760808503,1,3,1,2,5,2,4,5,3,5,2,3,3,2,5,2,5,2,4,5,4,5,5,3,4,3,5,2,4,3,2,3,4,4,4,2,3,2,3,1,5,5,,,,,,5,6,7,,,10,,,,,,,,,5,6,7,,9,10,,,,,,2,3,,5,,,,9,2,1,,,,3,2,3,,11,
-12760806735,1,2,1,1,2,5,3,2,1,2,3,2,1,1,1,1,4,4,4,4,4,4,5,4,5,2,1,3,4,4,3,4,4,4,5,3,3,2,1,2,5,5,,1,2,3,,,6,7,8,,10,,,,,,,3,,5,6,7,,,10,,,,,,2,3,4,5,,,,9,2,2,,,,,1,5,,5,
-12760805824,1,2,1,1,5,4,3,1,5,5,2,3,1,3,4,4,5,5,1,1,4,5,4,5,2,5,5,2,4,4,2,3,3,3,4,2,3,1,1,1,3,3,,,,,,,6,7,,,,,,,,,,,,,6,,,,,,,,,,,,4,5,,,,,2,2,,,,,2,17,,11,
-12760801533,1,2,1,2,2,2,2,2,3,4,1,2,2,2,3,3,4,3,4,5,4,4,4,4,5,3,5,4,3,2,2,2,3,3,3,1,2,1,1,1,3,5,,,,,,,6,7,,,10,,,,,1,,3,,,6,7,,,,,,,,1,2,3,4,5,,,8,9,2,1,,,,3,2,14,,5,
-12760801210,1,4,3,1,4,2,2,1,2,4,2,2,1,1,2,2,4,2,2,2,2,4,4,2,2,2,4,2,4,3,1,3,3,4,4,1,3,1,1,1,6,5,0,,,,,,,,,,,,,,,,,3,4,,6,7,8,,10,11,,,,1,,3,4,5,,,,9,2,2,,,,,2,14,,0,
-12760798270,1,2,2,1,2,4,2,1,4,2,2,4,1,2,2,2,3,3,3,1,2,3,3,4,1,5,5,5,4,4,3,4,3,4,4,2,4,1,1,1,5,5,,,2,3,4,5,6,7,8,,,11,,13,,,,3,4,5,6,7,,,,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,15,,17,
-12760796199,1,4,3,1,4,4,2,3,5,5,4,3,3,3,3,2,5,2,2,5,4,5,5,5,5,5,4,1,4,3,1,1,3,4,3,2,3,1,1,2,5,5,,,,3,,5,6,7,8,,10,,,,,,,3,,,6,7,,,,11,,,,,,3,4,5,,,,,2,2,,,,,2,6,,11,
-12760795769,1,3,2,1,3,4,2,1,4,5,3,3,2,2,4,3,4,4,3,4,5,3,5,5,3,4,4,5,4,4,2,1,4,0,4,3,2,2,3,2,6,4,0,,,,,,,,,,,,,,,,,3,,,,7,,9,,,,,,,,3,4,,,,,9,2,2,,,,,2,9,,5,
-12760795453,1,4,3,1,5,4,4,3,5,5,4,5,3,3,5,4,3,3,2,5,2,5,5,2,2,5,5,2,4,5,4,4,5,5,5,3,3,1,1,1,5,5,,,,,4,,,7,8,,10,11,,13,,,,3,4,,6,7,,,,11,,,,,,3,4,5,6,,,9,2,2,,,,,2,2,,2,
-12760794121,1,2,1,1,1,2,1,1,4,5,1,1,1,1,2,1,1,5,5,1,3,5,1,3,1,5,5,5,2,3,2,1,1,0,1,2,1,2,2,1,6,5,,,,,,5,,,8,,,,,13,,,,3,,5,6,,,,,,,,,1,2,3,,5,,,,9,1,1,,1,,3,2,14,,5,
-12760793749,1,4,3,1,5,4,1,4,5,5,2,2,1,2,4,2,5,2,1,2,4,2,5,2,1,5,5,2,5,4,1,3,4,4,5,1,1,1,1,1,5,5,,,,3,,,6,7,,9,,,,,,,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,12,,2,
-12760792871,1,4,3,1,4,3,1,1,4,4,2,2,1,2,4,4,5,5,1,1,5,5,5,5,2,3,5,5,2,4,1,1,2,2,3,1,1,1,2,3,6,5,0,,,,,,,,,,,,,,,,,,,5,,7,,,,,,,,,2,3,,,,,,,2,2,,,,,2,14,,2,
-12760791276,1,2,2,1,3,3,1,3,2,5,3,3,2,1,4,3,4,5,3,5,4,5,4,5,5,2,5,5,3,3,2,4,4,3,4,2,3,1,1,1,3,4,0,,,,,,,,,,,,,,,,,3,,,,,,9,10,,,,,,,3,,5,,,,,2,2,,,,,2,14,,2,
-12760791210,1,2,1,1,3,3,3,3,3,3,3,3,3,2,3,2,3,3,3,3,3,3,4,3,5,2,4,2,4,3,2,3,4,4,4,1,3,1,2,1,5,5,,1,2,3,4,5,6,7,8,9,10,11,12,13,,,2,3,4,5,6,7,,9,10,,,,,1,2,3,4,5,6,7,8,9,2,1,,,2,3,1,2,,9,
-12760788557,1,4,3,1,1,1,1,1,1,1,1,1,1,2,2,2,1,1,1,1,2,1,2,1,2,3,3,3,2,2,2,2,3,2,3,2,2,1,1,1,5,5,,,,,,,6,7,,,,,,,,,,,,5,,7,,,10,,,,,1,2,,4,5,6,,,9,2,2,,,,,2,14,,15,
-12760788335,1,4,3,1,2,2,4,1,2,4,1,1,1,2,4,3,2,3,4,4,3,3,3,1,2,5,5,4,3,4,2,3,3,3,3,2,3,1,3,2,3,3,,,,,,5,6,7,8,,,,,,,,,3,,5,6,7,,,,,,13,,,2,3,4,5,,,,9,2,1,,,,3,2,4,,11,
-12760788264,1,4,3,1,2,2,2,2,4,5,5,3,4,2,1,2,3,2,1,2,3,3,3,3,3,2,3,4,5,3,3,4,5,5,5,2,4,2,1,2,5,5,,1,2,3,,5,6,,8,9,10,,,,,1,,,,5,6,,,9,10,,,,,,,,4,,,,8,9,2,2,,,,,2,13,,11,
-12760787944,1,2,2,1,1,2,1,3,2,3,3,1,1,1,5,3,1,4,3,3,2,2,4,1,2,5,5,3,5,5,5,2,4,5,5,1,1,3,1,1,5,5,,1,,3,4,5,6,7,,9,,,,,,,2,3,4,5,6,7,,9,,11,12,13,,1,2,3,4,5,,7,,9,2,1,,1,,,2,1,,11,
-12760785373,1,3,1,1,5,5,5,2,5,5,3,4,1,4,5,5,5,5,5,2,5,5,5,5,2,5,5,5,5,5,3,3,4,4,4,4,3,1,1,5,2,3,,,,3,,,6,7,8,9,10,,,,,,,3,,,6,7,,9,10,,,,,,,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760784337,1,4,3,1,2,2,1,1,2,1,1,1,1,1,3,1,4,2,2,2,4,5,5,2,2,2,2,2,4,2,2,3,4,5,5,2,2,1,1,2,1,2,,,,,,,6,7,8,,,,,,,,,3,4,5,6,7,,9,,,,,,1,2,3,4,5,6,7,8,9,2,1,,,,3,2,2,,9,
-12760783742,1,3,3,1,5,4,1,2,5,5,4,4,2,3,5,1,5,4,1,5,5,5,5,5,5,5,5,4,5,3,2,3,5,5,4,3,4,1,1,1,5,5,,,,3,4,5,,7,,,,,,,,,,3,4,5,6,7,,,10,11,,13,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12760779849,1,4,3,1,2,3,2,1,4,2,3,1,3,1,2,2,4,4,4,4,4,4,4,4,5,2,4,4,3,4,1,1,5,4,,1,3,1,1,1,5,5,,,,3,4,,,7,8,9,,11,,,,,,3,,5,,7,,,10,11,,,,1,,3,,,6,,,9,2,2,,,,,1,14,,2,
-12760779205,1,4,3,1,4,4,2,2,4,5,2,4,2,4,4,2,4,4,4,4,5,5,5,5,5,5,5,5,3,3,1,1,4,3,2,2,1,1,2,1,5,5,,,,3,,5,6,,,,10,,,,,,2,,4,5,6,7,,,10,,,,,1,2,3,4,5,,,,,2,1,,,,3,2,14,,17,
-12760778995,1,4,3,2,2,3,2,2,4,2,3,2,1,1,2,2,1,3,2,1,2,3,2,2,1,1,3,2,3,3,2,2,3,3,3,3,2,1,1,3,5,5,,1,2,3,4,5,6,7,,,10,11,,,,,,3,4,5,6,7,,9,,,,,,1,2,3,4,5,6,,,9,2,1,,1,,,3,13,,1,
-12760778477,1,3,2,2,4,2,1,3,4,4,4,4,2,3,4,2,4,4,2,4,4,4,4,4,2,4,4,3,5,2,1,2,3,3,5,4,1,2,1,1,3,2,,,,3,,,,7,,,10,,,,,,2,3,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12760774698,1,2,1,3,2,3,2,2,2,4,2,2,1,1,1,1,3,3,2,4,3,0,5,4,1,0,1,1,3,2,3,,3,2,3,3,5,5,5,5,5,5,,1,,,4,5,6,7,,,,,,13,,,,,4,,6,7,8,,10,11,,,,1,2,3,4,5,6,,,9,2,2,,,,,3,14,,1,
-12760774307,1,3,2,2,2,1,1,1,5,5,1,3,1,1,4,4,2,4,1,4,2,4,4,4,3,3,5,4,2,2,2,2,2,3,4,3,1,1,1,1,5,5,,,,,4,,6,7,,,,,,,,,,,4,,6,7,,,,,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,2,,14,
-12760774003,1,2,1,1,3,2,2,2,4,4,4,2,2,1,2,2,5,4,5,3,5,5,5,2,5,1,4,4,2,2,4,2,4,2,4,2,2,1,1,1,2,1,,1,,3,4,5,,7,,9,,11,,,,,2,,4,5,6,7,,,,,,,,1,2,,4,,,,,,2,2,,,,,2,14,,2,
-12760773729,1,2,1,1,,4,1,2,2,4,2,1,1,1,3,1,,3,2,4,4,5,5,2,5,4,3,2,4,3,3,3,5,5,4,2,3,1,1,2,3,1,,,,,4,5,,7,8,9,10,11,,,,1,,3,,5,6,7,,,,,,13,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12760773711,1,3,2,2,5,5,5,5,3,5,5,3,4,1,2,3,5,5,5,5,3,5,5,3,5,1,1,3,0,0,0,0,3,0,0,3,0,1,1,3,6,3,0,,,,,,,,,,,,,,,1,,,4,,,7,,9,,,,,0,,,,,,,,,,2,2,,,,,1,4,,11,
-12760771373,1,4,3,1,3,3,2,5,3,5,4,5,4,2,4,3,4,4,3,5,4,5,4,5,5,1,4,3,3,3,2,0,3,0,0,4,3,2,2,2,6,5,0,,,,,,,,,,,,,,,,,,,,6,7,,9,,,,,,,,3,,,,,,9,2,2,,,,,2,5,,17,
-12760769924,1,3,2,1,4,2,2,2,4,4,2,2,2,1,2,4,4,2,4,4,5,4,4,2,2,2,4,4,5,4,5,5,5,5,5,2,3,2,1,1,4,2,,1,,3,,5,6,7,,,,,,,,,2,,,5,6,7,,,10,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,2,
-12760767783,1,4,2,1,5,3,3,3,5,5,5,5,3,1,3,3,5,5,5,5,5,5,5,5,5,1,5,5,4,3,4,4,4,4,4,2,4,1,1,1,2,5,,,2,,,5,6,7,8,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,14,,5,
-12760767757,1,2,3,1,4,5,2,1,5,5,5,4,1,1,2,1,5,5,4,5,5,5,5,5,5,2,2,1,3,4,2,4,5,5,5,4,4,1,1,1,2,1,,,2,,,5,6,,8,9,10,,,,,,,,,5,6,,8,9,10,,,,,1,,3,4,,,,,,2,2,,,,,2,2,,9,
-12760767230,1,3,2,2,3,3,1,3,3,4,2,4,1,2,3,3,4,3,1,4,4,4,4,3,1,5,5,4,3,3,2,2,4,3,3,2,1,2,1,2,4,3,,,,,,5,6,7,,9,10,,,13,,,,3,4,5,6,7,8,9,10,,,,,,2,3,4,5,,,,,2,1,,1,,,2,2,,11,
-12760766949,1,3,2,1,4,4,2,2,5,4,4,4,3,4,5,4,5,4,2,5,5,5,5,4,5,5,5,5,3,2,1,2,4,3,3,2,2,1,1,2,5,5,,,,,,,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,5,,1,
-12760766810,1,4,3,1,1,2,1,2,3,2,2,3,2,2,2,1,1,2,5,3,2,3,3,3,1,5,5,5,4,4,2,3,4,4,4,4,3,2,1,3,4,5,,,,3,,5,6,7,,,,11,,,,,2,3,,5,6,7,,,10,,,,,1,2,3,4,5,6,7,8,9,2,1,,,,3,2,13,,2,
-12760766680,1,3,2,1,2,1,2,3,3,3,2,2,3,2,3,2,3,1,2,4,3,3,2,2,4,3,4,2,4,3,4,4,3,4,4,2,4,2,2,2,5,5,,1,,,4,,6,7,,,10,,,,,1,,3,,5,6,7,,,10,,,13,,1,2,3,4,5,,,,9,2,1,,1,,3,2,3,,11,
-12760766548,1,3,2,1,2,2,1,2,4,5,2,2,,2,4,5,2,1,1,5,2,2,2,2,4,2,4,5,5,3,1,2,3,5,4,3,2,1,1,1,3,3,,,,3,,,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760765563,1,4,2,1,5,4,5,4,4,4,5,1,4,2,5,2,5,5,5,5,5,5,5,3,5,4,5,2,4,4,4,4,4,4,4,2,3,1,2,2,5,5,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,,,,3,,,,,,9,2,2,,,,,2,11,,17,
-12760765272,1,4,3,1,5,3,3,3,4,5,5,4,2,3,5,1,5,4,3,5,5,5,5,5,4,3,5,1,5,4,3,5,3,5,5,3,1,1,2,1,3,1,0,,,,,,,,,,,,,,,,,,4,,,7,,,,,,,,,2,3,,5,,,,9,2,1,,,,3,2,14,,17,
-12760765017,1,2,1,1,4,4,4,4,4,4,4,4,2,2,2,4,5,5,5,5,5,2,5,5,5,2,5,5,4,4,4,4,4,2,4,3,4,4,1,2,4,5,,1,,3,4,5,6,7,,9,,,,13,,,,3,,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760764898,1,3,2,1,2,1,4,2,2,5,4,4,1,5,5,5,5,0,5,5,5,5,5,5,1,5,5,5,5,5,3,4,5,5,5,1,1,1,1,1,6,2,0,,,,,,,,,,,,,,,,,,,5,6,,,9,,,,,,,,3,,5,,,,9,2,1,,,,3,2,14,,15,
-12760764496,1,3,2,1,3,1,1,3,3,3,3,3,1,1,3,2,5,5,5,5,3,5,5,5,5,1,5,5,4,5,3,1,2,0,2,2,2,1,1,3,5,5,,1,,3,,,6,7,,9,10,11,,,,1,,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,,,8,9,2,1,,,,3,2,3,,11,
-12760764098,1,4,3,1,5,5,5,4,5,5,5,5,5,2,5,5,5,5,5,5,5,5,5,5,5,4,5,5,2,2,2,3,3,3,3,1,3,1,1,2,2,2,,,2,,,5,6,7,,9,10,,,,,,2,3,,5,6,7,,9,10,,,13,,1,2,3,4,5,6,7,8,9,2,1,,,,3,2,7,,5,
-12760763807,1,2,2,1,2,3,3,1,,3,3,3,2,1,2,3,2,5,5,2,3,3,5,5,5,2,5,5,3,2,2,2,4,3,4,3,2,1,1,2,5,5,,,,,,5,6,7,8,9,,,,,,,,,,5,6,7,,9,,,,,,,2,3,4,5,,,,9,2,2,,,,,1,14,,1,
-12760763693,1,2,1,1,4,4,2,1,5,5,2,2,1,1,3,2,4,3,2,4,5,5,5,5,4,3,5,3,0,0,2,4,0,0,5,3,1,1,1,1,3,5,,,,3,,,6,,,,10,,,,,,,,,5,,7,,,,,,,,,,3,4,5,,,,,2,1,,1,,,1,14,,17,
-12760763417,1,4,3,1,4,4,3,2,3,5,2,3,2,1,4,2,5,5,4,4,5,5,5,4,4,1,2,3,5,5,3,3,5,0,0,3,3,1,1,3,6,3,,,,3,,,6,7,,9,,11,,,,1,,3,4,5,6,7,,,10,11,,13,,,,3,4,5,6,,,9,2,1,,,,3,2,4,,11,
-12760762839,1,4,3,2,2,2,2,4,2,4,2,2,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,5,5,5,5,5,5,5,5,5,5,5,5,1,5,,,,,,,,,,9,,,,,,,,,,,,7,,,,,,,,1,,,4,,,,,,2,1,,1,,,1,7,,5,
-12760762220,1,2,2,1,4,4,4,3,4,2,1,2,1,1,1,2,5,5,5,5,5,5,5,5,2,1,5,5,4,2,2,4,4,2,3,3,1,1,1,1,5,5,,1,,,4,,6,7,,,,,,13,,,,3,4,5,6,,,9,10,11,12,13,,1,,3,,,,7,8,,2,1,,1,,,2,3,,11,
-12760761294,1,3,3,1,3,5,2,5,5,4,3,4,5,1,5,4,5,5,2,5,5,2,5,5,5,5,5,5,4,3,1,4,4,2,3,2,2,1,1,2,5,5,,,2,,,5,6,7,,,,11,,13,,,2,3,,5,6,7,,,10,11,,,,1,2,3,4,5,6,,,9,2,1,,1,,3,2,14,,5,
-12760761244,1,3,2,1,2,2,1,4,4,3,2,4,2,2,2,1,3,2,1,4,4,4,2,4,2,2,2,1,3,2,2,1,3,3,3,3,1,1,2,2,5,5,0,,,,,,,,,,,,,,,,,,,5,,,,9,10,,,,,,,,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760759815,1,4,3,1,2,2,4,1,2,2,2,2,1,5,4,4,2,4,4,1,4,4,4,2,1,5,5,5,3,2,2,1,3,3,3,2,1,3,1,1,4,5,,,,,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,1,,,,3,1,17,,8,
-12760758930,1,2,1,1,3,3,2,2,4,5,3,4,1,1,1,1,3,4,4,4,5,5,4,4,5,1,3,4,5,3,3,4,5,5,5,2,3,1,1,1,1,1,,,,,,5,6,7,,,10,,,,,,,,,5,6,7,,,10,,,,,,2,3,4,5,,,,,2,2,,,,,1,14,,2,
-12760755467,1,3,2,1,3,4,3,5,3,3,1,5,5,1,2,3,0,1,1,4,5,4,1,5,4,2,4,2,5,5,3,5,5,5,3,1,3,1,1,1,3,3,,1,,3,4,,6,7,,,,,,,,,,3,4,,6,7,,,,11,,,,,,3,4,5,6,,,,2,1,,,,3,1,5,,1,
-12760755326,1,2,1,1,2,4,5,2,4,5,1,4,1,1,1,4,5,4,5,5,5,3,4,5,3,4,1,5,3,3,2,3,3,4,4,1,2,1,1,2,6,4,0,,,,,,,,,,,,,,,,,,,,,7,,9,10,,,,,1,2,,,5,,,,9,2,1,,,,3,3,14,,2,
-12760755053,1,4,3,1,2,4,2,2,2,4,4,3,2,2,3,4,4,4,4,1,2,4,5,2,5,2,4,5,3,3,2,2,2,4,4,2,3,1,3,1,2,2,,1,,3,,5,6,,,9,10,11,,,,,,,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,1,
-12760754891,1,3,2,1,1,3,2,1,2,2,2,1,1,1,1,5,4,4,4,4,3,4,4,4,4,1,2,5,5,3,3,5,5,5,5,5,4,1,1,3,5,3,,,2,,,5,6,7,,9,10,,,,0,,,,,,,,,,,,,,,1,2,3,4,5,6,7,8,9,2,2,,,,,1,14,,1,
-12760753874,1,4,3,1,3,3,2,2,3,3,2,2,2,1,1,2,3,3,4,5,4,3,4,4,3,2,1,4,3,3,2,3,3,5,3,3,4,1,1,1,3,3,,,,,4,,,7,,,10,,,,,,,3,,,6,7,,,,11,,,,,,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760752691,1,4,3,1,2,4,2,2,2,3,2,3,2,1,2,2,4,4,4,4,5,5,5,5,5,2,4,4,3,2,2,2,3,3,2,1,2,1,1,1,3,3,,,,,,5,6,7,,,,11,,13,,,,3,,5,6,7,,,,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,13,,11,
-12760752571,1,4,3,1,2,1,1,2,2,2,1,4,1,1,2,2,5,4,3,5,5,5,5,5,5,5,5,5,5,3,2,4,5,5,5,5,3,2,1,2,3,3,,,,3,,,6,7,,,,11,,,,,,3,,,6,7,,,,,,,,,,3,4,5,6,,,9,2,1,,,,3,2,7,,5,
-12760752217,1,4,3,1,3,3,2,2,4,4,4,4,3,2,2,4,5,5,4,5,5,5,5,5,5,2,4,5,3,4,2,3,4,4,4,2,3,1,1,1,3,2,,1,2,3,4,5,6,7,8,9,10,11,,13,,,2,3,4,5,6,7,8,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12760752207,1,4,3,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,2,5,,,,,,,6,7,,9,,11,,,,,,,,5,,7,,9,,11,,,,,,,4,,,,8,9,2,1,,1,,,1,9,,5,
-12760752192,1,3,2,1,4,4,4,4,3,3,3,3,3,3,4,2,3,1,1,1,1,0,5,5,3,5,4,2,4,2,2,2,2,0,3,3,3,0,2,1,5,3,,,,,,5,,,,9,,,,,,1,,3,,,6,,,9,,,,,,1,,,4,5,,,,9,1,1,,1,,,2,3,,11,
-12760751549,1,4,3,1,4,4,4,4,3,4,4,4,2,2,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,3,2,5,3,5,5,3,3,2,2,1,3,5,,,,3,4,,6,7,,9,10,,,,,,,,4,,6,7,,9,10,,,,,,,3,4,,,,,,2,2,,,,,2,14,,17,
-12760751266,1,2,1,2,2,4,4,3,2,5,1,4,3,1,1,4,2,4,5,3,4,5,3,2,5,1,1,5,4,3,2,3,3,3,5,4,2,1,1,1,1,3,,,,,,,,7,,9,10,,,,,,,,,5,6,7,,9,,,,,,,,3,4,5,,,,,2,1,,,,3,1,14,,5,
-12760750730,1,2,1,1,2,1,1,3,3,5,3,2,2,1,1,4,3,2,2,5,3,4,5,5,3,3,2,5,5,3,2,5,3,4,3,2,2,1,1,1,5,5,,,,,,5,6,7,,9,,,,,,,,3,,5,6,7,,9,,,,13,,,2,,4,5,,,8,9,2,1,,,,3,2,1,,11,
-12760750657,1,4,2,1,3,2,1,1,3,5,4,2,3,2,3,2,5,4,2,2,5,5,5,2,5,5,5,5,4,2,1,3,3,4,3,2,4,1,1,1,2,1,,,2,3,4,5,6,7,8,9,10,11,,13,,1,2,,4,5,6,7,,,10,11,,13,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,2,
-12760748344,1,4,3,1,3,1,1,1,3,3,3,1,1,1,1,1,5,5,1,5,3,3,5,3,5,1,4,1,2,1,1,1,4,3,3,3,2,1,1,1,5,3,,1,2,3,4,,,7,,9,,,,,,,2,,,5,,7,,9,,,,,,,,3,4,5,,,,,2,1,,,,3,2,6,,15,
-12760748307,1,2,1,3,2,1,2,2,3,4,3,4,1,2,3,4,3,1,3,3,4,4,4,4,4,5,5,4,2,2,2,2,3,4,4,3,1,2,4,3,6,3,,1,,3,,,,7,,,,,,,,1,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,17,
-12760747815,1,4,3,1,1,2,2,1,2,1,1,1,1,1,2,2,1,5,4,1,4,1,2,1,3,4,5,5,3,5,4,2,3,5,4,3,4,1,1,4,4,5,,,2,,4,5,6,7,,9,10,,,,,,2,3,4,5,6,7,,9,10,11,,13,,1,2,3,4,5,6,7,8,9,2,2,,,,,2,14,,5,
-12760746636,1,3,2,2,2,4,1,1,2,1,2,1,3,1,3,1,5,5,5,5,3,5,5,5,5,5,3,5,4,2,1,2,4,1,2,3,2,1,1,1,3,3,,,,3,,5,6,7,,9,10,,,,,,,,4,5,,7,,9,10,11,,,,1,2,3,4,5,6,7,,9,2,1,,,,3,3,14,,5,
-12760746562,1,4,3,1,5,5,5,5,4,5,4,5,3,1,2,4,4,4,4,5,4,5,4,5,4,1,2,5,4,3,3,5,3,4,5,3,5,1,1,3,3,2,,1,,3,4,5,6,7,,,,11,,,,1,,3,4,5,6,7,,,10,,,,,,2,3,4,5,6,,,,2,1,,,,3,2,14,,5,
-12760745742,1,4,1,1,3,4,3,2,4,4,2,2,1,5,5,4,3,5,5,2,4,5,3,2,1,5,5,5,4,3,3,1,4,3,3,1,3,3,1,2,5,5,,1,2,3,4,,6,,8,9,10,11,12,13,,,,3,4,,,7,,9,10,,,13,,1,,3,,5,6,7,8,9,1,1,,1,,,1,14,,2,
-12760745355,1,4,3,1,3,2,1,2,2,4,2,2,2,1,3,2,5,3,2,5,5,5,5,5,5,3,5,5,3,3,1,2,0,3,3,2,4,3,2,2,6,5,,,2,,,,6,,8,9,,,12,,,,,,,,6,7,,,,,,,,,2,3,,5,,,,,2,2,,,,,2,14,,2,
-12760744688,1,3,1,1,1,2,3,3,2,4,1,4,2,2,4,3,2,4,4,4,3,4,2,4,4,4,4,3,4,3,2,3,3,3,4,3,4,1,2,2,2,4,,,,,4,,6,,,,10,11,,,,,,,,5,6,,,,,,,,,,,3,4,5,,,,,1,1,,,,3,2,17,,17,
-12760743999,1,4,3,1,5,3,3,3,5,5,2,4,2,2,5,2,5,2,2,5,5,5,5,5,5,5,5,5,5,3,1,4,4,5,5,3,2,1,1,2,5,5,,,2,,,5,6,7,8,9,,,,,,,2,,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,0,Mauritian ,9,
-12760742383,1,4,3,1,5,4,5,1,5,2,5,5,2,1,2,2,5,5,5,2,5,2,5,5,5,2,5,5,3,3,4,1,5,2,2,2,4,1,1,1,1,5,,1,2,,4,5,6,7,8,9,10,11,,13,,,,3,4,5,6,7,,,,11,,,,1,2,3,4,5,,,8,9,2,2,,,,,2,14,,5,
-12760740407,1,4,3,1,5,4,3,3,5,5,5,4,2,2,5,2,4,3,3,3,4,5,5,3,3,2,4,2,3,4,3,2,3,4,3,2,2,1,3,1,5,5,,1,2,3,,5,6,7,8,9,10,,,13,,1,,3,4,5,6,7,8,9,10,11,,13,,1,2,3,4,5,,,,9,2,2,,,,,2,2,,14,
-12760739596,1,4,3,1,4,1,2,2,2,4,2,3,2,1,4,4,4,2,4,2,4,4,4,5,2,2,4,5,4,3,2,3,2,3,3,2,4,1,1,1,4,2,,,,3,,,6,7,,9,,,,,,,,3,,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,1,
-12760737989,1,4,3,1,3,4,2,2,2,5,2,2,3,2,1,1,5,5,4,5,5,3,5,5,5,2,1,3,4,4,2,5,3,0,4,2,3,1,1,1,6,1,0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,2,3,,,,,,,2,1,,,,3,1,14,,17,
-12760737368,1,3,2,1,1,5,4,1,1,1,1,4,1,5,5,5,2,5,5,2,2,2,2,5,1,5,5,5,2,3,3,3,2,2,2,3,2,2,2,1,5,5,,1,,,,5,6,7,,,,,,,,,,,,,6,7,,,,,,,,,2,3,4,5,,,,9,1,1,,1,,,2,14,,2,
-12760736555,1,3,2,1,3,3,3,3,3,3,3,3,4,1,3,4,3,3,3,3,3,3,3,3,3,1,3,3,4,5,3,5,5,5,5,1,3,1,2,3,5,5,,,,3,,5,6,7,,,,,,,,1,,,,5,,7,,,10,,,,,,,,,,,7,,,2,1,,,,3,2,2,,11,
-12760735372,1,4,3,1,5,2,1,2,4,3,4,4,2,3,3,3,2,1,1,4,2,2,4,5,1,5,5,4,4,2,2,3,4,3,4,2,3,3,3,2,3,1,,1,,,4,5,6,7,8,,10,11,,13,,,,3,,5,6,7,,,,,12,,,,,3,4,,6,,8,9,2,2,,,,,2,14,,17,
-12760735328,1,2,1,1,2,2,1,1,2,3,1,2,1,1,2,2,2,3,1,2,2,4,5,4,2,2,4,4,5,4,2,2,4,4,3,2,2,1,1,1,5,5,,,,3,4,5,6,7,,9,,11,,13,,,2,3,4,5,6,7,,9,,11,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,2,,2,
-12760734416,1,4,3,1,3,2,2,2,4,4,1,2,1,1,4,2,4,3,4,3,5,4,3,3,2,3,,5,4,3,2,3,5,4,3,3,3,2,3,3,3,3,,,,,,,6,7,,,,,,,,,,,,,,7,,,,,,13,,,2,3,4,5,,,,9,2,1,,1,,,2,7,,,
-12760734140,1,3,2,1,5,5,2,3,2,5,2,4,2,3,5,5,5,5,4,5,4,5,5,5,5,5,5,5,3,3,2,4,1,3,4,4,1,1,1,1,5,5,,1,,3,4,,6,7,,,10,11,,,,1,,3,4,5,6,7,,,10,,,,,,2,3,4,5,6,,,9,2,1,,1,,,2,14,,5,
-12760733433,1,4,3,1,3,3,3,3,3,3,3,3,2,1,3,4,3,3,3,3,3,3,3,3,4,1,2,3,3,3,3,3,3,3,3,3,3,1,2,3,4,4,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,13,,,,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760733430,1,4,3,1,5,4,4,1,5,5,5,5,2,2,4,1,4,2,2,5,4,5,5,4,1,5,5,1,5,5,2,4,4,5,5,3,3,1,1,1,3,5,,,,,,5,,,,,,,,,,,,,4,5,6,7,,,,,,13,,1,2,3,4,5,6,,,,2,2,,,,,1,14,,1,
-12760732946,1,3,2,2,3,3,4,3,2,3,2,4,3,2,4,5,5,5,5,5,5,5,5,5,5,4,5,5,5,3,3,3,5,4,5,3,4,2,1,3,3,2,,,,,,5,6,7,,,10,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,5,
-12760732640,1,3,3,1,4,2,2,2,4,4,4,2,2,2,3,1,4,4,2,2,4,4,4,4,4,4,4,1,5,5,3,5,5,5,5,1,3,5,1,1,3,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,9,10,,,,,,,3,,5,,,,,2,1,,,,3,2,2,,11,
-12760732243,1,2,1,2,2,1,2,2,4,4,4,1,2,1,1,5,2,1,1,2,3,5,5,1,2,4,5,5,4,3,3,4,4,5,4,3,4,2,1,1,5,5,,1,2,3,4,5,6,7,8,9,10,,,,,,2,3,4,5,6,7,8,,10,11,,13,,1,2,3,,5,6,,8,9,2,2,,,,,2,14,,17,
-12760731854,1,3,2,1,3,3,2,2,3,3,2,4,3,3,2,3,3,5,3,3,4,4,4,4,3,5,5,5,4,4,3,3,3,4,5,3,3,2,1,3,5,5,,1,,3,4,5,6,7,,,,11,,13,,1,,3,4,5,6,7,,,,11,,13,,1,2,3,4,5,6,7,,9,2,2,,,,,2,3,,11,
-12760730318,1,2,1,1,2,2,2,2,2,2,2,2,2,2,2,2,4,4,4,2,4,4,5,2,4,4,5,4,4,4,4,4,4,4,4,3,4,4,2,3,5,5,,,,3,,,6,7,8,9,10,,,,,,,3,,5,6,7,8,9,,,,,,,2,3,4,5,,,,,2,2,,,,,2,14,,2,
-12760730210,1,3,3,1,5,4,4,4,5,5,4,3,3,1,1,2,5,5,5,5,5,5,5,5,5,1,2,5,3,3,3,3,3,4,4,1,3,1,1,1,3,5,,1,,,,,,7,8,,,,,,,,,3,,5,,7,,,10,,,,,,,3,,,6,7,,9,2,2,,,,,2,14,,17,
-12760729483,1,4,3,2,4,2,1,2,5,,5,4,2,2,4,4,2,2,1,4,2,4,5,4,4,5,2,4,4,1,1,5,2,4,4,2,2,1,1,1,5,5,,,,,,,,,,,,,,,,,,3,4,5,6,7,,9,10,11,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,8,
-12760729452,1,3,3,1,3,2,3,2,3,3,3,3,2,2,2,2,4,1,2,1,2,4,4,4,2,4,4,2,3,2,1,2,3,4,4,3,1,1,2,1,3,5,,,2,,,,6,7,,,10,,,13,,1,,,,,6,7,,,,,,,,,,3,4,,,,,9,2,2,,,,,2,14,,2,
-12760728874,1,4,3,1,2,2,1,1,2,3,1,2,1,1,1,2,5,4,2,5,5,5,5,5,4,4,4,4,4,4,1,3,5,5,5,3,3,2,1,1,3,1,,,,,4,,6,7,,,,,12,,,,,,,,6,7,,,,11,,,,,,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760728500,1,4,3,2,3,2,2,2,3,4,2,2,2,2,2,1,4,2,2,5,4,4,5,5,2,5,5,2,4,3,2,3,4,4,4,3,2,2,1,2,4,4,,1,,,,,6,,,,,,,,,,,3,,,6,7,,,,,,,,1,,3,,5,,,8,,2,2,,,,,2,14,,17,
-12760727718,1,4,3,1,1,2,1,1,2,1,1,2,1,1,1,2,1,2,2,2,2,3,4,2,2,4,2,5,4,5,2,5,3,5,5,5,2,1,1,4,5,5,,,,,,5,6,7,,9,10,11,,,,,,,,5,6,7,,9,,,,,,1,2,3,4,,6,,,9,2,1,,1,,,1,7,,5,
-12760726385,1,3,2,1,4,4,2,2,4,4,5,4,4,1,5,5,4,4,2,4,4,5,5,4,4,2,5,4,4,4,2,3,5,5,4,2,3,1,1,1,5,5,,,,,,,,7,,,10,,,,,,,3,4,5,,,,,10,,,,,1,2,3,4,,,,,9,2,2,,,,,1,14,,2,
-12760724149,1,3,3,1,5,3,2,2,4,5,1,4,5,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,2,1,1,4,4,3,2,3,1,1,1,5,5,,,,,,,6,7,,,10,,,,,,,,,,6,7,,,10,,,,,,2,3,4,5,,,,9,2,1,,1,,,1,14,,12,
-12760722576,1,4,2,1,3,2,1,3,3,3,2,3,3,5,4,1,5,2,1,5,3,3,4,2,5,5,3,1,3,3,3,3,3,3,3,3,3,3,1,3,3,1,,,,3,,,6,,,9,,,,,,,,,,5,,7,,,,,,,,1,,,4,,,,,9,2,2,,,,,1,4,,11,
-12760721882,1,4,3,1,3,1,1,5,2,3,3,4,2,1,5,3,5,2,2,5,5,5,5,5,5,3,5,5,2,1,1,2,2,4,4,2,1,1,1,1,1,3,,,,,,,6,,,,,,,,,,,,4,,6,7,,,,,,,,1,2,3,4,5,,,,9,2,1,,,,3,2,9,,5,
-12760721843,1,2,1,1,4,5,2,4,4,5,2,4,4,2,2,2,5,5,5,5,5,5,5,5,5,2,5,5,4,4,2,4,5,5,5,4,5,1,1,2,3,5,,1,,,4,5,6,,,9,10,,,,,,2,,,5,,,,9,10,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,5,
-12760721703,1,4,3,1,2,3,1,1,2,2,2,2,1,1,4,2,2,4,5,2,2,2,2,1,4,4,4,4,3,4,3,4,0,3,3,3,2,1,1,3,5,5,,,,3,4,5,6,7,,,,11,,13,,,,3,,5,6,7,,,,11,,,,1,2,3,4,5,6,,,9,2,1,,1,,3,2,7,,5,
-12760721537,1,4,3,1,2,3,2,1,2,2,2,3,2,2,3,4,5,5,5,5,5,5,5,5,5,2,5,5,4,2,3,1,4,4,2,2,5,1,1,2,5,5,,,2,,4,,6,7,,9,10,,12,,,,2,3,4,5,,7,8,9,10,,12,,,1,,3,4,5,,,,9,2,1,,,,3,2,14,,0,Similar values to Christians but I don’t believe in the religion. God could be real 
-12760721173,1,4,3,1,2,3,1,1,2,3,1,2,3,3,4,4,4,3,2,1,3,3,3,3,4,5,5,4,4,3,3,1,4,4,3,2,3,3,2,2,5,5,,,,,,,6,7,,9,10,,,,,,,,,5,6,7,,9,,,,,,1,2,3,4,5,,,,9,1,1,,1,,,2,14,,5,
-12760720194,1,3,3,1,3,3,2,2,3,4,2,3,4,1,4,3,4,3,4,2,5,4,5,5,5,3,5,5,5,5,3,3,5,5,4,5,5,1,1,4,5,5,,1,,3,,5,6,7,,,,,,,,,,,4,5,6,7,,,,,,13,,1,,3,4,5,,,,9,2,1,,,,3,2,3,,11,
-12760718708,1,4,3,1,4,1,1,1,1,4,1,2,1,1,2,2,5,2,2,3,3,5,4,4,4,5,5,5,4,4,3,4,4,4,4,2,3,1,3,2,3,3,,,,3,4,5,6,,,,10,,,,,,,,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,2,
-12760717329,1,4,3,1,2,2,2,2,2,4,2,2,1,3,3,2,4,3,4,4,4,4,5,2,2,5,5,4,4,3,2,4,4,4,4,3,3,1,1,1,5,5,,,,,,5,6,7,,9,,,,,,,2,3,,5,6,7,,9,10,11,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,15,
-12760717236,1,4,2,2,2,2,2,2,3,3,2,2,2,2,2,2,4,4,4,4,4,4,4,4,4,3,4,4,5,4,4,3,5,5,5,4,4,1,1,3,4,2,,,,,,,,,,9,,,,,,,,,,5,6,,,,,,,,,,,3,,,6,,,9,2,2,,,,,1,13,,0,
-12760716867,1,3,3,1,2,4,5,3,2,1,2,2,2,1,4,2,2,2,3,1,1,2,1,1,1,1,2,2,2,2,1,3,1,3,3,1,3,1,1,1,1,1,,,,,,5,6,7,8,,,11,12,13,,,,,,5,6,7,,,,11,12,13,,1,2,3,4,,6,7,,9,2,1,,1,2,3,4,0,,0,
-12760716671,1,4,3,1,1,2,1,2,1,2,1,4,2,4,5,2,4,4,1,4,4,4,4,4,4,5,5,2,4,4,1,4,4,4,4,4,2,1,2,1,5,5,,1,,3,4,5,6,,8,,,11,,,,1,,3,4,5,6,7,,,,,12,,,1,2,3,4,5,6,,,9,1,1,,1,,,2,2,,11,
-12760716521,1,4,3,1,4,2,5,1,1,4,1,2,2,1,4,4,1,2,5,2,1,5,5,4,4,5,5,5,5,4,3,4,5,4,4,3,4,1,1,1,2,3,,,,,,5,,,8,9,10,,,,,,,3,4,5,,7,,,,,,,,1,,3,,5,6,,,9,1,1,,,,3,2,15,,5,
-12760715861,1,3,2,1,4,1,1,2,5,5,2,2,2,1,3,4,3,1,1,5,3,3,2,3,4,5,5,3,3,2,1,3,3,4,4,2,2,2,1,1,3,2,,,,,4,5,,,8,9,,,,,,,,,4,,,7,,9,10,11,,,,,2,3,4,5,6,,,9,2,1,,,,3,2,14,,5,
-12760715384,1,3,2,1,5,2,2,2,2,5,2,3,2,2,2,3,5,3,2,2,5,5,3,5,3,5,5,5,4,5,4,3,4,4,4,3,2,1,1,3,2,1,,,2,,,,,,,9,10,,,,,,,,,5,,,8,9,10,,,,,1,2,,,,,,,,2,1,,,,3,2,3,,11,
-12760714772,1,3,2,2,3,2,2,2,3,3,3,2,2,1,3,1,5,4,5,4,4,5,5,4,5,2,5,1,3,2,2,2,4,4,4,3,2,1,1,2,5,5,,1,,3,4,5,6,7,,9,,,,,,1,,3,,5,6,7,,9,,,,,,1,,3,4,5,,,,9,2,1,,1,,,2,7,,5,
-12760714763,1,4,3,1,2,4,4,4,4,5,4,4,2,2,3,2,5,5,5,5,5,5,5,5,5,5,5,4,5,3,3,5,4,5,5,1,2,2,2,1,3,2,,,,3,4,5,6,7,,,,11,,,,,,,4,5,6,7,,,10,11,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,0,
-12760714683,1,2,1,1,4,2,2,4,3,4,4,3,3,1,4,2,4,3,2,4,3,4,4,3,5,1,4,3,4,3,2,3,3,5,4,3,3,1,1,2,5,5,,,,,,5,6,7,,,10,,,,,,,,,5,6,7,,,10,,,,,1,2,,4,5,,,,,2,2,,,,,2,10,,17,
-12760713472,1,2,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,1,1,1,1,1,1,3,1,1,1,5,5,,,,,,,6,7,,9,10,,,,,,,3,,,6,7,,9,10,,,,,,,3,,5,,,,9,1,1,,1,,,2,2,,14,
-12760713347,1,2,1,1,2,2,3,3,3,2,2,4,2,1,4,2,5,5,5,5,5,5,5,5,5,4,5,4,3,5,2,3,4,3,4,2,3,1,1,2,5,5,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,7,,5,
-12760710298,1,3,2,1,2,4,1,1,1,4,4,4,1,4,5,1,2,5,4,1,3,5,5,5,2,5,5,3,5,5,1,3,5,5,5,1,3,2,1,1,4,2,,1,,3,,5,6,7,,,10,,,13,,1,,3,,5,6,,,9,10,,,,,,2,3,4,,,,,9,2,2,,,,,2,17,,5,
-12760709208,1,4,3,2,5,4,4,2,5,5,2,2,2,1,2,1,5,5,5,5,5,5,5,5,5,3,4,2,0,0,0,0,0,0,0,0,0,2,2,3,6,5,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,1,,,,3,1,3,,11,
-12760709188,1,3,1,1,2,4,1,2,2,5,2,2,2,2,4,1,3,3,1,3,3,5,3,3,5,5,5,3,3,2,2,1,2,2,2,2,1,1,1,2,5,5,,,,,,,6,7,,9,,,,,,,,3,4,5,6,7,,9,,11,12,,,1,,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760708884,1,2,1,1,4,2,3,2,3,5,1,3,1,1,5,3,5,2,2,5,5,5,5,5,2,2,5,2,3,3,4,4,3,0,5,3,2,1,1,2,6,5,0,,,,,,,,,,,,,,,,,,4,5,,7,,,,,,,0,,,,,,,,,,2,2,,,,,2,14,,17,
-12760708626,1,3,2,2,4,4,4,4,4,4,2,2,3,2,2,2,5,5,5,5,5,5,5,5,4,2,2,1,4,3,3,4,3,5,5,2,3,1,1,1,3,3,,,,,,,6,,8,9,,,,,,,,,,5,,,,9,,,,,,1,,,,,6,,,,2,1,,,,3,2,6,,11,
-12760708427,1,2,1,2,,1,1,2,5,4,5,3,2,1,5,2,5,4,2,3,5,5,5,5,5,5,5,5,3,5,3,3,0,3,,1,3,2,3,1,4,3,,,,,,,6,7,,9,,11,,,,,,3,,,6,7,,9,,,,,,,2,3,4,5,6,,,,2,2,,,,,2,0,,0,
-12760707273,1,3,2,1,4,3,4,1,5,5,2,3,5,3,2,3,5,2,2,1,5,5,5,5,5,5,1,2,4,2,2,4,3,3,3,4,4,2,2,2,2,2,,,,3,,,6,7,,9,10,,,13,,,2,3,,,6,7,8,9,10,,,,,1,2,3,4,5,6,7,,9,2,1,,1,,3,1,2,,1,
-12760704101,1,3,2,1,5,4,3,2,4,5,2,5,1,2,4,5,3,4,2,5,3,2,3,3,2,4,3,3,4,3,3,4,4,5,4,4,4,2,1,5,4,5,,1,,,,5,,,,,,,,13,,,,3,,5,,7,,,,,,,,,,,4,5,,,,,2,2,,,,,2,14,,5,
-12760703269,1,4,3,1,2,1,2,2,5,4,2,5,2,2,2,3,2,1,1,2,2,3,4,4,1,5,4,4,4,2,2,3,3,3,3,4,2,1,2,4,5,5,,,2,3,,5,6,7,,,10,11,,,,,,,,5,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,1,14,,2,
-12760703264,1,4,3,1,2,3,1,2,2,4,2,1,2,2,3,2,5,5,2,5,5,5,5,5,4,5,5,4,4,4,2,3,4,4,4,4,3,4,1,2,5,5,,,,3,,,6,7,,9,,,,,,1,,3,,,6,7,,9,10,,,,,,,3,4,5,,,,9,2,2,,,,,2,17,,15,
-12760702578,1,2,1,1,5,5,,2,5,4,2,4,2,2,3,2,5,5,2,5,5,5,5,5,5,5,5,2,5,5,5,5,5,5,5,5,3,3,2,5,3,3,,,,,,,,7,,,,,,,,,,,,5,,,,,,,,,,,,3,,,,,,,2,1,,,,3,2,17,,5,
-12760702239,1,3,2,1,2,4,1,1,2,4,2,2,1,1,2,1,2,2,1,2,1,4,4,4,2,5,5,5,3,2,2,2,4,2,3,2,1,1,2,1,5,5,,,,,,5,6,7,,9,,,,,,,,3,4,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,14,,15,
-12760700853,1,3,2,1,2,5,5,2,2,2,2,4,2,2,3,3,4,4,3,5,3,3,3,5,5,4,4,2,4,4,3,5,5,3,3,4,4,2,1,1,5,4,,,,3,,,6,7,,9,,,,,,,,3,,5,6,7,,9,,11,,,,1,2,3,4,5,,,,,2,1,,1,,,1,4,,11,
-12760700632,1,2,1,1,3,4,3,2,3,5,2,3,1,1,3,3,2,2,2,2,2,2,5,4,4,5,5,4,4,2,1,3,4,3,3,3,2,1,1,1,4,5,,,2,,,5,6,7,,9,10,,,,,1,,3,4,5,6,7,,,,11,,,,1,2,3,4,5,6,,8,,2,2,,,,,2,2,,14,
-12760700064,1,3,2,1,3,3,3,2,4,4,2,2,2,2,3,2,5,5,5,5,5,5,5,3,5,3,5,3,4,3,3,3,4,4,4,2,2,2,1,1,5,5,,1,,3,,,6,7,,9,10,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,9,2,1,,,,3,2,14,,1,
-12760700010,1,4,3,2,3,2,2,2,2,5,2,3,2,2,4,2,4,2,2,2,4,5,2,5,1,2,5,5,3,3,2,3,3,0,4,3,1,1,1,1,5,5,,,,,4,5,6,7,8,,,11,,13,,,,,4,5,6,,,,10,11,12,,,1,,3,,5,6,7,,,2,1,,1,,,2,14,,17,
-12760698899,1,4,3,1,2,3,1,1,3,2,1,2,1,1,3,2,3,4,1,4,4,3,3,5,2,5,5,3,3,2,1,2,3,3,3,2,1,1,1,2,4,5,,,,,4,5,6,7,,,,,,,,,,,4,,6,7,,,,,,,,1,,3,4,5,,,,9,2,1,,,,3,2,7,,5,
-12760698808,1,4,3,1,2,4,4,1,2,2,1,3,1,5,4,4,1,2,1,1,1,1,1,2,1,5,4,4,5,5,2,5,5,4,4,2,3,2,1,2,5,5,,,,,,5,,7,,9,10,,,,,,,,,5,6,7,,9,,11,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,2,3,,11,
-12760698410,1,2,1,1,1,4,4,2,1,1,1,3,2,1,3,4,2,4,4,1,3,2,2,4,3,1,5,4,2,3,3,2,2,3,1,1,1,1,1,1,3,5,,,,,,5,6,7,,,10,,,,,,,,,,6,7,,9,10,,,,,1,,3,4,5,6,,,9,1,2,,,,,2,14,,15,
-12760697712,1,4,3,1,4,4,2,2,4,4,3,3,2,1,3,5,4,5,4,5,5,5,5,3,5,2,5,5,3,3,1,3,0,2,3,3,1,3,1,2,6,5,,,,,,5,6,7,,,10,,,,,,,,,,6,7,,,10,,,,,,2,3,4,5,6,,,,2,1,,1,,3,2,14,,5,
-12760697667,1,3,2,3,2,1,2,4,2,4,2,4,2,2,1,2,4,2,3,5,3,4,3,5,3,4,1,4,3,2,1,4,3,3,4,3,1,1,1,1,4,5,,,,3,,5,6,7,,,,,,,,,,3,,5,6,7,,,,11,,,,,,3,4,5,,,,9,2,1,,1,2,3,2,2,,14,
-12760696712,1,4,3,1,3,1,3,3,2,3,2,1,2,1,3,3,3,2,4,4,3,4,4,4,4,4,4,4,3,2,3,2,3,3,3,2,1,1,1,1,3,2,,1,,,,,,,,,,11,,,,,,,,,,,,9,,,,,,,,,4,,,,,9,2,2,,,,,2,14,,2,
-12760696706,1,3,2,1,2,2,2,1,3,2,2,2,1,1,3,3,3,2,4,2,3,4,5,1,2,5,5,5,4,2,1,1,3,3,4,1,2,2,1,1,5,5,,,,,,,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,1,2,3,4,5,,,,,2,2,,,,,2,14,,15,
-12760695482,1,2,1,3,3,4,4,4,4,5,4,4,4,3,2,5,3,2,3,3,5,4,4,5,5,3,2,5,4,3,2,3,4,5,4,3,3,1,1,2,5,5,,1,,3,,,6,7,,9,10,11,,13,,1,,3,4,5,6,7,8,9,,11,,,,,,3,4,5,6,,,,2,1,,,,3,2,7,,11,
-12760694800,1,2,1,2,2,2,4,3,2,4,4,1,0,1,3,4,2,5,2,4,2,2,2,1,2,4,1,1,4,3,3,2,2,1,5,2,3,2,2,4,6,6,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,3,3,,,,,2,2,,1,
-12760694694,1,3,2,2,2,4,5,5,1,2,1,2,2,2,5,4,2,5,5,5,2,2,1,4,3,4,5,5,2,4,4,4,3,4,2,3,3,3,4,3,3,3,,,2,3,,5,6,7,8,,,11,12,13,,,2,,4,,6,7,,,,,,,,1,,3,4,5,,,,,1,1,,1,,,2,10,,15,
-12760694211,1,3,2,2,4,5,4,3,2,4,3,4,3,3,2,4,4,3,4,3,5,4,3,4,3,4,5,4,4,3,,3,2,4,4,3,3,2,2,2,4,5,,,,,,,6,,,,,,,,,,,,4,,6,7,,,,11,,,,,,,4,,,,8,9,2,1,,1,,,3,14,,17,
-12760693352,1,4,3,1,5,4,5,4,3,4,3,4,4,1,4,4,4,4,2,5,4,4,5,5,5,3,4,4,5,4,3,5,3,4,5,3,4,2,1,4,5,5,,,,,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,,11,,,,,2,3,4,5,6,,,,2,1,,,,3,2,7,,5,
-12760693090,1,2,1,2,2,5,4,1,2,4,2,1,1,3,5,2,2,5,5,1,4,3,2,1,1,5,5,5,5,4,2,2,5,4,4,4,3,1,1,1,5,5,,,,3,4,,6,7,,,,,,,,,,,,,6,7,,,,,,,,1,,3,4,5,,,,,2,2,,,,,2,14,,2,
-12760692812,1,3,2,1,2,2,1,2,2,5,1,4,2,1,5,4,5,2,1,2,5,5,5,5,5,5,5,5,5,2,1,3,3,4,5,2,2,1,1,1,3,5,,,,,,,6,,,,,11,,,,,,,,,6,7,,,,11,,,,,,,4,5,6,,,,2,1,,1,,,2,14,,2,
-12760692735,1,2,1,1,3,4,2,2,4,,3,4,1,1,1,4,4,4,3,5,4,4,4,5,2,5,3,5,4,3,3,3,,4,4,3,2,1,2,1,5,5,,,,,,5,6,7,8,9,10,,,,,,,,,,6,,,9,,,,,,,2,,,,,,,9,2,1,,1,,,2,14,,1,
-12760691034,1,3,2,1,2,2,2,2,2,5,2,2,2,1,2,3,4,4,2,4,5,4,4,5,4,2,5,5,4,3,3,3,4,0,4,3,4,1,2,1,6,3,,,,,,,,,,,,11,,,,,,3,,5,6,7,,,,,,,,,,,,5,,,,,2,1,,1,,,2,14,,17,
-12760690605,1,4,3,1,2,2,2,2,2,2,2,2,2,2,2,2,3,2,1,3,3,3,2,3,4,2,5,2,4,2,2,4,4,4,4,3,2,4,3,1,5,5,,1,,,,5,6,7,8,,,,,,,1,,,,5,6,7,,,,,,,,,2,,4,5,,,8,9,2,1,,1,,,2,3,,11,
-12760689125,1,3,2,1,4,4,4,2,5,1,4,4,1,5,5,4,3,4,4,4,5,3,4,4,1,5,5,5,3,3,3,3,4,4,4,3,2,2,2,2,5,5,,,,,,5,6,,,,10,,,,,,,,,5,6,,,9,10,,,,,,2,,,5,,,,9,2,2,,,,,2,14,,17,
-12760687605,1,4,3,1,4,4,2,1,1,4,3,1,5,5,3,3,5,4,1,2,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,1,1,,,,,4,,,,,9,,,,,,,,,4,,6,7,,,,,,,,,,,,5,,,,9,2,1,,1,,,2,14,,5,
-12760686845,1,4,3,1,2,1,1,2,2,2,2,2,2,2,2,1,4,2,4,4,4,4,4,4,4,4,4,2,4,3,3,4,4,4,3,4,4,1,2,2,3,2,,,,,,,6,7,8,,10,,,,,,,,4,5,6,7,,,,,,,,1,2,3,4,5,6,7,,,2,2,,,,,2,14,,17,
-12760685944,1,3,2,2,3,2,1,1,5,5,1,2,1,1,2,4,3,5,1,5,5,5,5,5,2,5,5,3,3,4,3,5,3,5,5,4,1,1,3,1,5,5,,,2,,,5,,,8,,10,,,,,1,,,,,6,7,,,,,,13,,,,3,,5,,,,9,2,1,,,,3,2,14,,5,
-12760685921,1,2,1,1,2,2,2,3,5,5,2,4,2,2,5,3,3,3,4,5,3,3,4,5,2,5,5,5,3,3,2,3,3,4,3,2,2,1,1,1,5,5,,1,,3,,5,6,,,9,,,,,,1,,3,,5,6,7,,9,,,,,,1,2,3,4,5,,,,,2,1,,1,,,2,7,,5,
-12760685844,1,3,3,1,5,4,4,4,4,5,5,3,5,1,1,1,5,5,5,5,5,5,5,5,5,2,2,2,5,4,4,5,5,5,5,4,5,1,1,1,4,2,,1,2,,,5,6,7,,9,,,,,,,2,,,5,6,7,8,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,1,2,,9,
-12760684374,1,2,1,1,1,1,1,1,1,1,1,3,2,2,3,2,2,2,2,4,2,2,2,4,4,4,4,4,3,1,1,1,2,3,2,3,1,1,2,3,5,5,,1,,3,4,5,6,7,,,10,11,,,,1,,3,4,5,6,7,8,,,11,,13,,1,2,3,4,5,6,,,9,1,1,,1,,3,2,14,,1,
-12760683685,1,2,1,1,5,2,2,5,5,5,5,5,2,5,4,5,5,5,5,5,5,5,5,5,5,5,5,5,3,3,1,3,3,4,3,2,2,3,1,1,5,3,0,,,,,,,,,,,,,,,,,,,5,6,,,,10,,,,,,2,,4,,,,,9,2,2,,,,,2,1,,11,
-12760682504,1,4,3,1,2,1,2,1,2,1,2,2,1,2,5,0,5,5,4,1,3,0,1,5,1,2,2,1,3,2,1,1,2,3,4,2,1,2,1,2,1,2,,,,,,,6,,,,,,,,,,,3,,,,,,,,,,,,1,,,,,,,,,1,1,,,2,,2,2,,6,
-12760682177,1,3,2,1,1,3,3,1,1,1,1,2,1,4,4,3,1,4,4,2,2,,2,2,1,5,5,4,3,5,2,3,1,4,3,3,1,2,1,1,5,5,,1,,3,4,5,6,7,8,9,10,,,,,1,,,4,5,6,7,,9,10,,,13,,1,2,3,4,5,6,,8,9,1,1,,1,,,2,14,,1,
-12760681997,1,3,2,1,2,2,1,2,4,5,2,4,1,4,5,4,4,2,1,5,4,4,4,5,2,5,5,5,4,2,2,1,4,3,4,2,1,1,1,2,5,5,,1,,3,,,6,7,,9,10,,,,,,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,8,
-12760681372,1,4,3,1,2,1,2,1,2,3,2,2,2,2,4,1,4,1,2,2,2,4,4,4,4,4,5,2,4,3,2,3,4,4,4,3,3,2,4,2,4,5,,,,3,4,,6,7,,9,,11,,13,,,,,4,,6,7,,,,,,13,,1,2,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760680964,1,2,1,2,4,4,3,1,3,4,1,3,1,2,2,2,4,3,2,1,4,4,1,4,1,2,1,2,3,2,3,2,2,2,3,3,3,1,2,1,5,5,,,,,,,,,8,,,,,,,,,,,,6,7,8,,,,,,,,,3,,,,,,,2,1,,,,3,2,6,,15,
-12760679990,1,2,1,1,0,4,2,4,5,5,5,5,3,1,,1,5,1,1,5,5,5,5,5,1,1,5,1,4,5,1,1,4,5,4,5,1,1,4,1,4,2,,,,,,,,,,,,,,,,,2,,,,6,7,8,,,,,,,,,,,,,,8,,1,1,,1,,,2,3,,12,
-12760679370,1,4,3,1,4,4,2,2,4,4,4,4,2,2,3,3,3,2,2,3,3,3,4,5,5,2,3,4,3,3,2,3,4,5,3,2,4,2,1,2,5,5,,,,,,5,6,7,,9,10,11,,,,,,3,,5,6,7,,9,10,11,,13,,,,3,4,5,6,,,9,2,2,,,,,2,14,,17,
-12760679332,1,4,3,3,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,2,2,2,1,1,2,3,1,1,2,2,2,5,1,,,,,,,,7,,,,,,,,,,,,,6,,,,,,,,,,,,,5,,,,,2,1,,,2,3,1,0,Anglo Persian ,16,
-12760677846,1,2,2,1,5,5,5,5,5,5,5,5,3,3,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,3,3,5,5,5,2,4,2,1,1,5,5,,,,3,,5,6,7,,,,,,,,,,,,,6,,,,,,,,,,,3,4,,,,,,2,2,,,,,2,14,,2,
-12760677102,1,2,1,2,4,3,4,1,5,5,5,3,1,1,1,4,5,5,5,5,5,5,5,5,4,2,2,5,5,4,5,4,5,5,5,2,5,1,1,1,3,1,,1,2,3,4,5,6,7,8,9,10,11,12,,,,,3,4,5,6,7,,,,11,,,,1,,3,4,5,6,,,,2,2,,,,,1,13,,2,
-12760676288,1,3,2,1,4,4,2,3,5,5,5,3,2,2,2,2,2,5,2,5,5,5,5,5,4,2,2,2,5,3,2,4,5,0,5,3,3,2,1,1,5,5,,,,,,5,6,,8,9,10,,,,,,2,3,,5,6,7,,9,10,,,,,,,3,,,,,,9,2,2,,,,,2,2,,9,
-12760675438,1,4,3,1,5,2,2,3,5,5,2,4,2,3,5,4,5,2,2,5,5,5,3,5,4,5,5,4,5,2,2,4,2,5,5,2,2,1,1,2,3,5,,,,3,,,6,7,,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12760675125,1,2,2,1,2,3,1,1,4,4,2,1,2,1,2,1,3,2,1,5,3,3,4,2,1,5,5,2,3,2,1,3,4,4,3,2,2,1,1,1,5,5,,,,3,,,6,7,,,10,,,,,,,3,,5,6,7,,,,,,,,,2,3,4,5,,,,9,2,1,,1,,,2,14,,1,
-12760674741,1,2,1,1,4,4,2,1,5,4,2,4,1,2,2,2,4,3,4,4,5,5,4,3,2,5,4,5,3,2,1,1,3,4,3,2,1,1,1,1,5,5,,1,2,,,,6,7,,9,10,,,,,1,2,3,,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,14,,1,
-12760674326,1,2,1,2,1,3,4,2,1,2,1,2,2,2,4,4,3,2,5,5,2,3,2,2,5,5,5,5,4,2,1,3,3,4,2,2,4,2,2,1,4,5,,,,3,,5,6,7,8,9,10,,,,,1,,,,5,6,7,,9,,11,,,,1,2,3,4,5,6,7,,9,1,1,,1,,,2,14,,1,
-12760674219,1,4,3,1,3,4,1,2,5,4,5,3,4,2,2,4,5,5,4,5,5,5,5,5,5,4,5,5,5,3,2,4,5,5,5,3,4,2,1,2,6,6,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,2,3,,,,,,,2,2,,,,,2,17,,2,
-12760673740,1,2,1,1,2,4,2,1,3,5,3,2,2,1,2,3,4,2,4,2,4,3,5,4,2,5,5,4,4,3,3,3,4,3,4,1,2,1,1,2,3,5,,,,,,,,,,9,,,,,,1,,3,4,5,6,7,,9,10,11,,,,1,,3,,5,,,,,2,2,,,,,1,14,,5,
-12760673613,1,3,2,1,4,3,2,2,4,5,3,5,4,2,4,3,5,5,2,2,5,5,5,5,5,5,5,5,5,4,2,3,3,5,5,3,3,2,2,2,3,5,,,,,,,6,,8,,10,,,,,,,,,5,6,,,,,11,,,,,2,3,4,5,,,,,2,1,,,2,,2,14,,5,
-12760672907,1,2,1,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,3,4,3,4,3,3,4,3,4,4,3,3,3,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,3,3,,,,,2,2,,1,
-12760672433,1,2,1,1,1,2,1,5,1,2,1,5,2,1,3,4,3,4,1,4,4,4,3,4,5,2,5,4,4,4,3,2,4,4,4,4,2,2,1,1,5,5,,,,,,5,6,7,,,,,,,,,,,4,,6,7,,,,,,,,,,3,4,,,,,,2,1,,,,3,2,14,,17,
-12760672302,1,2,2,1,2,3,3,2,5,2,2,2,2,2,4,3,1,4,3,4,3,1,1,4,4,3,5,4,4,4,3,4,5,3,4,2,4,1,1,1,,3,,,,,,,6,7,,9,,,,,,,2,,,,6,7,,9,10,,,,,1,2,3,4,5,6,7,8,9,1,1,,1,,,1,10,,2,
-12760672222,1,3,2,1,2,2,2,2,2,2,2,2,2,1,4,3,2,4,4,4,4,3,4,4,4,2,4,4,4,3,2,3,4,3,4,2,3,2,1,2,5,5,,1,,,4,5,6,7,,,10,11,,,,,,,,,6,7,,,10,11,,,,1,,3,4,5,6,,,9,2,1,,,,3,2,14,,5,
-12760671805,1,3,1,1,4,2,3,2,3,2,1,2,1,1,3,2,5,2,2,5,5,4,3,4,5,3,2,4,5,4,4,5,5,2,5,2,3,3,1,1,5,5,,,,,,,,,,,,,,13,,,,,,5,,7,,,,,,13,,,2,,,,,,,9,2,2,,,,,2,1,,11,
-12760671610,1,3,2,1,4,2,1,5,5,3,3,4,2,2,1,3,2,2,1,5,3,3,3,4,4,3,5,1,0,0,1,0,0,1,1,3,2,1,1,1,1,1,,,,,,,6,7,,9,,,,,,1,,,,5,6,7,,9,,,,,,1,2,3,4,5,6,7,8,9,2,2,,,,,2,6,,5,
-12760671546,1,3,2,1,2,4,1,4,3,4,4,4,3,4,4,4,2,2,1,4,3,5,5,4,4,5,5,5,3,3,2,3,3,3,3,2,3,1,2,1,5,5,,,,,4,,6,7,,,10,,,,,,,,4,5,6,7,,,,,,,,1,2,3,4,5,,,,9,1,1,,,,3,3,12,,2,
-12760671249,1,3,2,1,3,3,2,2,4,4,3,3,3,1,2,3,5,5,4,4,5,5,5,3,5,2,3,5,4,4,3,2,3,5,4,2,4,1,1,3,5,2,,1,2,3,4,5,,,8,,,11,,,,,,,4,5,6,7,,,,11,,,,,2,3,4,5,6,,,,2,1,,,,3,1,14,,5,
-12760671100,1,2,1,1,2,4,1,2,2,4,2,2,2,1,4,2,2,4,1,2,4,4,4,4,2,4,5,2,3,4,2,2,3,4,3,1,1,1,1,1,6,5,,,,,,,6,7,,,10,,,,,,,,4,,6,7,,9,,11,,,,,,3,4,,,,,9,2,1,,,,3,2,14,,15,
-12760670966,1,4,3,1,3,1,2,2,3,4,2,2,1,2,2,2,4,2,2,4,4,3,5,3,3,5,5,3,4,3,3,4,3,3,5,2,4,1,2,2,3,2,,1,2,3,,5,6,7,,,,,,,,1,,3,4,5,,7,,,10,,,,,1,2,3,4,5,,7,,,2,2,,,,,2,14,,17,
-12760670287,1,2,1,1,3,2,2,2,3,4,1,1,1,2,5,5,5,5,5,5,5,5,5,2,2,5,5,5,4,2,3,3,5,4,4,3,1,1,1,1,5,3,,,,,4,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,7,,11,
-12760670026,1,4,3,1,4,2,4,2,4,5,2,4,4,2,4,5,5,3,3,5,4,5,4,5,4,4,5,3,4,5,4,5,4,4,5,1,3,1,1,2,1,5,,1,,,,,,,,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12760669222,1,3,2,1,3,3,2,2,3,3,2,1,2,2,2,3,2,2,4,2,3,5,4,1,4,5,5,4,2,4,4,2,3,3,2,2,2,1,1,3,1,2,,,,,,,6,,,9,,,,,,,,,,,6,7,,9,,,,,,,2,3,,5,,,,,2,1,,,,3,2,14,,1,
-12760668820,1,2,3,1,3,3,3,2,3,4,2,1,1,1,2,2,4,2,2,4,4,4,4,2,4,2,4,2,3,2,2,2,3,3,3,1,3,2,3,1,4,5,,,,,,,,,,,10,11,12,,,,,,,5,,7,,,,11,,,,,2,3,,,,,,,2,1,,,,3,2,1,,11,
-12760668581,1,3,2,2,3,3,3,2,3,3,3,2,2,2,2,1,3,3,3,3,3,3,3,3,3,3,3,1,0,0,0,0,0,0,0,0,0,0,0,1,6,5,0,,,,,,,,,,,,,,,,,,,,,7,8,,,,,,0,,,,,,,,,,2,2,,,,,2,14,,5,
-12760668417,1,4,3,1,3,3,1,2,4,2,3,2,3,2,2,4,1,3,1,3,4,3,4,4,4,4,3,4,4,3,4,4,3,3,3,5,4,4,5,4,3,5,,1,,3,,,6,,,,10,,,,,1,,3,,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12760667850,1,3,1,1,4,5,3,2,1,2,2,4,1,3,2,4,2,3,5,1,3,4,5,4,2,5,5,4,4,3,3,3,4,4,3,2,3,1,1,1,4,5,,,,,,5,6,7,,9,,,,,,,,3,,5,6,7,,9,10,,,,,1,2,3,4,5,,,,9,2,2,,,,,2,14,,15,
-12760667831,1,2,1,1,2,4,3,1,2,5,3,2,1,2,2,3,3,3,4,1,3,3,3,2,3,3,2,3,5,4,2,4,5,5,4,3,1,1,1,2,5,5,,,,,,,,7,,,,,,,,,,,,5,6,,8,,,,,,,,,3,4,5,,,,9,2,2,,,,,2,2,,14,
-12760667205,1,2,1,2,4,4,4,1,4,3,2,4,1,4,2,4,5,5,4,2,2,2,2,2,3,4,2,3,5,4,4,3,5,5,4,3,4,1,1,2,5,5,,,,3,,5,6,7,,9,10,,,,,,,3,4,5,6,7,8,9,,11,,13,,1,2,3,4,5,6,,,9,2,1,,,,3,4,0,,0,
-12760667059,1,4,3,1,4,4,3,2,5,5,3,4,2,1,2,3,3,4,2,5,4,4,5,5,4,1,5,4,4,3,3,3,5,5,4,3,4,1,2,2,3,3,,,2,3,4,,6,7,,,,,,,,,2,,,,6,7,,,,,,,,1,,3,4,,,,,9,2,2,,,,,2,14,,17,
-12760666867,1,4,3,1,1,1,4,2,1,1,1,4,2,2,5,4,2,1,5,5,5,2,2,5,5,5,5,5,4,1,1,2,4,4,5,1,1,1,0,1,5,5,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,,,,,,,1,1,,,,3,2,8,,5,
-12760666572,1,2,1,1,2,2,2,2,2,4,4,1,2,2,4,2,2,4,4,2,2,3,2,1,4,5,5,4,4,3,3,3,4,4,3,2,3,1,1,2,3,4,,,,3,,,6,7,,,,,,,,,,3,4,,6,,8,9,,,,,,1,,3,4,5,,,,9,2,1,,,,3,2,17,,2,
-12760666192,1,3,2,1,4,2,2,2,3,4,2,3,1,2,5,4,5,4,4,5,5,5,5,5,4,5,5,5,3,4,3,2,4,4,4,2,4,1,1,4,5,5,,,,3,,5,6,7,,,10,,,13,,,,3,,,6,,,9,10,,,,,,,3,,,,,,9,2,1,,,,3,2,14,,5,
-12760666164,1,3,3,1,2,4,2,3,2,5,2,4,2,1,2,3,3,5,2,5,2,5,5,5,5,2,2,4,5,4,2,3,4,5,5,5,3,1,1,1,3,2,,1,2,3,,5,,7,8,9,10,,,,,,2,3,4,5,6,,8,9,10,11,12,,,1,2,3,4,5,6,7,8,9,2,2,,,,,2,14,,2,
-12760665898,1,3,2,1,3,4,4,3,4,3,,4,3,1,2,2,2,5,5,5,5,5,5,5,5,2,2,2,3,3,3,3,4,5,5,4,4,1,1,1,2,5,,,,3,,5,6,7,8,9,,,,,,,2,3,4,5,6,7,8,9,,,,,,,2,,,5,,,,9,2,2,,,,,2,17,,0,Catholic
-12760664674,1,3,2,1,5,4,5,4,5,5,2,5,2,5,5,5,2,2,2,2,2,2,2,3,2,3,4,2,4,1,1,2,2,5,2,5,3,5,5,1,5,5,,1,,3,,,6,,,,,,,13,,,,,,5,,,,,,,,,,,,,4,,,,,9,2,1,,1,,,2,14,,5,
-12760664547,1,4,3,2,4,4,1,2,4,4,4,4,2,4,4,5,4,2,2,5,2,2,3,2,2,5,5,5,4,4,2,2,4,3,4,3,5,2,3,3,5,5,,,,3,,,,7,,9,10,,,,,,,,4,,,7,,9,10,11,,13,,1,2,3,4,5,,,,9,2,1,,1,,,3,14,,2,
-12760664239,1,2,1,1,5,2,1,2,5,5,5,5,5,5,5,5,5,2,1,2,5,5,5,5,5,5,5,5,2,2,1,4,3,4,4,3,2,1,1,1,3,5,,1,,,,,6,7,,,,,,,,1,,3,,5,,,,,,11,,,,,,3,,5,,,,9,2,2,,,,,2,14,,17,
-12760663576,1,2,1,1,1,3,2,2,2,4,1,2,2,2,4,5,2,4,4,5,2,3,3,4,1,5,5,5,4,4,3,4,4,5,4,2,3,2,1,1,5,5,,1,,3,,5,6,7,,9,,,,,,,,3,4,5,6,7,,9,,,,,,,2,3,4,5,,,,9,1,1,,1,,,2,14,,2,
-12760663440,1,3,2,3,3,4,3,3,4,3,3,3,3,2,1,3,5,5,3,3,5,5,5,5,3,4,2,5,3,2,3,2,3,3,3,2,2,2,1,2,3,4,,1,,3,,5,6,7,,9,10,,,,,1,,3,4,5,6,7,8,9,10,,,,,,,3,4,5,,,,9,2,2,,,,,2,13,,5,
-12760662542,1,3,2,2,3,2,3,2,4,5,3,3,1,4,1,2,3,2,5,4,3,4,3,3,1,5,3,4,4,3,2,3,4,4,4,4,2,2,1,2,3,4,,,2,3,4,,6,7,8,9,10,,,,,,2,3,,5,6,7,8,,10,,,,,1,2,3,4,5,,,8,,2,2,,,,,2,14,,1,
-12760662496,1,2,1,1,2,2,3,2,3,5,4,2,2,2,5,3,3,4,2,2,4,4,5,2,4,5,5,4,3,5,2,3,5,3,5,1,4,1,1,2,5,5,,,2,,,5,6,7,8,,10,,,,,,,3,,5,,7,,,,,,,,1,2,3,4,5,6,7,,,2,2,,,,,1,13,,2,
-12760661859,1,2,2,3,5,4,4,1,5,5,3,4,2,1,4,2,5,5,5,5,5,5,5,2,5,2,5,5,4,4,4,3,5,5,5,3,3,1,1,4,1,1,,1,,,4,5,6,7,,9,,,,,,1,,,4,5,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,1,14,,2,
-12760661500,1,3,2,1,1,5,4,3,1,2,4,4,5,1,4,2,1,5,1,5,1,5,5,5,5,1,5,5,4,3,2,4,3,5,4,3,3,1,1,2,5,5,,,2,3,4,5,6,7,,9,10,11,,,,,,3,4,5,6,7,,,10,11,,,,1,2,3,4,5,6,7,8,9,2,2,,,,,1,5,,1,
-12760661473,1,4,3,1,5,5,5,5,5,5,5,5,5,3,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,3,3,4,4,3,1,1,2,4,5,0,,,,,,,,,,,,,,,,,,4,5,6,7,,,,11,,,0,,,,,,,,,,2,1,,1,,,2,8,,5,
-12760661459,1,3,2,1,4,4,2,1,1,5,4,4,1,1,5,4,2,5,5,1,2,2,5,2,2,5,5,5,5,5,5,5,5,5,5,4,5,1,1,1,1,1,,,,,,,6,7,,,,,,,,,,,,,6,7,8,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,5,
-12760661011,1,4,3,1,4,3,2,3,5,5,2,4,3,1,3,2,5,5,4,5,5,5,5,5,5,5,5,5,5,2,3,5,3,4,4,2,4,3,3,1,5,5,,,,3,,,6,7,,9,,,,13,,1,,3,,5,,7,,,10,,,,,,,3,4,,,,,,2,1,,,,3,2,4,,11,
-12760660756,1,3,2,1,2,1,1,4,3,2,5,2,2,1,2,1,4,4,4,5,5,4,5,2,5,4,3,1,4,3,2,5,3,3,4,3,3,1,1,2,5,5,,,,,4,5,6,7,,,10,,,,,1,2,3,,5,6,7,8,9,10,11,,13,,1,2,3,4,5,6,,,9,2,2,,,,,1,14,,2,
-12760659783,1,3,3,1,3,4,3,1,3,4,2,1,1,2,2,2,2,2,2,1,3,3,4,5,2,4,2,2,4,3,1,3,4,4,4,2,3,3,1,1,5,5,,,2,3,4,5,6,7,,,10,,,,,1,,3,4,5,6,7,,,10,11,12,,,,2,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12760658844,1,3,3,1,5,4,3,1,4,5,4,5,2,3,2,5,4,4,3,1,4,4,5,5,2,5,4,4,3,3,2,2,3,3,4,2,2,3,2,1,2,2,,,,3,,,6,7,8,,10,11,,,,,,,,5,6,7,8,9,10,11,,,,,2,,,,6,,,9,2,2,,,,,2,14,,17,
-12760658623,1,2,2,1,5,3,1,2,3,4,2,4,1,2,2,3,2,3,1,3,3,4,3,4,3,3,2,4,3,3,1,3,3,4,3,3,2,1,1,2,5,5,,1,,,,,6,7,,,,,,,,,,3,,,6,,,,,,,,,,,3,,,,,,9,2,2,,,,,2,3,,11,
-12760657651,1,3,2,1,3,2,2,1,2,5,1,2,1,2,2,3,4,3,2,4,3,5,3,5,2,5,1,4,1,2,1,3,3,3,3,3,2,1,1,1,5,5,,,,,,,6,,,,,,12,,,,,,,,6,7,,,,,,,,,2,3,,5,,,8,,2,1,,,,3,2,2,,5,
-12760657203,1,3,2,2,3,3,4,2,3,3,3,2,3,2,2,3,5,5,5,4,4,5,5,5,5,2,2,3,4,4,5,4,4,5,4,4,4,2,1,2,3,3,,1,,3,,5,6,7,,,,,,,,1,,,,5,6,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,1,14,,5,
-12760657152,1,2,1,3,3,4,4,2,4,5,4,4,1,1,2,2,5,2,5,4,3,2,5,5,5,4,5,1,5,3,2,4,5,4,5,2,2,1,1,1,5,5,,,,,,,6,7,,9,,,,,,,,,,,6,7,8,,,,,,,,,3,4,5,,,,9,2,2,,,,,1,4,,11,
-12760656607,1,3,2,1,2,4,5,2,2,2,1,5,1,4,5,5,2,5,5,4,2,4,2,5,3,5,5,5,2,1,1,4,4,4,4,1,1,1,1,1,5,5,,,,,,5,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,,3,4,5,,,,9,1,1,,,,3,3,14,,15,
-12760656529,1,4,3,1,2,3,2,1,2,5,2,3,1,1,1,1,5,5,5,5,5,5,5,5,5,5,5,5,4,2,2,3,4,4,4,2,3,3,1,1,5,5,,,,,,,6,7,8,,10,,,,,1,,3,,,6,7,,,,,,13,,,,3,4,5,,,,9,2,2,,,,,2,2,,11,
-12760655960,1,4,3,1,2,1,1,2,4,4,4,1,4,2,2,2,5,2,2,5,5,5,4,1,5,3,5,2,5,2,5,4,4,5,2,2,3,1,1,1,5,3,,,,3,,,,,8,9,10,,,,,,,3,,,6,7,,9,10,,,,,,,3,4,,,,,9,2,1,,1,,,2,2,,11,
-12760655902,1,3,2,1,1,4,2,3,3,4,1,4,2,3,5,2,1,5,4,2,2,5,2,2,2,3,5,2,3,3,3,3,3,3,3,3,5,3,1,1,1,1,,1,,3,,,,,8,9,,,,,,,,,,5,6,,,9,10,,,,,,,3,,,,,8,,2,1,,1,,,2,14,,5,
-12760655786,1,3,3,1,2,4,1,1,1,5,1,4,1,2,3,1,2,3,3,1,2,4,5,5,3,5,5,4,5,2,1,1,2,5,5,1,3,1,1,1,5,5,,,2,,,,6,,,,,,,,,,,,,,6,7,,9,,,,,,,2,,4,,,,,9,1,2,,,,,2,14,,5,
-12760655425,1,4,3,1,2,4,2,1,2,5,4,1,1,1,2,5,5,5,5,1,2,5,5,1,1,5,5,5,3,5,3,1,5,5,5,2,1,1,1,1,3,1,,,,,,,,,,9,,,,,,,,,,5,6,7,,9,,,,,,,,3,,,6,7,,,2,1,,,,3,2,14,,2,
-12760654702,1,2,2,1,3,3,3,3,3,3,3,3,3,2,3,3,5,5,5,5,5,5,5,5,5,4,5,5,0,0,0,0,0,0,0,0,0,0,0,0,5,5,,,,,4,,6,7,,,,,,,,,,,,,6,7,,,,,,,0,,,,,,,,,,2,1,,,,3,2,14,,2,
-12760654535,1,4,3,2,5,2,4,5,4,3,2,4,3,2,5,2,5,3,4,4,4,4,4,4,5,2,4,2,4,2,2,5,3,4,5,1,3,1,1,1,5,3,,1,2,3,,5,6,7,8,9,10,,,13,,1,2,,4,5,6,7,,,10,11,,13,,,,3,4,5,,,,9,2,1,,,,3,2,7,,2,
-12760654220,1,3,2,1,1,3,2,2,1,2,1,2,1,2,2,3,2,4,3,3,2,3,2,4,2,4,2,4,4,4,2,3,4,4,4,2,3,1,1,2,4,5,,,,,,5,6,7,,,10,,,,,,,,,,6,7,8,9,10,,,13,,,2,3,4,5,,,,9,1,1,,,,3,2,14,,2,
-12760654180,1,4,3,1,2,4,5,1,2,5,5,5,2,1,1,2,5,5,5,5,5,5,5,5,5,2,1,5,5,2,3,4,5,0,4,3,3,3,1,1,1,5,,,2,,,,6,7,,9,,,,,,,,,,5,6,7,,9,10,,,,,1,2,3,,5,6,,,9,2,1,,,,3,1,15,,1,
-12760653651,1,3,2,1,4,1,2,4,4,4,3,4,1,4,4,4,5,1,5,5,5,5,4,5,2,5,5,5,4,4,1,3,4,4,4,2,3,2,1,2,3,3,,,,,,,6,7,,,,,,,,,,,,,,7,,,,,,,,,,3,4,,,,,9,2,2,,,,,2,3,,11,
-12760652607,1,4,3,1,4,4,4,1,4,5,1,1,1,1,2,1,5,5,5,3,4,5,5,2,5,5,5,4,4,3,3,2,4,4,4,1,3,1,1,1,3,5,0,,,,,,,,,,,,,,,1,,3,4,5,6,7,8,,10,11,,,,1,2,3,4,5,6,7,,9,2,2,,,,,2,14,,5,
-12760652573,1,4,3,1,1,1,2,2,2,2,2,1,2,1,4,1,2,2,2,1,2,2,2,1,2,4,5,2,3,2,1,2,3,3,3,2,3,1,1,2,5,5,,1,2,3,4,5,6,7,8,9,10,11,,13,,,2,,4,5,6,7,8,9,10,11,,13,,,2,3,4,5,6,,,9,2,2,,,,,2,14,,5,
-12760652413,1,4,3,1,5,1,2,5,2,5,5,2,1,2,5,2,5,1,1,5,5,3,5,2,1,5,5,1,4,3,3,4,5,3,5,1,4,1,1,1,2,3,,,,,,,,,8,,,,,,,,,,,,6,,,,,,,,,,,,,,,7,,,2,2,,,,,2,14,,17,
-12760651997,1,2,1,1,1,3,4,1,1,2,4,2,1,2,4,4,1,3,3,1,1,5,5,3,1,5,4,1,3,3,3,2,3,5,5,3,1,1,1,1,3,,,,2,,,5,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,1,17,,2,
-12760651451,1,2,1,1,4,3,4,1,4,4,3,4,1,1,1,4,4,4,4,2,4,4,4,3,3,1,4,4,5,4,5,2,5,4,5,1,2,1,1,4,3,5,,,,,,5,,7,,9,,,,,,,,,4,5,6,,8,9,,,,,,,,3,4,5,6,,,,2,2,,,,,2,14,,5,
-12760651430,1,4,3,1,5,5,5,3,5,5,5,4,3,2,4,3,5,5,5,3,5,5,5,5,5,2,3,3,4,4,3,3,4,4,5,3,2,1,1,1,6,6,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,2,,,,,2,14,,2,
-12760651149,1,4,3,1,5,5,5,1,4,5,1,5,1,1,1,2,5,5,3,5,5,5,5,5,5,2,2,3,4,4,1,3,5,4,4,3,3,1,1,2,5,5,,,2,,,5,,7,,9,10,,,,,,,3,4,5,6,7,,9,,11,,,,1,2,3,4,5,6,,,,2,1,,,,3,1,3,,11,
-12760650517,1,2,1,1,2,4,2,1,3,5,2,3,5,1,1,2,2,4,5,5,4,4,3,5,5,1,1,3,4,4,5,2,3,5,4,3,5,1,1,2,3,3,,,,,4,,6,7,8,9,,11,,13,,1,2,3,4,5,6,7,8,,10,,,,,,2,,4,5,,,8,9,2,2,,,,,1,1,,11,
-12760650201,1,4,3,1,4,2,2,2,4,4,4,2,2,2,4,4,2,2,3,2,2,2,2,1,1,4,4,4,3,3,2,3,4,4,4,3,3,2,1,2,2,1,,,2,,,5,6,7,,,10,11,,,,,2,3,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,,8,9,2,2,,,,,2,14,,2,
-12760649967,1,3,2,2,5,4,4,4,5,5,5,5,5,2,3,2,5,5,5,5,5,5,5,5,5,3,5,5,4,4,1,3,3,4,3,3,2,3,3,2,6,6,,,,,,5,,,8,,,,,,,,,,,5,6,7,,,,,,13,,,2,3,4,5,,,,,2,2,,,,,2,14,,5,
-12760649586,1,3,2,1,5,3,3,1,4,5,1,3,1,1,1,3,5,2,,5,5,5,5,5,5,2,5,5,5,,1,5,5,5,5,1,5,1,1,1,5,5,,,,,4,,6,7,8,,,11,,,,,2,,4,,6,7,8,,,,,,,1,,,4,5,,,,,2,1,,,,3,2,7,,5,
-12760648989,1,2,1,1,3,3,2,1,4,4,2,3,1,1,4,3,4,4,3,3,4,4,5,5,5,2,4,4,4,4,2,3,3,4,4,3,3,2,1,2,3,4,0,,,,,,,,,,,,,,,,2,,4,5,,7,,,,,,,,,2,3,4,,,,,9,2,2,,,,,2,14,,2,
-12760648752,1,2,1,1,4,2,2,2,4,4,2,4,2,2,4,2,5,5,1,5,5,5,5,5,5,5,5,5,4,3,2,3,4,4,4,3,2,1,1,2,5,4,,,,,,,6,7,,,,,,,,,,3,,5,,7,,9,,,,,,,,3,4,,,,,9,2,1,,1,,,2,2,,9,
-12760648641,1,2,3,1,4,3,2,2,4,4,5,3,1,1,1,5,5,5,2,2,5,5,5,5,1,1,1,5,3,3,1,4,4,3,3,3,3,1,1,1,5,4,,,,,,,6,7,,9,10,,,,,,,,,5,6,,8,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,2,2,,2,
-12760647852,1,3,3,1,3,3,2,2,4,4,3,3,2,1,3,2,4,4,4,4,4,4,4,4,4,2,4,4,4,4,4,2,4,4,4,2,2,1,1,2,3,3,,,,,,,6,,,,,,,,,,,,,,,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12760646154,1,4,3,1,2,1,2,1,2,2,1,1,1,2,2,1,4,4,4,2,4,4,4,4,1,5,5,2,5,4,3,3,5,5,5,3,3,1,1,1,5,5,,1,,,,,6,7,,,,,,,,1,,3,4,5,6,7,,,,11,,,,1,2,3,4,5,,,,9,2,2,,,,,2,14,,14,
-12760645670,1,4,3,1,5,2,1,4,4,5,4,5,2,5,5,4,5,2,1,4,5,,5,4,2,5,5,5,3,3,2,4,5,4,5,2,2,4,3,4,4,3,,,,,,5,,7,,,10,11,,,,,,,4,,,,8,,,,,13,,,2,,,,,7,,9,2,2,,,,,2,17,,2,
-12760645257,1,4,3,1,3,4,3,2,2,3,3,4,2,2,2,3,4,4,3,3,4,4,4,5,3,4,2,3,3,2,3,3,3,3,2,2,3,1,2,2,6,3,0,,,,,,,,,,,,,,,,,3,,5,6,,,9,10,,,,,1,,,,,,,,9,2,1,,,,3,3,14,,5,
-12760645220,1,3,3,1,4,1,2,2,3,5,3,4,2,2,4,4,2,1,5,2,4,4,4,4,4,5,5,5,4,2,2,2,4,4,4,4,3,3,2,1,5,5,,,,3,,5,6,7,,,10,,,,,,,3,,5,6,7,8,,,11,,13,,1,,3,4,5,,,,9,2,1,,,,3,2,14,,2,
-12760645196,1,4,3,1,4,5,5,5,5,5,5,4,2,5,5,4,5,3,2,4,5,3,4,2,5,5,4,2,4,3,3,2,4,3,3,2,3,3,1,2,6,5,0,,,,,,,,,,,,,,,,,,4,5,6,7,,,10,,,,,1,2,3,,,,,,9,2,2,,,,,2,14,,1,
-12760644759,1,2,1,1,3,3,4,1,2,3,2,1,2,3,5,2,3,2,5,1,2,3,4,1,3,5,5,3,3,2,0,3,3,4,5,1,2,1,1,1,3,5,0,,,,,,,,,,,,,,,1,,3,4,5,,7,,,,11,,,,,,3,4,5,6,,,,2,1,,,,3,2,14,,17,
-12760644088,1,4,3,1,3,2,2,2,3,2,2,2,1,1,2,1,2,2,2,3,2,3,3,2,1,1,2,1,4,2,3,3,3,3,2,3,1,1,1,1,3,2,,,2,,4,5,,,,,,11,,,,1,2,3,4,,6,,,,10,11,,13,,,2,3,4,,,,8,,2,1,0,,,,2,17,,5,
-12760643315,1,3,2,3,2,1,1,1,2,2,2,1,,1,1,2,2,,1,4,2,2,2,5,5,2,1,5,2,1,1,3,2,4,3,1,3,2,1,1,5,5,,1,2,3,,5,6,7,8,9,10,,,,,,2,,4,5,6,7,8,9,,11,,,,,2,3,4,5,6,7,,9,2,1,,,,3,2,14,,1,
-12760643118,1,3,2,1,2,2,2,1,2,2,2,2,2,2,3,3,4,5,5,1,5,5,5,4,4,4,5,5,3,3,3,2,2,3,3,2,2,2,3,2,5,5,,1,,3,,,6,7,,9,10,,,,,1,,3,,5,6,7,8,9,10,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,5,
-12760642960,1,2,1,2,3,3,2,3,3,3,2,3,2,2,3,2,5,4,3,3,4,5,5,4,3,4,5,4,4,3,2,3,4,4,3,2,2,2,2,2,4,4,,,,,,5,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,,2,3,4,,,,,,2,2,,,,,2,14,,2,
-12760642618,1,2,2,1,4,1,2,1,4,5,2,2,1,3,3,2,4,2,2,3,3,3,4,2,2,5,5,2,4,3,2,2,4,3,5,3,2,2,1,2,2,3,,,2,,4,5,6,7,,9,10,11,,,,,2,,4,5,6,7,,9,10,11,,13,,,2,3,4,5,,,,9,2,2,,,,,2,10,,1,
-12760642256,1,4,3,1,4,5,2,2,2,4,2,2,1,1,1,5,4,4,4,5,4,5,4,5,5,5,5,5,4,4,3,1,4,4,4,4,1,1,1,1,5,5,,,,3,4,5,6,7,,9,,11,,,,,,3,,5,6,7,,9,,11,,,,,,3,4,5,,,,9,2,1,,,,3,2,7,,11,
-12760641875,1,2,2,1,5,5,5,3,5,5,5,5,5,5,2,5,4,4,4,4,4,4,4,4,4,4,2,4,4,2,2,4,3,3,5,1,3,1,1,1,4,4,,,,,,,,7,,,10,,,,,,,,,,6,7,,,,,,,,,,,4,,,,,,2,1,,,,3,2,7,,5,
-12760641578,1,4,3,1,3,4,4,1,4,3,2,2,3,2,2,3,4,4,4,3,4,4,4,3,4,2,4,2,4,3,3,3,5,5,5,3,3,1,1,2,2,2,,1,2,3,4,5,6,7,,9,10,,,13,,,2,3,,5,,7,8,9,10,,,,,1,2,3,4,5,,,,9,2,1,,,,3,1,2,,5,
-12760641425,1,2,1,1,2,2,2,1,2,4,2,2,2,5,3,5,,,,,,,,,,,,,3,2,1,1,2,4,3,1,2,2,4,3,5,5,,,,,,,6,7,,,,,,,,,,3,,5,6,7,,,,,,,,1,,,4,,,,,,2,2,,,,,2,14,,5,
-12760641398,1,2,2,2,3,5,2,1,3,3,4,2,1,1,2,3,2,3,3,5,2,3,5,1,1,4,5,5,3,5,3,2,3,5,5,1,1,1,2,4,3,3,,1,,3,,5,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,1,,3,4,5,6,,,9,2,2,,,,,1,14,,2,
-12760641340,1,3,3,1,2,3,3,1,2,4,2,3,2,2,3,3,5,3,3,5,4,3,5,5,4,5,4,2,4,3,1,1,0,0,5,2,1,1,2,1,1,5,,,,,,,6,7,,9,,,,,,,,,,,6,7,,9,,,,,,,,3,,5,,,,9,2,1,,,,3,2,14,,2,
-12760641245,1,2,2,1,,4,4,4,4,4,4,1,2,1,2,2,5,5,2,5,5,5,5,2,4,1,2,3,3,4,3,4,4,4,4,2,3,2,1,1,5,5,,,,,,,,7,,9,,,,,,,2,3,,,6,7,,9,,,,,,1,2,3,4,5,,,8,9,2,2,,,,,2,2,,0,
-12760641200,1,3,2,1,4,2,3,2,4,5,3,5,1,2,2,2,5,2,2,5,5,4,4,5,4,5,4,4,5,2,2,2,5,4,4,1,2,1,1,1,5,5,,,,3,4,5,6,7,8,,10,,,,,,,,,5,6,7,8,,10,,,,,1,2,3,4,5,6,,8,9,2,2,,,,,2,14,,1,
-12760640693,1,3,1,2,3,1,1,2,4,5,3,3,3,5,5,5,2,1,1,2,3,2,3,5,3,5,4,5,4,3,3,3,4,,4,3,4,2,1,1,5,5,0,,,,,,,,,,,,,,,,,,,5,6,7,,,,,,,,,2,3,4,5,,,,,2,2,,,,,3,14,,1,
-12760640398,1,4,3,2,2,2,2,2,4,5,4,3,1,2,4,4,1,1,2,1,3,2,4,2,1,4,3,3,0,4,3,5,5,4,4,3,4,1,1,2,2,3,,1,,3,,5,6,,,9,10,,,,,,,,,5,6,7,,9,,,,,,1,,3,4,5,6,,,9,2,2,,,,,3,17,,1,
-12760640371,1,2,1,1,1,2,1,1,2,2,2,1,1,2,4,2,1,2,4,1,4,4,4,1,4,4,5,5,5,4,3,3,4,4,3,2,3,2,1,2,4,5,,,2,3,,5,6,7,,9,10,11,,,,,,3,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,7,8,9,2,2,,,,,2,14,,1,
-12760640317,1,4,3,1,3,3,2,1,3,4,2,2,2,2,3,2,5,3,4,4,3,5,5,2,3,2,5,2,4,3,2,3,4,4,4,1,3,2,2,2,4,5,,,,3,,5,6,7,,,,,,,,,,3,,5,6,7,,9,10,,,,,,2,3,4,5,,,,9,2,1,,,,3,2,2,,5,
-12760640054,1,4,3,1,1,1,1,1,1,3,1,1,1,2,1,1,0,0,0,0,0,0,0,0,0,0,0,1,3,0,3,4,1,3,2,1,2,2,1,1,6,5,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,0,,,,,,,,,,2,1,,,,3,2,0,,11,
-12760640019,1,4,3,1,4,4,4,2,5,4,4,2,2,1,4,2,4,4,4,4,4,4,4,4,4,1,4,4,3,3,3,3,3,4,5,2,2,1,2,1,1,1,,,,,,5,,7,8,,,,,,,,,3,,,6,,,,,,,,,1,,3,,5,,,,,2,2,,,,,2,14,,17,
-12760639936,1,4,3,1,5,5,2,2,4,1,2,2,1,1,5,4,2,5,2,4,5,2,1,3,4,2,4,3,4,5,5,3,5,4,4,3,5,1,1,1,5,5,,1,2,,,,6,7,8,9,10,,,,,1,,3,,,6,7,8,9,,,,,,,,3,4,5,6,7,8,9,2,1,,1,,,2,14,,1,
-12760639886,1,4,3,1,2,4,2,2,4,2,2,2,2,2,2,4,4,4,1,2,4,4,4,4,4,2,4,5,4,3,2,3,4,5,5,2,,1,1,1,5,4,,,,,,5,6,7,,9,,,,,,,,,,5,6,7,,9,,,,,,,2,3,4,,,,,9,2,2,,,,,2,17,,1,
-12760639698,1,2,1,1,4,4,4,4,2,3,4,3,4,1,4,3,2,2,2,3,2,3,3,2,3,1,1,2,3,3,3,4,2,3,3,1,3,2,1,1,4,5,,1,,3,4,,6,,,9,10,11,,,,,,3,4,,6,7,,9,,,,,,,,3,4,5,,,,9,2,2,,,,,1,5,,4,
-12760639661,1,3,3,1,3,1,2,1,4,5,2,1,2,3,5,4,5,5,4,1,5,5,5,5,3,5,5,5,4,4,2,2,3,3,4,2,2,1,1,2,5,5,,,,3,,,6,7,,9,10,,,13,,,,,,5,6,,,9,10,,,13,,,,3,4,5,,,,9,2,1,,,,3,2,14,,1,
-12760639572,1,4,3,1,3,2,1,3,3,5,2,4,2,2,4,2,5,1,2,5,4,0,5,5,5,5,5,5,5,3,2,4,5,4,4,3,3,3,1,2,6,3,0,,,,,,,,,,,,,,0,,,,,,,,,,,,,,,,,3,,,,,,,2,2,,,,,2,14,,17,
-12760639524,1,3,2,1,2,2,2,1,3,4,1,2,1,1,2,2,3,2,2,1,3,4,1,2,1,1,2,2,3,3,1,1,4,4,4,1,1,1,1,1,6,5,,1,,3,,,6,,,,,,,,,1,2,3,4,5,6,,,9,10,11,12,13,,1,2,,,,,,,9,2,1,,1,,,2,14,,5,
-12760639465,1,2,1,1,3,2,3,2,2,4,2,3,2,1,3,3,4,2,2,3,4,3,4,4,4,4,4,2,4,5,1,5,5,5,5,4,5,1,1,1,5,5,0,,,,,,,,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,,,,,,3,1,,1,,,2,0,,2,
-12760639411,1,3,2,1,3,3,1,2,1,3,3,1,1,1,3,4,1,4,1,4,2,4,4,1,1,5,5,3,3,3,1,1,0,5,4,1,3,1,1,2,5,5,,,,,,,6,7,8,9,,,,,,,,,,5,,7,8,9,,,,,,1,,3,4,5,,,,9,2,2,,,,,1,7,,5,
-12760639044,1,4,3,1,5,5,2,2,3,5,2,4,2,4,2,3,5,2,4,2,3,3,3,3,4,5,5,3,5,3,2,2,3,4,4,2,3,1,1,2,2,5,0,,,,,,,,,,,,,,,,2,3,,5,,,8,,10,11,,13,,1,2,3,,5,,,,9,2,2,,,,,3,14,,15,
-12760638854,1,4,3,2,3,3,3,3,4,5,4,1,2,1,4,2,4,2,2,4,5,3,5,3,2,5,5,2,3,2,2,4,3,0,3,1,3,2,1,1,6,4,0,,,,,,,,,,,,,,,1,,,4,5,6,7,,,10,,,,,1,2,3,,5,6,,,9,2,2,,,,,2,14,,17,
-12760638272,1,2,1,1,1,2,2,1,2,2,1,2,1,1,4,3,2,3,1,2,3,4,4,2,2,3,2,5,2,3,3,1,4,5,5,2,1,1,2,2,3,3,,,2,3,4,5,6,7,8,9,10,11,,,,,2,3,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,,8,9,2,1,,,,3,1,17,,1,
-12760637940,1,4,3,1,4,4,3,5,4,4,4,4,4,2,1,3,5,4,2,5,4,4,5,4,5,5,1,3,4,4,2,3,3,4,3,4,2,1,1,1,4,5,,,2,,4,,6,,,9,,11,,,,1,,,,5,6,,,9,10,,,,,1,2,3,,,,,,9,2,1,,,,3,1,4,,11,
-12760637883,1,2,1,2,3,2,2,2,4,5,2,2,3,2,2,2,4,5,3,5,5,5,5,4,5,4,2,2,5,5,3,5,5,5,5,3,4,1,1,2,2,3,,1,,,,5,,,,9,10,,,,,1,,3,,,6,,,9,10,11,,,,,,3,4,5,6,,,9,2,1,,,,3,1,2,,9,
-12760637761,1,2,3,2,3,1,3,4,3,3,2,5,2,2,3,3,3,1,1,4,3,3,4,5,4,4,3,3,3,1,1,3,3,3,2,4,2,2,2,1,3,3,,1,,3,4,,,7,,,10,,,,,,,,,,,7,,,10,,12,,,,,,4,5,6,,,9,2,2,,,,,2,14,,17,
-12760637595,1,3,2,2,2,1,1,2,2,2,2,3,2,2,1,4,4,2,2,4,4,4,4,5,4,5,3,5,3,2,1,3,2,4,4,1,3,2,1,1,5,5,,,,,,,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,2,1,,,,3,2,14,,15,
-12760637542,1,3,2,1,1,1,3,1,1,1,1,2,1,2,2,2,2,4,4,2,2,2,2,2,4,5,5,2,3,3,2,2,3,3,3,2,2,1,1,2,5,5,,,,,,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,,,3,4,,,,,,1,2,,,,,2,2,,14,
-12760637369,1,2,2,1,5,4,1,4,2,4,2,4,2,2,4,4,5,5,1,5,5,4,5,5,2,5,2,2,5,4,1,4,4,3,5,4,1,2,1,2,3,1,,,,,,,,7,,,,,,13,,1,,3,,,,,8,,,,,,,1,,3,,,,,,9,2,2,,,,,2,0,Lithuanian ,17,
-12760637076,1,3,2,1,3,2,3,2,3,3,3,2,2,3,3,3,3,3,4,2,3,3,3,3,2,5,5,4,2,2,2,2,2,2,2,2,2,2,2,2,5,5,,,,3,4,5,6,7,,,,11,,,,1,,3,,5,,7,,,,11,,13,,1,,3,4,5,6,,8,,2,2,,,,,2,11,,5,
-12760637059,1,4,3,2,5,5,5,2,5,5,2,5,2,1,2,2,1,1,1,1,1,1,1,5,1,5,5,1,3,1,1,4,1,1,3,1,1,1,1,1,5,5,,,2,3,4,5,,7,,,,,,,,1,,,4,,,7,,,,,,13,,1,,3,,,6,7,,,2,1,,,,3,2,14,,17,
-12760635976,1,4,2,2,3,5,2,2,4,3,2,4,1,3,5,5,5,5,5,4,4,5,5,5,2,5,5,5,5,3,4,4,5,5,5,1,3,2,1,1,4,4,,,,3,4,,6,7,,,10,11,,,,,,3,4,5,6,7,,,,,,,,,2,3,4,,6,,,9,2,1,,,,3,2,14,,1,
-12760635941,1,4,3,1,5,1,3,2,4,5,2,2,2,5,5,2,2,2,2,4,3,3,4,2,1,5,5,2,5,3,3,3,5,4,5,3,2,2,1,1,5,5,0,,,,,,,,,,,,,,,1,2,3,4,5,6,7,8,9,10,11,12,13,,1,2,3,4,5,6,7,8,9,2,2,,,,,3,14,,17,
-12760635869,1,3,2,1,3,2,2,2,3,2,3,2,2,3,3,3,2,2,2,2,2,2,2,2,2,5,5,4,3,2,3,2,3,3,3,3,1,1,1,2,5,5,,,,,,5,6,7,8,,10,11,,,,,,,4,5,6,,,,10,,,,,1,2,3,4,,6,,,9,2,1,,,,3,2,7,,5,
-12760635855,1,3,2,1,5,3,1,3,5,5,3,4,1,2,4,3,5,5,2,5,5,5,5,5,2,5,5,5,4,4,2,3,4,4,4,3,2,2,2,2,4,4,,,,,,5,6,,,9,10,,,,,,,3,,,6,7,,,,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,14,,2,
-12760635821,1,4,3,1,4,4,2,2,2,5,2,2,2,1,1,2,5,5,3,5,5,5,5,5,5,1,1,4,4,4,2,4,5,5,5,3,4,1,1,1,4,4,,1,,3,4,5,6,,8,9,,,,,,1,,3,4,5,6,7,,,10,,,,,1,2,3,4,5,6,7,,,2,2,,,,,2,14,,2,
-12760635796,1,3,2,1,2,3,2,1,3,2,3,2,1,1,1,1,5,4,4,1,5,3,5,4,3,5,1,2,4,3,3,3,4,4,4,2,2,1,1,1,4,3,,,,3,,,6,,,9,,,,,,,,3,,,6,7,,,10,,,,,,,3,4,5,,,,,2,2,,,,,1,14,,2,
-12760635606,1,2,2,1,2,4,3,3,3,5,5,2,3,2,2,2,3,3,2,4,4,4,5,2,3,3,5,2,3,3,3,2,3,3,4,2,3,2,1,1,5,5,,1,,3,4,5,6,7,,,10,,,,,1,,3,,,6,7,,,10,11,,,,1,2,3,4,5,6,,,,2,2,,,,,2,6,,5,
-12760635598,1,3,2,1,2,3,1,2,3,4,3,2,2,2,3,2,3,4,1,4,2,4,5,3,5,4,5,3,5,5,3,4,5,5,5,2,5,1,1,3,5,5,,,,,,5,6,7,,,10,,,,,,,,,5,6,7,,,10,,,,,,2,3,4,5,,,,,2,2,,,,,2,14,,17,
-12760635415,1,3,2,3,4,1,2,1,4,4,1,1,1,1,1,1,4,4,4,4,4,4,4,4,4,4,1,2,3,1,1,3,3,3,5,2,4,1,1,1,5,5,,1,,3,,,6,,,,,,12,,,1,,3,,,6,7,,,,,,,,1,2,3,4,5,,,,,2,2,,,,,2,14,,2,
-12760635345,1,4,3,1,4,4,4,4,4,4,4,2,2,2,4,2,5,5,5,5,5,5,5,3,5,3,5,2,5,4,3,3,5,5,5,2,3,1,1,1,5,5,,1,,3,,5,6,7,,9,10,,,,,1,,,,5,6,7,,,,,,,,1,2,3,4,5,6,,,9,2,1,,,,3,2,7,,5,
-12760635327,1,5,3,3,4,3,4,4,4,4,3,4,3,2,2,3,4,3,4,3,4,4,4,4,4,3,2,3,4,3,2,2,3,4,4,2,2,3,2,3,4,3,,1,,3,,5,,,,,10,11,12,,,1,,3,,,,,,,,,,,,,,,4,5,,,,,2,2,,,,,1,4,,11,
-12760635232,1,2,1,1,1,1,1,1,1,2,2,2,1,2,2,2,2,1,4,2,2,4,4,5,2,5,4,4,3,,2,3,3,5,5,2,2,1,1,1,5,5,,,2,,,,6,7,,9,,,,,,,,3,,5,,7,,9,,,,,,,2,3,4,,,,,9,2,1,,,,3,2,14,,17,
-12760635044,1,3,2,1,5,1,1,1,5,5,4,5,1,1,1,1,5,3,1,3,5,5,5,5,3,5,5,5,5,5,1,5,5,5,5,3,5,1,1,1,5,1,,,,,,,6,,,9,,,,,,,,,,,6,7,,9,,,,,,,,3,4,,6,,,,2,2,,,,,2,14,,17,
-12760635003,1,4,3,1,4,2,1,1,3,4,1,4,1,1,3,2,4,4,1,3,4,4,4,4,4,3,4,1,3,2,1,1,3,4,3,3,2,1,3,1,4,5,,,,,,5,6,7,8,,,,,,,,,,,5,6,7,8,,,,,,,,,,,,,,,9,2,1,,1,,,2,5,,17,
-12760634887,1,2,1,1,2,2,1,4,3,5,2,4,2,2,5,4,2,2,1,4,3,3,5,5,3,3,5,4,4,3,2,4,4,4,5,1,3,1,1,1,5,5,,,,,,,6,7,,9,10,,,,,,,,,5,6,7,,9,10,,,,,,,3,4,5,6,,,9,2,1,,,,3,2,14,,1,
-12760634833,1,3,2,1,2,3,3,2,3,4,3,2,1,2,3,2,5,5,5,5,5,5,5,5,4,5,5,5,2,1,1,3,4,4,4,1,1,1,1,1,6,3,,,,3,,,6,7,,,,,,,,,2,3,,,6,7,,9,,,,,,,,3,,5,,,,9,2,2,,,,,1,14,,2,
-12760634467,1,2,1,2,2,2,2,2,3,3,2,2,2,2,2,2,2,4,4,3,4,4,4,1,4,4,3,4,3,4,4,4,4,5,5,3,4,3,1,3,5,5,,,,,4,5,6,7,,9,10,11,12,13,,,,3,4,5,6,7,,9,10,,,,,1,2,3,4,5,,,,,2,2,,,,,1,14,,17,
-12760634285,1,2,1,1,2,4,4,1,2,5,1,5,1,2,5,5,4,4,4,4,4,4,4,5,2,5,5,5,4,3,4,3,4,3,4,2,1,1,2,1,5,5,,1,,3,4,,6,7,,,,11,,,,,,,4,5,6,7,,9,,11,,,,1,2,3,4,5,6,,,,1,1,,1,,,2,14,,5,
-12760634257,1,4,3,1,2,3,2,2,3,2,2,2,1,4,5,4,2,4,4,2,2,2,3,2,1,5,5,5,3,3,3,3,3,3,3,1,2,3,2,2,5,5,,,,,,,6,7,,,,11,,,,,,,,,6,7,,,,11,,,,,,3,4,5,,,,,2,1,,1,,3,2,14,,1,
-12760634138,1,3,2,1,2,2,1,2,4,5,4,2,2,1,2,3,2,2,1,2,4,5,3,4,2,5,5,5,3,3,2,2,2,4,3,2,3,2,1,2,5,5,,,,3,,,6,7,,,,,,,,,,3,,5,6,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,5,
-12760633761,1,3,2,1,2,2,1,5,4,5,2,1,1,1,2,1,2,5,4,5,4,5,5,1,5,1,2,2,5,4,2,4,5,5,5,1,3,1,1,1,5,1,,,,,,,6,,,,10,11,,,,,,,4,5,6,7,8,,10,11,,13,,,,3,4,5,,,,9,2,1,,,,3,2,9,,5,
-12760615990,1,4,3,1,4,3,1,1,2,4,1,1,1,1,2,3,4,4,3,5,5,5,5,2,5,2,4,3,3,3,2,3,4,4,3,2,3,1,1,2,3,4,,,,,,5,6,7,,,10,,,,,,,,,5,,7,,9,,,,,,,,3,4,,,,,9,2,2,,,,,2,14,,2,
-12760611371,1,3,2,1,4,4,2,2,4,4,2,4,2,2,2,2,5,5,3,5,5,5,5,5,5,5,3,5,3,3,1,3,3,3,3,1,3,1,1,3,5,5,,1,2,,4,5,6,7,8,9,10,11,,,,,,,,5,6,7,8,9,10,11,,,,,2,3,4,5,6,,8,9,2,1,,,,3,2,2,,14,
-12760610712,1,2,1,1,4,4,4,3,5,5,2,4,2,1,4,1,4,4,3,4,5,4,5,5,3,2,5,2,4,3,2,,5,4,4,3,1,1,2,1,5,5,,1,,3,,5,6,7,,9,10,,,,,1,,,,,6,7,,9,,,,,,,2,,4,5,6,,,9,2,1,,1,,3,2,7,,11,
-12760581791,1,4,3,1,4,2,1,2,4,4,2,2,1,2,4,2,3,2,1,4,4,3,4,4,2,5,5,5,4,3,2,4,3,4,4,2,4,2,1,2,5,4,,,2,,,5,6,7,,,,,,,,,,,,5,6,7,,,,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,17,
-12760577899,1,3,2,2,2,2,3,3,2,2,2,3,2,3,5,2,3,3,3,4,4,3,3,3,3,4,4,3,3,2,3,3,3,3,3,3,2,3,3,3,5,5,,,,,,,6,7,,,,11,,,,,,,,,6,7,,,,11,,,,,,3,4,5,,,,,1,2,,,,,2,14,,17,
-12760577365,1,3,2,2,4,2,2,2,4,4,2,2,1,1,4,2,5,2,2,4,5,3,5,5,2,3,5,3,3,3,2,4,3,5,3,2,3,2,4,2,4,2,,1,,3,,5,6,7,,,,,,,,,,,,,6,7,,,,,,,,,,3,4,5,,,,,2,2,,,,,2,14,,2,
-12760574950,1,4,3,1,3,1,2,2,3,2,2,4,1,5,3,1,3,2,2,5,3,3,4,4,3,5,5,1,4,4,3,3,5,3,5,4,2,2,1,1,3,3,,,,,,,6,7,,9,,,,,,,,3,4,5,6,7,8,9,10,,,,,1,2,,4,5,6,7,,,2,1,,,,3,2,17,,5,
-12760553713,1,3,3,1,2,1,1,1,2,2,1,1,1,2,4,2,2,1,4,1,2,2,2,1,2,5,5,5,3,4,4,4,3,3,3,4,4,5,5,4,5,5,,,,,4,5,6,7,,,,,,,,,,3,4,5,6,7,,9,,,,,,,,3,4,5,,,,9,2,1,,,,3,2,6,,9,
-12760548968,1,3,2,1,2,4,2,2,2,2,1,2,3,2,5,4,1,2,2,2,2,1,2,5,4,3,4,5,5,3,2,4,5,4,5,3,4,3,4,2,5,5,,,,,,,6,7,,9,10,11,,13,,1,,3,,5,6,7,,9,10,,,13,,,2,3,4,5,,,,9,1,1,,1,,,2,14,,5,
-12760530895,1,2,1,1,3,5,3,2,3,2,5,4,2,1,4,4,5,4,2,4,4,4,5,3,5,2,5,4,5,5,1,5,5,5,5,1,5,1,2,1,5,5,0,,,,,,,,,,,,,,,1,2,3,4,5,6,7,8,9,10,11,12,,,1,2,3,,5,6,,8,9,2,2,,,,,1,14,,2,
-12760522279,1,2,1,1,3,2,1,1,3,3,2,2,1,2,4,5,2,2,2,1,3,3,4,4,1,5,5,5,2,3,1,1,3,3,3,2,1,1,1,2,4,3,,,2,3,,5,6,7,,9,10,,,,,,2,3,,5,6,7,8,9,10,,,,,,,3,4,5,,,,9,2,2,,,,,2,14,,2,
-12760505147,1,3,2,1,4,4,3,1,3,5,2,4,2,1,5,1,4,4,4,3,4,4,5,5,5,4,5,1,3,3,3,4,4,3,5,1,2,1,1,1,3,2,,1,,3,4,5,6,7,,,,11,12,,,1,,3,,5,6,7,,,,,,13,,1,2,3,4,5,6,7,8,9,2,1,,1,,3,2,14,,2,
-12760495009,1,3,2,1,4,2,2,2,3,5,2,4,2,2,2,2,1,2,4,2,4,4,2,4,5,2,4,3,3,5,2,2,4,3,2,2,4,1,1,1,3,5,,,2,,,,6,7,,9,,11,,,,1,,3,,5,,,,9,10,,,13,,1,2,3,4,5,6,,,9,2,1,,1,,3,2,4,,11,
-12760494888,1,2,1,1,3,3,2,3,3,3,3,3,1,5,5,5,4,3,2,3,5,4,5,5,2,5,5,5,4,3,1,3,4,4,4,2,3,1,1,1,5,5,,1,,3,4,5,6,7,,9,10,11,,,,1,,3,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,7,,9,2,1,,,,3,2,14,,2,
-12760479804,1,4,3,1,3,3,3,2,3,2,2,4,2,2,2,3,4,4,2,3,2,2,2,2,4,2,2,2,3,4,4,2,4,2,2,2,5,1,1,1,3,2,,,,,,5,6,7,8,9,10,,,,,,,,,5,,,8,9,10,11,,,,1,2,3,,,,,,9,2,1,,1,,,2,17,,0,
-12760469673,1,2,1,1,3,5,1,2,4,5,3,3,3,1,1,3,5,4,2,2,5,5,5,2,2,2,1,3,3,4,1,2,3,4,4,2,4,1,1,1,2,1,,,,,4,,,7,,9,,11,,,,,,,4,5,,7,,9,,,,,,1,,,4,5,,7,,9,2,2,,,,,1,12,,17,
-12760460045,1,2,1,1,2,2,2,2,2,2,1,4,1,1,4,2,2,2,2,4,2,1,1,5,5,5,4,4,2,2,3,3,3,2,1,3,3,1,1,1,2,2,,,,,,,6,7,,,,,,,,1,,,,,,7,,9,,,,,,,,3,,5,,,,,2,1,,1,,3,1,14,,5,
-12760456158,1,4,3,2,5,3,3,2,4,3,2,4,2,2,2,4,5,5,5,5,5,5,5,5,5,5,5,5,4,4,3,4,4,4,4,2,3,3,1,1,3,3,,1,2,3,4,5,6,7,,9,10,,,13,,,2,3,4,5,6,7,,9,10,,,,,1,2,3,4,5,,,8,9,2,2,,,,,2,17,,17,
-12760448986,1,4,3,1,2,4,3,2,2,4,2,4,2,3,3,4,2,5,2,1,3,3,3,5,4,5,4,5,3,5,4,2,3,5,3,4,4,2,3,3,3,5,,1,,,,,6,7,,9,,,,,,,,,,,6,7,,,,,,,,1,2,3,4,5,,,,,1,1,,1,,3,1,14,,17,
-12760445331,1,2,1,1,4,4,4,2,5,5,2,2,1,1,5,5,5,5,2,2,5,5,5,5,5,1,3,3,5,3,2,3,5,4,4,3,2,1,2,2,3,3,,,,,4,5,6,7,8,9,10,,,,,,2,,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,,,,,2,1,,,,3,2,13,,2,
-12760426232,1,4,3,1,2,1,1,1,1,5,1,1,1,1,1,1,5,5,5,5,5,3,5,5,4,2,5,5,0,0,0,0,0,0,0,0,0,0,0,0,6,6,0,,,,,,,,,,,,,,,,,,4,5,6,7,,9,,,,,0,,,,,,,,,,2,2,,,,,2,14,,17,
-12760404346,1,2,1,1,1,2,2,1,1,4,1,3,1,1,2,2,1,2,4,1,1,4,4,1,4,4,4,1,4,3,3,4,3,3,4,2,3,2,3,2,5,5,,,,3,,5,6,7,,,,,,,,,,3,,,6,7,,,,,,,,,2,3,4,5,6,,,9,2,1,,1,,,2,14,,15,
-12760396383,1,2,2,1,4,2,4,4,4,4,2,1,1,1,1,4,4,2,5,4,4,5,5,2,2,5,4,4,4,2,3,2,3,4,2,3,2,1,1,1,3,2,,,2,3,4,5,,,,,10,,,13,,,,,4,,6,7,,,,,,,,1,,3,,5,,,,9,1,2,,,,,2,3,,11,
-12760376704,1,4,3,1,2,2,1,1,2,2,1,2,1,1,2,2,4,4,4,2,4,4,4,5,1,5,4,5,3,4,2,2,5,2,2,3,1,1,1,2,5,4,,,,,,5,6,7,,9,,,,,,,,3,4,5,,7,,9,10,,,,,1,2,3,4,,,,,,2,2,,,,,2,14,,1,
-12760368883,1,3,2,1,3,2,5,2,4,4,4,1,1,4,4,2,4,4,2,0,5,4,1,2,4,4,3,1,4,1,3,4,0,1,1,1,2,3,5,5,5,3,,,2,,,,6,7,,,,,,,,1,2,,4,,,7,,9,10,,,,,,,,4,,,,,,2,1,,1,,,3,17,,13,
-12760365642,1,3,2,1,4,2,1,2,4,5,4,4,1,4,5,2,4,2,1,4,2,4,4,4,2,4,4,2,2,1,1,2,2,2,3,1,1,1,2,1,4,5,,1,,3,,5,6,7,,9,10,,,13,,1,2,3,4,5,6,7,,9,10,11,,,,1,2,3,4,5,6,,8,9,2,1,,,,3,2,14,,17,
-12760358768,1,2,1,3,4,2,2,1,4,3,1,4,1,2,4,1,4,1,1,5,3,5,5,3,4,5,4,1,2,1,2,3,2,3,4,3,1,1,2,1,3,1,,1,2,3,,5,,,,,,,,,,,2,3,,5,,7,,,,,,,,,2,3,,,,,,9,2,1,,,,3,2,8,,5,
-12760355632,1,3,2,1,4,3,1,3,4,5,4,4,4,2,4,1,5,3,2,5,5,5,5,5,5,5,5,3,4,4,3,4,4,4,4,2,3,4,2,2,2,3,,,,,,,,7,,,,11,,,,,,,,,6,7,,,,,,,,1,,,4,,,,,,2,2,,,,,2,2,,2,
-12760350994,1,3,2,1,4,5,2,4,5,5,4,2,2,2,4,2,5,5,2,4,4,5,4,5,3,2,4,4,2,2,2,4,4,3,3,3,3,1,2,1,5,5,,1,2,3,,5,6,7,,9,10,,,,,,,,,,6,7,,9,10,,,13,,1,2,3,4,5,6,7,,9,2,2,,,,,2,6,,5,
-12760342980,1,2,1,1,4,4,4,5,0,5,2,3,3,2,2,5,5,5,2,5,5,5,5,5,5,1,2,5,0,3,0,3,0,0,0,0,1,1,2,1,6,5,0,,,,,,,,,,,,,,,,,,4,,,7,,9,10,,,,0,,,,,,,,,,2,1,,,,3,2,14,,5,
-12760341450,1,3,2,2,5,4,2,4,4,5,3,4,3,2,2,1,4,3,3,5,3,3,4,4,5,3,3,3,0,0,1,3,0,0,0,2,1,1,3,1,6,1,0,,,,,,,,,,,,,,,,,3,,,6,,,,,,,,,,2,,,,,,,,2,2,,,,,1,8,,5,
-12760334839,1,4,3,1,3,2,1,1,2,3,1,2,1,1,2,1,5,5,5,5,5,5,5,5,3,3,5,3,3,3,3,1,3,3,4,3,3,1,,1,5,5,,,,,,5,6,7,8,,10,,,,,,,,,,6,7,,,10,,,,0,,,,,,,,,,2,2,,,,,2,14,,17,
-12760333610,1,3,2,1,4,2,1,3,5,4,4,2,5,3,3,1,3,2,1,5,3,4,3,1,5,2,1,1,4,3,2,3,4,4,4,1,4,1,1,2,3,5,,1,2,3,4,5,6,7,,,10,,,,,,,3,4,,6,7,,,,11,,,,,2,3,4,5,,,,,2,1,,1,,,2,6,,11,
-12760328084,1,2,2,1,2,2,1,1,4,4,1,1,1,1,1,1,5,5,3,5,5,5,5,5,5,3,4,5,4,3,2,3,5,0,5,2,4,3,2,1,5,5,0,,,,,,,,,,,,,,,,,,4,5,,7,,,,,,,,,,,,5,,,,,2,2,,,,,2,14,,17,
-12760319724,1,2,1,1,4,2,1,1,4,5,2,2,1,1,5,3,5,5,2,5,5,5,5,5,5,5,5,5,5,5,3,2,5,5,5,2,2,1,1,3,3,5,,,,,,,6,,,9,,,,,,,,3,4,,6,7,,,,11,,,,,,3,4,5,,,,9,2,1,,,,3,2,7,,5,
-12760319722,1,2,1,2,1,3,3,2,2,3,1,5,1,1,4,4,5,5,5,5,5,5,3,5,5,3,5,5,4,4,3,2,1,2,1,3,1,1,4,3,3,5,,1,,3,,,6,,,9,,,,13,,1,2,3,,,6,7,,9,10,,,13,,,2,3,4,5,6,,,,2,1,,1,,,1,3,,11,
-12760314488,1,4,3,1,3,2,2,4,2,5,4,2,4,1,1,2,2,4,3,5,2,5,5,3,4,2,1,3,3,4,2,4,3,5,5,2,4,2,1,2,2,1,,,2,3,,5,6,7,,9,10,,,,,1,2,,4,,6,7,,9,10,,,,,1,2,3,4,5,6,,,9,2,2,,,,,1,2,,2,
-12760313918,1,2,1,1,1,4,1,2,1,2,2,4,2,2,4,4,1,4,1,2,1,2,2,5,2,4,4,5,3,3,2,3,4,3,3,2,2,4,1,1,5,5,,1,,,,5,6,7,8,,,,,,,1,,,,5,6,7,8,,,,,,,,2,3,4,5,,,,9,2,1,,1,,,3,17,,0,Agnostic Jewish
-12760313820,1,3,2,1,4,1,4,2,2,5,4,2,1,1,4,2,4,1,2,5,2,4,4,4,2,5,5,2,3,2,2,2,4,4,4,3,2,3,4,2,4,4,,,,3,4,5,,7,,,10,,,,,1,,3,4,5,,7,,,,,,,,1,2,3,4,,6,,,,2,2,,,,,2,14,,2,
-12760306577,1,2,1,1,3,3,2,1,2,2,1,1,2,1,2,3,5,5,3,5,4,5,5,2,5,2,2,5,5,3,2,3,4,5,5,2,5,1,1,2,5,5,,1,2,3,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,7,8,9,10,11,,,,1,2,3,4,5,6,7,8,9,2,2,,,,,1,7,,1,
-12760306138,1,2,1,1,2,2,2,3,1,1,2,4,2,1,1,3,3,2,2,5,3,5,5,5,4,1,1,4,3,1,1,3,2,4,3,3,1,1,1,1,3,3,0,,,,,,,,,,,,,,,,2,3,,5,,7,,9,,11,,,,,2,3,4,5,6,,,9,2,1,,1,,,4,2,,0,
-12760306034,1,4,3,1,4,3,1,1,3,5,2,4,1,1,4,2,4,3,2,2,3,5,5,5,1,5,5,5,4,3,2,3,4,5,5,2,2,2,1,1,3,2,0,,,,,,,,,,,,,,,,,3,4,5,6,7,,,,11,,,,1,2,3,,5,6,,,9,2,1,,,,3,2,14,,17,
\ No newline at end of file
diff --git a/data/TSR_data_labels.xlsx b/data/TSR_data_labels.xlsx
deleted file mode 100644
index 17abd3f..0000000
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diff --git a/data/TSR_data_numbers.xlsx b/data/TSR_data_numbers.xlsx
deleted file mode 100644
index 56597c2..0000000
Binary files a/data/TSR_data_numbers.xlsx and /dev/null differ
diff --git a/data/instrument/TSR Insight Birmingham Theology and RS survey 17th June 2021 penultimate.docx b/data/instrument/TSR Insight Birmingham Theology and RS survey 17th June 2021 penultimate.docx
deleted file mode 100644
index d03cb1d..0000000
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diff --git a/data/instrument/~$R Insight Birmingham Theology and RS survey 17th June 2021 penultimate.docx b/data/instrument/~$R Insight Birmingham Theology and RS survey 17th June 2021 penultimate.docx
deleted file mode 100644
index 16ca442..0000000
Binary files a/data/instrument/~$R Insight Birmingham Theology and RS survey 17th June 2021 penultimate.docx and /dev/null differ
diff --git a/data/survey_raw_data.xlsx b/data/survey_raw_data.xlsx
deleted file mode 100644
index 56597c2..0000000
Binary files a/data/survey_raw_data.xlsx and /dev/null differ
diff --git a/final_draft.qmd b/final_draft.qmd
index 0a5d221..c9bc0ee 100644
--- a/final_draft.qmd
+++ b/final_draft.qmd
@@ -6,19 +6,19 @@ editor: visual
 ---
 
 ```{r setup}
-library(ggplot2)
-library(usethis)
-library(devtools)
-library(likert)
-library(RColorBrewer)
-library("readxl")
-library(haven)
-library(scales)
-library(tidyverse)
-library(likert)
-library(data.table)
-library(formattable)
-library(corrplot)
+library(here)  |> suppressPackageStartupMessages()
+library(ggplot2)  |> suppressPackageStartupMessages()
+library(usethis)  |> suppressPackageStartupMessages()
+library(devtools)  |> suppressPackageStartupMessages()
+library(likert)  |> suppressPackageStartupMessages()
+library(RColorBrewer)  |> suppressPackageStartupMessages()
+library("readxl")  |> suppressPackageStartupMessages()
+library(haven)  |> suppressPackageStartupMessages()
+library(scales)  |> suppressPackageStartupMessages()
+library(tidyverse)  |> suppressPackageStartupMessages()
+library(data.table)  |> suppressPackageStartupMessages()
+library(formattable)  |> suppressPackageStartupMessages()
+library(corrplot)  |> suppressPackageStartupMessages()
 
 # Set a few color variables to make our table more visually appealing
 customGreen0 = "#DeF7E9"
@@ -26,9 +26,15 @@ customGreen = "#71CA97"
 customRed = "#ff7f7f"
 coul3 <- brewer.pal(3, "RdYlBu") # Using RdYlBu range to generate 3 colour palette
 
-subject_data <- read.csv("./data/Subject data.csv")
-admissions_data <- read_excel("./data/TSR_data_numbers.xlsx", sheet = "Raw data - completes")
-admissions_data_numeric <- read_excel("./data/TSR_data_numbers.xlsx", sheet = "Raw data - completes")
+# Download dataset from zenodo
+if (file.exists(here("data", "survey_raw_data.xlsx")) == FALSE) {
+download.file("https://zenodo.org/records/10673332/files/survey_raw_data.xlsx?download=1", destfile = "data/survey_raw_data.xlsx")
+}
+
+# Read in datasets as dataframes
+admissions_data <- read_excel("./data/survey_raw_data.xlsx", sheet = "Raw data - completes")
+# Preserve a second dataframe as numeric without factoring, for the sake of cor() later
+admissions_data_numeric <- read_excel("./data/survey_raw_data.xlsx", sheet = "Raw data - completes")
 admissions_data_numeric <- select(admissions_data_numeric, -c(Q17_other, Q18_other))
 TSR_data <- read.csv("./data/TSR data complete.csv") # From analysis in 2021
 
@@ -116,6 +122,7 @@ admissions_data$Q17 <- labelled(admissions_data$Q17, c("Arab"=1, "Indian"=2, "Pa
 
 admissions_data$Q18 <- labelled(admissions_data$Q18, c("Agnostic"=1, "Atheist"=2, "Baha'i"=3, "Buddhist"=4, "Christian"=5, "Confucian"=6, "Jain"=7, "Jewish"=8, "Hindu"=9, "Indigenous Traditional Religious"=10, "Muslim"=11, "Pagan"=12, "Shinto"=13, "Sikh"=14, "Spiritual but not religious"=15, "Zoroastrian"=16, "No religion"=17, "Other"=18, "Prefer not to say"=0), label = "What is your religion?")
 ```
+
 ```{r bins and subsetting}
 
 # For Q5 - understanding
@@ -290,8 +297,6 @@ ggplot(admissions_data, aes(factor(Q16))) +
   labs(title = "Respondent Gender Self-Identification Distribution", x = "Gender", y = "") + scale_x_discrete(labels = labels(q16_labels))
 ```
 
-
-
 ```{r ethnicity}
 q17_labels <- c("Arab"=1, "Indian"=2, "Pakistani"=3, "Bangladeshi"=4, "Chinese"=5, "Any other Asian background"=6, "Black - African"=7, "Black - Caribbean"=8, "Any other Black background"=9, "Mixed - White and Black Caribbean"=10, "Mixed - White and Black African"=11, "Mixed - White and Black Asian"=12, "Any other Mixed/Multiple Ethnic background"=13, "White - British"=14, "White - Irish"=15, "Any other White background"=16, "Prefer not to say"=17, "Other"=18)
 
@@ -302,7 +307,6 @@ ggplot(admissions_data, aes(factor(Q17))) +
   theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5), text = element_text(size = 10)) + scale_x_discrete(labels = labels(q17_labels))
 ```
 
-
 ```{r religion}
 
 q18_labels <- c("Agnostic"=1, "Atheist"=2, "Buddhist"=4, "Christian"=5, "Confucian"=6, "Jain"=7, "Jewish"=8, "Hindu"=9, "Muslim"=11, "Pagan"=12, "Shinto"=13, "Sikh"=14, "Spiritual but not religious"=15, "Zoroastrian"=16, "No religion"=17, "Other"=18)
@@ -379,6 +383,7 @@ names(Understanding_data) <- c("Philosophy", "Sociology", "Psychology", "History
 likert_test_understand <- likert(Understanding_data)
 plot(likert_test_understand)
 ```
+
 We've plotted these results as a diverging bar chart centred on neutral responses, so that negative and positive visually diverge in clear ways. The bottom four subjects represent those where respondents were on average, less confident that they understood what study of the subject might involve. It is perhaps not surprising to see that subjects which are universally studied in school like "math," "english" and "history" were considered well-understood. It is interesting to note, however, that while respondents were confident that they knew what "Religious Studies" involved (60% were "strongly agree" or "agree"), these results were inverted (63% and 22%), almost perfectly for "Theology". However, it is important to note that - as we will go on to observe - a lack of understanding did *not* correlate to a lack of interest in studying a subject.
 
 ## Employability prospects
@@ -441,6 +446,7 @@ plot(likert_test_employability)
 # save to png file for reports
 ggsave("figures/employability_likert.png")
 ```
+
 When responding to the question around employability prospects, the responses were as one might expect with public stereotypes around the "value" of study in the humanities conveyed with a sharp drop and quite optimistic assessments of math and science. As we will explore further below, employability does not seem to be strongly correlated to student subject interest. This can be seen with theology, where a Pearson test shows a value of `cor(admissions_data_numeric$Q6_Theology, admissions_data_numeric$Q7_Theology, use = "complete.obs")`, very little correlation between responses on Theology for Q6 and Q7. And indeed, this lack of correlation holds true for almost all categories as a matrix of Pearson correlation coefficients for responses to these two questions. Values closer to +/-1 indicate a strong correlation, whereas values closer to 0 indicate a lack of correlation:
 
 ```{r correlation plot for employability and interest}
@@ -456,7 +462,6 @@ M <- cor(Q6, Q7, use = "complete.obs")
 corrplot(M, method = 'number', number.cex = 0.5, tl.col = "black")  # Displays colorful numbers
 ```
 
-
 ## Interest in subjects
 
 ```{r interest in studying}
@@ -521,6 +526,7 @@ When it came to interest in studying the subject at University, responses were l
 It is also interesting to note that no subject exceeded more than 50% interest among survey responses, indicating that there may be be a single "average student", but a variety of interest profiles or clusters among prospective students and not a clear leader among all respondents. We do find that three of the top four "understood" subjects remain in the upper half. However, it is interesting to note that they shift ordering to some extent, with Psychology as a clear leader. Further still, one of the least understood subjects "sociology" shifts from rank 9 to rank 4 for interest.
 
 We can generate a correlation matrix to assess whether interest in one subject correlated to others:
+
 ```{r subject interest correlation matrix}
 Q6 <- admissions_data_numeric %>%
   select(starts_with("Q6"))
@@ -532,6 +538,7 @@ corrplot(Q6_correlation_matrix, method = "number", type = "upper",
          col = colorRampPalette(c("blue", "red"))(9),
          order = "FPC", hclust.method = "ward.D2")
 ```
+
 We can see that there are several reasonably strong positive correlations and these are all clustered around TRS, ethics and philosophy with the exception of the strong correlation between interest in computer science and math. For interest in theology, the strongest correlations are with interest in religious studies (ρ0.62) ethics (ρ0.60) and philosophy (ρ0.57). For interest in religious studies, the strongest correlations are with interest in the same subjects, albeit with slightly lower correlations: these are theology (ρ0.62), ethics (ρ0.56) and philosophy (ρ0.54).
 
 We will explore further Further research would be helpful in identifying the significance of these associations in the next section. It is interesting to compare the results above subsetting data based on whether a given pupil has or has not taken RE as a GCSE subject. Responses to this question (Q14) were split fairly evenly among our respondents with 493 responding "yes" and 432 "no". The differences here are striking:
@@ -548,7 +555,8 @@ corrplot(Q6_correlation_matrix, method = "number", type = "upper",
          col = colorRampPalette(c("blue", "red"))(9),
          order = "FPC", hclust.method = "ward.D2")
 ```
-One should be careful not to confuse correlation here with causation, as it is possible that the students who self-select to participate in RE GCSE bring a certain orientation, and not necessarily that their coursework alters their understanding of the subject composition. Nonetheless, we note that while some correlations remain relatively stable across the two cohorts, for example, relating philosophy and ethics, the salience of the relationship between several subjects for this subset of respondents loosens substantially. This includes the relationship between interest in religious studies and theology which drops to ) as well as theology and ethics (). 
+
+One should be careful not to confuse correlation here with causation, as it is possible that the students who self-select to participate in RE GCSE bring a certain orientation, and not necessarily that their coursework alters their understanding of the subject composition. Nonetheless, we note that while some correlations remain relatively stable across the two cohorts, for example, relating philosophy and ethics, the salience of the relationship between several subjects for this subset of respondents loosens substantially. This includes the relationship between interest in religious studies and theology which drops to ) as well as theology and ethics ().
 
 ```{r}
 Q6_yes_GCSE <- admissions_data_numeric %>%
@@ -562,7 +570,8 @@ corrplot(Q6_correlation_matrix, method = "number", type = "upper",
          col = colorRampPalette(c("blue", "red"))(9),
          order = "FPC", hclust.method = "ward.D2")
 ```
-Looking at the subset of pupils who indicate they have taken RE GCSE, there emerge some novel correlations, between theology and 
+
+Looking at the subset of pupils who indicate they have taken RE GCSE, there emerge some novel correlations, between theology and
 
 We can also analyse for the strength of correlations for students who identify as religious.
 
@@ -585,41 +594,15 @@ We also asked respondents to indicate what they think the study of theology and
 
 Responses to the question about what "a theology degree would include" were as follows:
 
-Philosophy - 74%
-Ethics - 70%
-History - 48%
-Literature - 42%
-Textual studies - 40%
-Sociology - 37%
-Psychology - 26%
-Politics - 24%
-Law - 20%
-Arts - 18%
-Archaeology - 18%
-Science - 13%
-Economics - 4%
+Philosophy - 74% Ethics - 70% History - 48% Literature - 42% Textual studies - 40% Sociology - 37% Psychology - 26% Politics - 24% Law - 20% Arts - 18% Archaeology - 18% Science - 13% Economics - 4%
 
 Responses to what respondents thought a "religious studies degree would include" varied slightly:
 
-Ethics - 84%
-Philosophy - 81%
-History - 67%
-Textual studies - 47%
-Literature - 43%
-Sociology - 42%
-Politics - 34%
-Law - 26%
-Psychology - 22%
-Arts - 17%
-Archaeology - 16%
-Science - 15%
-Economics - 4%
-
+Ethics - 84% Philosophy - 81% History - 67% Textual studies - 47% Literature - 43% Sociology - 42% Politics - 34% Law - 26% Psychology - 22% Arts - 17% Archaeology - 16% Science - 15% Economics - 4%
 
 ```{r}
 ```
 
-
 # Analysis
 
 ## Situating interest data
@@ -628,7 +611,7 @@ Particularly with respect to the TRS focus of this study, it is important to emp
 
 ## Comparing Theology and Religious Studies
 
-For the sake of this analysis, we are particularly interested in the similar responses for religious studies and theology. In spite of sharp differences in how well the cohort thought they understood the subjects, they achieve a very similar rank for interest. Subsetting the responses also reveals some surprising trends in the data. 
+For the sake of this analysis, we are particularly interested in the similar responses for religious studies and theology. In spite of sharp differences in how well the cohort thought they understood the subjects, they achieve a very similar rank for interest. Subsetting the responses also reveals some surprising trends in the data.
 
 There were a number of asymmetrical responses with 43 respondents marking Agree or Strongly Agree in one column and Disagree or Strongly Disagree in the other. In this case, around 21% (25 total of 116) of positive responses to this question on "Religious Studies" as a subject had a dichotomous, or confidently negative sentiment with regard to studying "Theology". Similarly, around 22% (24 total of 107) of positive responses to this question on "Theology" had a confidently negative response with regard to "Religious Studies". However, in all cases where a respondent marked that they "Strongly Agree" with regard to the study of theology they had a positive or ambiguous ("Neither/Nor" or "Prefer not to answer") response to Religious Studies. The opposite ("Strongly Agree" on "Religious Studies" and a negative sentiment towards "Theology") was only the case for 7 responses out of a total of nearly 1000. We take this to indicate that sentiments towards theology and religious studies do not dichotomise in straight-forward ways. Many of our respondents had overlapping, if asymetrical interest in both. We would recommend further qualitative research to develop some more nuanced and in-depth tests for the perceptions of prospective University students towards these two themes alongside others such as "spirituality" or specific religious traditions (e.g. Islam, Judaism, Sikhism, etc.).
 
@@ -640,7 +623,7 @@ Only 7% of students who took the survey indicated "Yes" to the question "Are you
 
 Positive sentiments also did not correlate in significant ways to participation in an organised religion. When data was filtered to select students who marked "Agnostic", "Atheist", " Spiritual but not religious" or "No Religion", the proportion of students who indicated participation/intention to participate in A-Level RS did not change, nor was there a significant overall change to the proportion of students who marked "Agree" or "Strongly Agree" to the statement "I would be interested in studying this subject at University".
 
-Negative responses for "theology" do not correlate in easily perceptible ways to religious identity. Prospective students who marked "Atheist" (68%) and "No religion" (77%) were likely to indicate disagreement, but so were Hindu (71%), Muslim (65%) and Pagan (71%) students. Lower, but still significant Disagree/Strongly Disagree responses were also the case for "Spiritual but not religious" (53%), "Christian" (55%) and "Agnostic" (55%) students. 
+Negative responses for "theology" do not correlate in easily perceptible ways to religious identity. Prospective students who marked "Atheist" (68%) and "No religion" (77%) were likely to indicate disagreement, but so were Hindu (71%), Muslim (65%) and Pagan (71%) students. Lower, but still significant Disagree/Strongly Disagree responses were also the case for "Spiritual but not religious" (53%), "Christian" (55%) and "Agnostic" (55%) students.
 
 ```{r}
 Q5_religious_cor_matrix <- cor(admissions_data_numeric[, grep("^Q5", colnames(admissions_data_numeric))], admissions_data_numeric$religion_bin, use = "complete.obs")
@@ -657,7 +640,7 @@ str(Q6_religious_cor_matrix)
 
 ## Some observations regarding mystique
 
-It was particularly interesting to note that there is positive interest in studying Theology in spite of the lack of understanding of what that study involves. Further research would be necessary to judge the meaning of this discovery, e.g. whether interest numbers would be increased, unaffected or lessened if the level of "unknowing" or conversely the "mystique" of the subject were reduced. For the sake of this study, we can explore the data to a certain extent in an attempt to ascertain whether the "mystique" factor is significant. 
+It was particularly interesting to note that there is positive interest in studying Theology in spite of the lack of understanding of what that study involves. Further research would be necessary to judge the meaning of this discovery, e.g. whether interest numbers would be increased, unaffected or lessened if the level of "unknowing" or conversely the "mystique" of the subject were reduced. For the sake of this study, we can explore the data to a certain extent in an attempt to ascertain whether the "mystique" factor is significant.
 
 If we look at the responses to Q6 around interest in studying the subject, we find that the mean response by respondents who indicated that they did not understand what the subject involved was `mean(admissions_data$Q6_Theology[admissions_data$understanding_theology_bin == "high"], na.rm = TRUE)`. Bearing in mind that higher response codes in this dataset indicated a more negative response (strongly disagree was coded as 5 whereas strongly agree was coded as 1), we find that the sentiment shifts towards the negative for higher levels of perceived understanding, with a mean interest value of `mean(admissions_data$Q6_Theology[admissions_data$understanding_theology_bin == "neutral"], na.rm = TRUE)` for neutral responses on understanding and a mean interest value of `mean(admissions_data$Q6_Theology[admissions_data$understanding_theology_bin == "low"], na.rm = TRUE)` for low levels of understanding. We use the term "mystique effect" to refer to this pattern where the more a student thinks they understand the subject, the less interested they are in studying it. The same pattern holds true for interest in religious studies, with a mean interest score for high levels of understanding result. We believe that this effect should be observed with some caution, given that the correlations between understanding and interest are low for nearly all except for some outlier categories. This can be seen in a matrix of Pearson correlation coefficients for all responses to these two questions. Values closer to +/-1 indicate a strong correlation, whereas values closer to 0 indicate a lack of correlation:
 
@@ -670,6 +653,7 @@ Q6 <- admissions_data_numeric %>%
 M <- cor(Q6, Q5, use = "complete.obs")
 corrplot(M, method = 'number', number.cex = 0.5, tl.col = "black")  # Displays colorful numbers
 ```
+
 Here, the least weak correlation (between interest and understanding of computer science) is just over 0.5, and even this correlation should be considered weak at best.
 
 ```{r}
@@ -683,9 +667,6 @@ admissions_data[understanding_theology_bin == "high", mean(Q6_Theology, na.rm =
 
 ```
 
-
-
-
 ```{r}
 q6 <- c(data1[18:29])
 q7 <- c(data1[29:40])
@@ -695,5 +676,4 @@ q12 <- c(data1[71:80])
 
 ```
 
-
 # Appendix A: Instrument
diff --git a/final_draft.tex b/final_draft.tex
deleted file mode 100644
index 1cfcacb..0000000
--- a/final_draft.tex
+++ /dev/null
@@ -1,641 +0,0 @@
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-\CommentTok{\# Define colour palettes for plots below}
-\NormalTok{coul3 }\OtherTok{\textless{}{-}} \FunctionTok{brewer.pal}\NormalTok{(}\DecValTok{3}\NormalTok{, }\StringTok{"RdYlBu"}\NormalTok{) }\CommentTok{\# Using RdYlBu range to generate 3 colour palette: https://colorbrewer2.org/\#type=diverging\&scheme=RdYlBu\&n=5}
-
-\NormalTok{subject\_data }\OtherTok{\textless{}{-}} \FunctionTok{read.csv}\NormalTok{(}\StringTok{"./data/Subject data.csv"}\NormalTok{)}
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}} \FunctionTok{read\_excel}\NormalTok{(}\StringTok{"./data/TSR\_data\_numbers.xlsx"}\NormalTok{, }\AttributeTok{sheet =} \StringTok{"Raw data {-} completes"}\NormalTok{)}
-
-\CommentTok{\# Set up local workspace, as needed:}
-
-\ControlFlowTok{if}\NormalTok{ (}\FunctionTok{dir.exists}\NormalTok{(}\StringTok{"data"}\NormalTok{) }\SpecialCharTok{==} \ConstantTok{FALSE}\NormalTok{) \{}
-  \FunctionTok{dir.create}\NormalTok{(}\StringTok{"data"}\NormalTok{) }
-\NormalTok{\}}
-
-\CommentTok{\# These paths are excluded from github as it is best practice for end{-}user to generate their own}
-
-\ControlFlowTok{if}\NormalTok{ (}\FunctionTok{dir.exists}\NormalTok{(}\StringTok{"figures"}\NormalTok{) }\SpecialCharTok{==} \ConstantTok{FALSE}\NormalTok{) \{}
-  \FunctionTok{dir.create}\NormalTok{(}\StringTok{"figures"}\NormalTok{) }
-\NormalTok{\}}
-\ControlFlowTok{if}\NormalTok{ (}\FunctionTok{dir.exists}\NormalTok{(}\StringTok{"derivedData"}\NormalTok{) }\SpecialCharTok{==} \ConstantTok{FALSE}\NormalTok{) \{}
-  \FunctionTok{dir.create}\NormalTok{(}\StringTok{"derivedData"}\NormalTok{)}
-\NormalTok{\}}
-
-\CommentTok{\# Refactor data}
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q2 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q2, }\FunctionTok{c}\NormalTok{(}\StringTok{"15 or under"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"16"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"17"} \OtherTok{=} \DecValTok{3}\NormalTok{, }\StringTok{"18"} \OtherTok{=} \DecValTok{4}\NormalTok{, }\StringTok{"19"} \OtherTok{=} \DecValTok{5}\NormalTok{, }\StringTok{"20"} \OtherTok{=} \DecValTok{6}\NormalTok{, }\StringTok{"21 or over"} \OtherTok{=} \DecValTok{7}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{8}\NormalTok{), }\AttributeTok{label =} \StringTok{"How old are you?"}\NormalTok{)}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q3 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q3, }\FunctionTok{c}\NormalTok{(}\StringTok{"Year 11/S4/Year 12(NI)"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"Year 12/S5/Year 13(NI)"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"Year 13/S6/Year 14(NI)"} \OtherTok{=} \DecValTok{3}\NormalTok{, }\StringTok{"I am currently on a gap year"} \OtherTok{=} \DecValTok{4}\NormalTok{, }\StringTok{"I am currently on an undergraduate/HE college course"} \OtherTok{=} \DecValTok{5}\NormalTok{, }\StringTok{"I am in full{-}time employment"} \OtherTok{=} \DecValTok{6}\NormalTok{, }\StringTok{"I am unemployed"} \OtherTok{=} \DecValTok{7}\NormalTok{, }\StringTok{"Other"} \OtherTok{=} \DecValTok{8}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{9}\NormalTok{), }\AttributeTok{label =} \StringTok{"Which of the following best describes your MOST RECENT year of study?"}\NormalTok{)}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q4 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q4, }\FunctionTok{c}\NormalTok{(}\StringTok{"Yes, definitely"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"Yes, probably"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"I haven’t ruled it out"} \OtherTok{=} \DecValTok{3}\NormalTok{), }\AttributeTok{label =} \StringTok{"Are you considering or planning to go to university in the future?"}\NormalTok{)}
-
-\NormalTok{common\_labels }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}
-  \StringTok{"Strongly agree"} \OtherTok{=} \DecValTok{1}\NormalTok{,}
-  \StringTok{"Agree"} \OtherTok{=} \DecValTok{2}\NormalTok{,}
-  \StringTok{"Neither/Nor"} \OtherTok{=} \DecValTok{3}\NormalTok{,}
-  \StringTok{"Disagree"} \OtherTok{=} \DecValTok{4}\NormalTok{,}
-  \StringTok{"Strongly disagree"} \OtherTok{=} \DecValTok{5}\NormalTok{,}
-  \StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}
-\NormalTok{)}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q5\_"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels, }\AttributeTok{label =} \StringTok{"I have a good understanding of what this subject involves"}\NormalTok{))}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q6\_"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels, }\AttributeTok{label =} \StringTok{"I would be interested in studying this subject at University"}\NormalTok{))}
-
-\NormalTok{common\_labels2 }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}
-  \StringTok{"Good employability prospects"} \OtherTok{=} \DecValTok{1}\NormalTok{,}
-  \AttributeTok{NULL =} \DecValTok{2}\NormalTok{,}
-  \AttributeTok{NULL =} \DecValTok{3}\NormalTok{,}
-  \AttributeTok{NULL =} \DecValTok{4}\NormalTok{,}
-  \StringTok{"Poor employability prospects"} \OtherTok{=} \DecValTok{5}\NormalTok{,}
-  \StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}
-\NormalTok{)}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q7\_"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels2, }\AttributeTok{label =} \StringTok{"This subject has… employability prospects"}\NormalTok{))}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q8 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q8, }\FunctionTok{c}\NormalTok{(}\StringTok{"Theology is a subject for religious people"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\AttributeTok{NULL =} \DecValTok{2}\NormalTok{, }\AttributeTok{NULL =} \DecValTok{3}\NormalTok{, }\AttributeTok{NULL =} \DecValTok{4}\NormalTok{, }\StringTok{"Theology is a subject for religious and non{-}religious people"} \OtherTok{=} \DecValTok{5}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}\NormalTok{), }\AttributeTok{label =} \StringTok{"Thinking about Theology, please select an option on the scale from 1 to 5 which best represents your opinion"}\NormalTok{)}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q9 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q9, }\FunctionTok{c}\NormalTok{(}\StringTok{"Religion is a subject for religious people"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\AttributeTok{NULL =} \DecValTok{2}\NormalTok{, }\AttributeTok{NULL =} \DecValTok{3}\NormalTok{, }\AttributeTok{NULL =} \DecValTok{4}\NormalTok{, }\StringTok{"Religion is a subject for religious and non{-}religious people"} \OtherTok{=} \DecValTok{5}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}\NormalTok{), }\AttributeTok{label =} \StringTok{"Thinking about Religion, please select an option on the scale from 1 to 5 which best represents your opinion"}\NormalTok{)}
-
-\NormalTok{common\_labels3 }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}
-  \StringTok{"Psychology"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"Arts"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"Sociology"} \OtherTok{=} \DecValTok{3}\NormalTok{, }\StringTok{"Politics"} \OtherTok{=} \DecValTok{4}\NormalTok{, }\StringTok{"History"} \OtherTok{=} \DecValTok{5}\NormalTok{, }\StringTok{"Philosophy"} \OtherTok{=} \DecValTok{6}\NormalTok{, }\StringTok{"Ethics"} \OtherTok{=} \DecValTok{7}\NormalTok{, }\StringTok{"Archaeology"} \OtherTok{=} \DecValTok{8}\NormalTok{, }\StringTok{"Textual studies"} \OtherTok{=} \DecValTok{9}\NormalTok{, }\StringTok{"Literature"} \OtherTok{=} \DecValTok{10}\NormalTok{, }\StringTok{"Law"} \OtherTok{=} \DecValTok{11}\NormalTok{, }\StringTok{"Economics"} \OtherTok{=} \DecValTok{12}\NormalTok{, }\StringTok{"Science"} \OtherTok{=} \DecValTok{13}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}\NormalTok{)}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q10\_"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels3, }\AttributeTok{label =} \StringTok{"I think that a theology degree would include..."}\NormalTok{))}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q11\_"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels3, }\AttributeTok{label =} \StringTok{"I think that a religious studies degree would include..."}\NormalTok{))}
-
-\NormalTok{common\_labels4 }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}
-  \StringTok{"Politics"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"History"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"Ethics"} \OtherTok{=} \DecValTok{3}\NormalTok{, }\StringTok{"Theology"} \OtherTok{=} \DecValTok{4}\NormalTok{, }\StringTok{"Religion"} \OtherTok{=} \DecValTok{5}\NormalTok{, }\StringTok{"Law"} \OtherTok{=} \DecValTok{6}\NormalTok{, }\StringTok{"Economics"} \OtherTok{=} \DecValTok{7}\NormalTok{, }\StringTok{"Maths"} \OtherTok{=} \DecValTok{8}\NormalTok{, }\StringTok{"Logic"} \OtherTok{=} \DecValTok{9}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}\NormalTok{)}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q12\_"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels4, }\AttributeTok{label =} \StringTok{"I think that a philosophy degree would include..."}\NormalTok{))}
-
-\NormalTok{common\_labels5 }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"Yes"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"No"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"Prefer not to say"} \OtherTok{=} \DecValTok{0}\NormalTok{)}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q13"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels5, }\AttributeTok{label =} \StringTok{"Are you currently studying A level Religious Studies, or intending to?"}\NormalTok{))}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate\_at}\NormalTok{(}\FunctionTok{vars}\NormalTok{(}\FunctionTok{starts\_with}\NormalTok{(}\StringTok{"Q14"}\NormalTok{)), }\SpecialCharTok{\textasciitilde{}} \FunctionTok{labelled}\NormalTok{(., common\_labels5, }\AttributeTok{label =} \StringTok{"Are you studying or did you previously study GCSE Religious Studies?"}\NormalTok{))}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q16 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q16, }\FunctionTok{c}\NormalTok{(}\StringTok{"Male"}\OtherTok{=}\DecValTok{1}\NormalTok{, }\StringTok{"Female"}\OtherTok{=}\DecValTok{2}\NormalTok{, }\StringTok{"I identify my gender in another way"}\OtherTok{=}\DecValTok{3}\NormalTok{, }\StringTok{"Prefer not to say"}\OtherTok{=}\DecValTok{4}\NormalTok{), }\AttributeTok{label =} \StringTok{"I identify my gender as…"}\NormalTok{)}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q17 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q17, }\FunctionTok{c}\NormalTok{(}\StringTok{"Arab"}\OtherTok{=}\DecValTok{1}\NormalTok{, }\StringTok{"Indian"}\OtherTok{=}\DecValTok{2}\NormalTok{, }\StringTok{"Pakistani"}\OtherTok{=}\DecValTok{3}\NormalTok{, }\StringTok{"Bangladeshi"}\OtherTok{=}\DecValTok{4}\NormalTok{, }\StringTok{"Chinese"}\OtherTok{=}\DecValTok{5}\NormalTok{, }\StringTok{"Any other Asian background"}\OtherTok{=}\DecValTok{6}\NormalTok{, }\StringTok{"Black {-} African"}\OtherTok{=}\DecValTok{7}\NormalTok{, }\StringTok{"Black {-} Caribbean"}\OtherTok{=}\DecValTok{8}\NormalTok{, }\StringTok{"Any other Black background"}\OtherTok{=}\DecValTok{9}\NormalTok{, }\StringTok{"Mixed {-} White and Black Caribbean"}\OtherTok{=}\DecValTok{10}\NormalTok{, }\StringTok{"Mixed {-} White and Black African"}\OtherTok{=}\DecValTok{11}\NormalTok{, }\StringTok{"Mixed {-} White and Black Asian"}\OtherTok{=}\DecValTok{12}\NormalTok{, }\StringTok{"Any other Mixed/Multiple Ethnic background"}\OtherTok{=}\DecValTok{13}\NormalTok{, }\StringTok{"White {-} British"}\OtherTok{=}\DecValTok{14}\NormalTok{, }\StringTok{"White {-} Irish"}\OtherTok{=}\DecValTok{15}\NormalTok{, }\StringTok{"Gypsy or Irish Traveller"}\OtherTok{=}\DecValTok{16}\NormalTok{, }\StringTok{"Any other White background"}\OtherTok{=}\DecValTok{17}\NormalTok{, }\StringTok{"Other"}\OtherTok{=}\DecValTok{18}\NormalTok{, }\StringTok{"Prefer not to say"}\OtherTok{=}\DecValTok{0}\NormalTok{), }\AttributeTok{label =} \StringTok{"What is your ethnic group?"}\NormalTok{)}
-
-\NormalTok{admissions\_data}\SpecialCharTok{$}\NormalTok{Q18 }\OtherTok{\textless{}{-}} \FunctionTok{labelled}\NormalTok{(admissions\_data}\SpecialCharTok{$}\NormalTok{Q18, }\FunctionTok{c}\NormalTok{(}\StringTok{"Agnostic"}\OtherTok{=}\DecValTok{1}\NormalTok{, }\StringTok{"Atheist"}\OtherTok{=}\DecValTok{2}\NormalTok{, }\StringTok{"Baha\textquotesingle{}i"}\OtherTok{=}\DecValTok{3}\NormalTok{, }\StringTok{"Buddhist"}\OtherTok{=}\DecValTok{4}\NormalTok{, }\StringTok{"Christian"}\OtherTok{=}\DecValTok{5}\NormalTok{, }\StringTok{"Confucian"}\OtherTok{=}\DecValTok{6}\NormalTok{, }\StringTok{"Jain"}\OtherTok{=}\DecValTok{7}\NormalTok{, }\StringTok{"Jewish"}\OtherTok{=}\DecValTok{8}\NormalTok{, }\StringTok{"Hindu"}\OtherTok{=}\DecValTok{9}\NormalTok{, }\StringTok{"Indigenous Traditional Religious"}\OtherTok{=}\DecValTok{10}\NormalTok{, }\StringTok{"Muslim"}\OtherTok{=}\DecValTok{11}\NormalTok{, }\StringTok{"Pagan"}\OtherTok{=}\DecValTok{12}\NormalTok{, }\StringTok{"Shinto"}\OtherTok{=}\DecValTok{13}\NormalTok{, }\StringTok{"Sikh"}\OtherTok{=}\DecValTok{14}\NormalTok{, }\StringTok{"Spiritual but not religious"}\OtherTok{=}\DecValTok{15}\NormalTok{, }\StringTok{"Zoroastrian"}\OtherTok{=}\DecValTok{16}\NormalTok{, }\StringTok{"No religion"}\OtherTok{=}\DecValTok{17}\NormalTok{, }\StringTok{"Other"}\OtherTok{=}\DecValTok{18}\NormalTok{, }\StringTok{"Prefer not to say"}\OtherTok{=}\DecValTok{0}\NormalTok{), }\AttributeTok{label =} \StringTok{"What is your religion?"}\NormalTok{)}
-
-\CommentTok{\# Create bins:}
-
-\CommentTok{\# For Q5 {-} understanding}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q5\_Theology =} \FunctionTok{ifelse}\NormalTok{(Q5\_Theology }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q5\_Theology),}
-    \AttributeTok{understanding\_theology\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q5\_Theology }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"high"}\NormalTok{,}
-\NormalTok{      Q5\_Theology }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"low"}\NormalTok{,}
-\NormalTok{      Q5\_Theology }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"low"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"high"}\NormalTok{))}
-\NormalTok{  )}
-\CommentTok{\# For Q5 {-} understanding}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q5\_Religious\_Studies =} \FunctionTok{ifelse}\NormalTok{(Q5\_Religious\_Studies }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q5\_Religious\_Studies),}
-    \AttributeTok{understanding\_religion\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q5\_Religious\_Studies }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"high"}\NormalTok{,}
-\NormalTok{      Q5\_Religious\_Studies }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"low"}\NormalTok{,}
-\NormalTok{      Q5\_Religious\_Studies }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"low"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"high"}\NormalTok{))}
-\NormalTok{  )}
-\CommentTok{\# For Q6 {-} interest}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q6\_Theology =} \FunctionTok{ifelse}\NormalTok{(Q6\_Theology }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q6\_Theology),}
-    \AttributeTok{interest\_theology\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q6\_Theology }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"high"}\NormalTok{,}
-\NormalTok{      Q6\_Theology }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"low"}\NormalTok{,}
-\NormalTok{      Q6\_Theology }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"low"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"high"}\NormalTok{))}
-\NormalTok{  )}
-
-\CommentTok{\# For Q6 {-} interest}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q6\_Religious\_Studies =} \FunctionTok{ifelse}\NormalTok{(Q6\_Religious\_Studies }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q6\_Religious\_Studies),}
-    \AttributeTok{interest\_religion\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q6\_Religious\_Studies }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"high"}\NormalTok{,}
-\NormalTok{      Q6\_Religious\_Studies }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"low"}\NormalTok{,}
-\NormalTok{      Q6\_Religious\_Studies }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"low"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"high"}\NormalTok{))}
-\NormalTok{  )}
-
-\CommentTok{\# For Q7 {-} employability prospects}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q7\_Theology =} \FunctionTok{ifelse}\NormalTok{(Q7\_Theology }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q7\_Theology),}
-    \AttributeTok{employability\_optimism\_theology\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q7\_Theology }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"high"}\NormalTok{,}
-\NormalTok{      Q7\_Theology }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"low"}\NormalTok{,}
-\NormalTok{      Q7\_Theology }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"low"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"high"}\NormalTok{))}
-\NormalTok{  )}
-
-\CommentTok{\# For Q7 {-} employability prospects}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q7\_Religious\_Studies =} \FunctionTok{ifelse}\NormalTok{(Q7\_Religious\_Studies }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q7\_Religious\_Studies),}
-    \AttributeTok{employability\_optimism\_religion\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q7\_Religious\_Studies }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"high"}\NormalTok{,}
-\NormalTok{      Q7\_Religious\_Studies }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"low"}\NormalTok{,}
-\NormalTok{      Q7\_Religious\_Studies }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"low"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"high"}\NormalTok{))}
-\NormalTok{  )}
-
-\CommentTok{\# For Q8 {-} employability prospects}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q8 =} \FunctionTok{ifelse}\NormalTok{(Q8 }\SpecialCharTok{==} \DecValTok{6}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q8),}
-    \AttributeTok{theology\_for\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q8 }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"religious"}\NormalTok{,}
-\NormalTok{      Q8 }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"all\_people"}\NormalTok{,}
-\NormalTok{      Q8 }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"all\_people"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"religious"}\NormalTok{))}
-\NormalTok{  )}
-
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q9 =} \FunctionTok{ifelse}\NormalTok{(Q9 }\SpecialCharTok{==} \DecValTok{6}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q9),}
-    \AttributeTok{religion\_for\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q9 }\SpecialCharTok{\textless{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"religious"}\NormalTok{,}
-\NormalTok{      Q9 }\SpecialCharTok{\textgreater{}} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"all\_people"}\NormalTok{,}
-\NormalTok{      Q9 }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"neutral"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"all\_people"}\NormalTok{, }\StringTok{"neutral"}\NormalTok{, }\StringTok{"religious"}\NormalTok{))}
-\NormalTok{  )}
-
-\CommentTok{\# Q17 non{-}white / white ethnicity bins}
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-    \AttributeTok{Q17 =} \FunctionTok{ifelse}\NormalTok{(Q17 }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q17),}
-    \AttributeTok{ethnicity\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q17 }\SpecialCharTok{\textgreater{}} \DecValTok{13} \SpecialCharTok{|}\NormalTok{ Q17 }\SpecialCharTok{\textless{}} \DecValTok{18} \SpecialCharTok{\textasciitilde{}} \StringTok{"white"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"non{-}white"}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"white"}\NormalTok{, }\StringTok{"non{-}white"}\NormalTok{))}
-\NormalTok{  )}
-
-\CommentTok{\# Q18 non{-}religious / institutioal bins}
-\NormalTok{admissions\_data }\OtherTok{\textless{}{-}}\NormalTok{ admissions\_data }\SpecialCharTok{\%\textgreater{}\%}
-  \FunctionTok{mutate}\NormalTok{(}
-      \AttributeTok{Q18 =} \FunctionTok{ifelse}\NormalTok{(Q18 }\SpecialCharTok{==} \DecValTok{0}\NormalTok{, }\ConstantTok{NA}\NormalTok{, Q18),}
-      \AttributeTok{religion\_bin =} \FunctionTok{case\_when}\NormalTok{(}
-\NormalTok{      Q18 }\SpecialCharTok{\%in\%} \FunctionTok{c}\NormalTok{(}\DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{5}\NormalTok{, }\DecValTok{17}\NormalTok{) }\SpecialCharTok{\textasciitilde{}} \StringTok{"non{-}religious"}\NormalTok{,}
-      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"religious"}
-\NormalTok{    ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{factor}\NormalTok{(}\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"non{-}religious"}\NormalTok{, }\StringTok{"religious"}\NormalTok{))}
-\NormalTok{  )}
-\end{Highlighting}
-\end{Shaded}
-
-\hypertarget{introduction}{%
-\subsection{Introduction}\label{introduction}}
-
-Opening about UG admissions scenario.
-
-At the same time that there is increasing pressure on admissions, it is
-also the case that in the particular case of theology and religious
-studies, public perceptions and framings of religion are shifting in
-significant ways. Pointing to a variety of phenomena, like vicarious
-religion, everyday religion, the increasing interest in spirituality and
-new religious movements, scholars have suggested that we are operatign
-in a new post-secular social landscape, which is not less religious, as
-secularisation theorists might have expected, but differently religious.
-Research into youth and religion has shown that this phenomena works out
-in the same ways for young people as it does for adults.
-
-Working off the expectation that people are interfacing with theology
-and religion in different ways, we sought to explore in this study how
-this might inflect undergraduate admissions in Theology and Religious
-Studies (``TRS'') programmes. We theorised that young people in the UK
-aged 16 - 18 might actually be interested in studying this topic, but
-that their interests might have shifted into differently framed
-definitions and expectations from previous generations. Gathering this
-knowledge will be crucial for faculty involved in designing academic
-programmes and UG recruitment in TRS, especially as there is a broader
-government push to shift enrollments for students from the humanities to
-STEM subjects.
-
-For this research, we conducted a survey of prospective undergraduate
-students in the UK, aged 16-19. The survey instrument (Appendix A) was
-designed by Paul Ashby and Jeremy Kidwell at the University of
-Birmingham, with helpful critical input from other colleagues at
-Birminngham: Amy Daughton, Jagbir Jhutti-Johal, Carissa Sharp, Rachael
-Shillitoe, and Karen Wenell. Survey data was collected via online survey
-using Qualtrics by TSR Insight and delivered to members of the online
-platform ``The Student Room'' which was open from 21st June and 4th July
-2021. The resulting dataset is a random sample of 933 complete survey
-results from UK students (aged 16-18) in years 11, 12 and 13.
-
-Responses were anonymous, and respondents were informed of the survey
-purposes and asked to indicate if they were happy to participate in the
-survey.
-
-There were three additional sifting questions: (1) we asked respondents
-their age, with results from ``15 and under'' and ``prefer not to say''
-excluded and (2) we asked students about their most recent year of
-study, with responses that were not Y11-Y13 excluded. These included ``I
-am currently on a gap year,'' ``I am currently on an undergraduate / HE
-college course,'' ``I am in full-time employment'' (readers can find the
-full list of excluded response categories in Appendix A). The final
-sifting question asked respondents ``Are you considering or planning to
-go to university in the future?'' and responses of ``no'' or ``prefer
-not to say'' were excluded. The resulting sample only included
-respondents who reported themselves as pupils in school aged 16-19 who
-were considering going to University in the future.
-
-\hypertarget{demographics}{%
-\section{Demographics}\label{demographics}}
-
-The sample was distributed evenly across the age cohorts with around 300
-responses from each category:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{q2\_labels }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"16"} \OtherTok{=} \DecValTok{1}\NormalTok{, }\StringTok{"17"} \OtherTok{=} \DecValTok{2}\NormalTok{, }\StringTok{"18"} \OtherTok{=} \DecValTok{3}\NormalTok{, }\StringTok{"19"} \OtherTok{=} \DecValTok{4}\NormalTok{)}
-
-\FunctionTok{ggplot}\NormalTok{(admissions\_data, }\FunctionTok{aes}\NormalTok{(}\FunctionTok{factor}\NormalTok{(Q2))) }\SpecialCharTok{+} 
-  \FunctionTok{geom\_bar}\NormalTok{() }\SpecialCharTok{+}
-  \FunctionTok{geom\_text}\NormalTok{(}\AttributeTok{stat =} \StringTok{"count"}\NormalTok{, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{label =} \FunctionTok{after\_stat}\NormalTok{(count)), }\AttributeTok{vjust =} \SpecialCharTok{{-}}\FloatTok{0.5}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{labs}\NormalTok{(}\AttributeTok{title =} \StringTok{"Respondent Age Distribution"}\NormalTok{, }\AttributeTok{x =} \StringTok{"Age"}\NormalTok{, }\AttributeTok{y =} \StringTok{""}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{scale\_x\_discrete}\NormalTok{(}\AttributeTok{labels =} \FunctionTok{labels}\NormalTok{(q2\_labels))}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{figure}[H]
-
-{\centering \includegraphics{final_draft_files/figure-pdf/age-1.pdf}
-
-}
-
-\end{figure}
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\CommentTok{\# save to png file for reports}
-\FunctionTok{ggsave}\NormalTok{(}\StringTok{"figures/admissions\_data\_summaries\_age.png"}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{verbatim}
-Saving 5.5 x 3.5 in image
-\end{verbatim}
-
-We also asked respondents to self-identify their gender, ethnic group
-and religion. Distribution across these categories was as follows:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{q16\_labels }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"Male"}\OtherTok{=}\DecValTok{1}\NormalTok{, }\StringTok{"Female"}\OtherTok{=}\DecValTok{2}\NormalTok{, }\StringTok{"I identify my gender in another way"}\OtherTok{=}\DecValTok{3}\NormalTok{, }\StringTok{"Prefer not to say"}\OtherTok{=}\DecValTok{4}\NormalTok{)}
-
-\FunctionTok{ggplot}\NormalTok{(admissions\_data, }\FunctionTok{aes}\NormalTok{(}\FunctionTok{factor}\NormalTok{(Q16))) }\SpecialCharTok{+} 
-  \FunctionTok{geom\_bar}\NormalTok{() }\SpecialCharTok{+}
-  \FunctionTok{geom\_text}\NormalTok{(}\AttributeTok{stat =} \StringTok{"count"}\NormalTok{, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{label =} \FunctionTok{after\_stat}\NormalTok{(count)), }\AttributeTok{vjust =} \SpecialCharTok{{-}}\FloatTok{0.5}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{labs}\NormalTok{(}\AttributeTok{title =} \StringTok{"Respondent Gender Self{-}Identification Distribution"}\NormalTok{, }\AttributeTok{x =} \StringTok{"Gender"}\NormalTok{, }\AttributeTok{y =} \StringTok{""}\NormalTok{) }\SpecialCharTok{+} \FunctionTok{scale\_x\_discrete}\NormalTok{(}\AttributeTok{labels =} \FunctionTok{labels}\NormalTok{(q16\_labels))}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{figure}[H]
-
-{\centering \includegraphics{final_draft_files/figure-pdf/gender-1.pdf}
-
-}
-
-\end{figure}
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{q17\_labels }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"Arab"}\OtherTok{=}\DecValTok{1}\NormalTok{, }\StringTok{"Indian"}\OtherTok{=}\DecValTok{2}\NormalTok{, }\StringTok{"Pakistani"}\OtherTok{=}\DecValTok{3}\NormalTok{, }\StringTok{"Bangladeshi"}\OtherTok{=}\DecValTok{4}\NormalTok{, }\StringTok{"Chinese"}\OtherTok{=}\DecValTok{5}\NormalTok{, }\StringTok{"Any other Asian background"}\OtherTok{=}\DecValTok{6}\NormalTok{, }\StringTok{"Black {-} African"}\OtherTok{=}\DecValTok{7}\NormalTok{, }\StringTok{"Black {-} Caribbean"}\OtherTok{=}\DecValTok{8}\NormalTok{, }\StringTok{"Any other Black background"}\OtherTok{=}\DecValTok{9}\NormalTok{, }\StringTok{"Mixed {-} White and Black Caribbean"}\OtherTok{=}\DecValTok{10}\NormalTok{, }\StringTok{"Mixed {-} White and Black African"}\OtherTok{=}\DecValTok{11}\NormalTok{, }\StringTok{"Mixed {-} White and Black Asian"}\OtherTok{=}\DecValTok{12}\NormalTok{, }\StringTok{"Any other Mixed/Multiple Ethnic background"}\OtherTok{=}\DecValTok{13}\NormalTok{, }\StringTok{"White {-} British"}\OtherTok{=}\DecValTok{14}\NormalTok{, }\StringTok{"White {-} Irish"}\OtherTok{=}\DecValTok{15}\NormalTok{, }\StringTok{"Any other White background"}\OtherTok{=}\DecValTok{16}\NormalTok{, }\StringTok{"Prefer not to say"}\OtherTok{=}\DecValTok{17}\NormalTok{, }\StringTok{"Other"}\OtherTok{=}\DecValTok{18}\NormalTok{)}
-
-\FunctionTok{ggplot}\NormalTok{(admissions\_data, }\FunctionTok{aes}\NormalTok{(}\FunctionTok{factor}\NormalTok{(Q17))) }\SpecialCharTok{+}
-  \FunctionTok{geom\_bar}\NormalTok{(}\AttributeTok{fill =} \StringTok{"darkgreen"}\NormalTok{, }\AttributeTok{stat =} \StringTok{"count"}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{geom\_text}\NormalTok{(}\AttributeTok{stat =} \StringTok{"count"}\NormalTok{, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{label =}\NormalTok{ scales}\SpecialCharTok{::}\FunctionTok{percent}\NormalTok{(}\FunctionTok{after\_stat}\NormalTok{(count }\SpecialCharTok{/} \FunctionTok{sum}\NormalTok{(count)))), }\AttributeTok{vjust =} \SpecialCharTok{{-}}\FloatTok{0.5}\NormalTok{, }\AttributeTok{size=}\FloatTok{2.5}\NormalTok{) }\SpecialCharTok{+}  
-  \FunctionTok{labs}\NormalTok{(}\AttributeTok{title =} \StringTok{"Respondent Ethnicity"}\NormalTok{, }\AttributeTok{x =} \StringTok{"Ethnicity"}\NormalTok{, }\AttributeTok{y =} \StringTok{""}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{theme}\NormalTok{(}\AttributeTok{axis.text.x =} \FunctionTok{element\_text}\NormalTok{(}\AttributeTok{angle =} \DecValTok{90}\NormalTok{, }\AttributeTok{hjust =} \DecValTok{1}\NormalTok{, }\AttributeTok{vjust =} \FloatTok{0.5}\NormalTok{), }\AttributeTok{text =} \FunctionTok{element\_text}\NormalTok{(}\AttributeTok{size =} \DecValTok{10}\NormalTok{)) }\SpecialCharTok{+} \FunctionTok{scale\_x\_discrete}\NormalTok{(}\AttributeTok{labels =} \FunctionTok{labels}\NormalTok{(q17\_labels))}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{figure}[H]
-
-{\centering \includegraphics{final_draft_files/figure-pdf/ethnicity-1.pdf}
-
-}
-
-\end{figure}
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{q18\_labels }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"Agnostic"}\OtherTok{=}\DecValTok{1}\NormalTok{, }\StringTok{"Atheist"}\OtherTok{=}\DecValTok{2}\NormalTok{, }\StringTok{"Buddhist"}\OtherTok{=}\DecValTok{4}\NormalTok{, }\StringTok{"Christian"}\OtherTok{=}\DecValTok{5}\NormalTok{, }\StringTok{"Confucian"}\OtherTok{=}\DecValTok{6}\NormalTok{, }\StringTok{"Jain"}\OtherTok{=}\DecValTok{7}\NormalTok{, }\StringTok{"Jewish"}\OtherTok{=}\DecValTok{8}\NormalTok{, }\StringTok{"Hindu"}\OtherTok{=}\DecValTok{9}\NormalTok{, }\StringTok{"Muslim"}\OtherTok{=}\DecValTok{11}\NormalTok{, }\StringTok{"Pagan"}\OtherTok{=}\DecValTok{12}\NormalTok{, }\StringTok{"Shinto"}\OtherTok{=}\DecValTok{13}\NormalTok{, }\StringTok{"Sikh"}\OtherTok{=}\DecValTok{14}\NormalTok{, }\StringTok{"Spiritual but not religious"}\OtherTok{=}\DecValTok{15}\NormalTok{, }\StringTok{"Zoroastrian"}\OtherTok{=}\DecValTok{16}\NormalTok{, }\StringTok{"No religion"}\OtherTok{=}\DecValTok{17}\NormalTok{, }\StringTok{"Other"}\OtherTok{=}\DecValTok{18}\NormalTok{)}
-
-\FunctionTok{ggplot}\NormalTok{(admissions\_data, }\FunctionTok{aes}\NormalTok{(}\FunctionTok{factor}\NormalTok{(Q18))) }\SpecialCharTok{+}
-  \FunctionTok{geom\_bar}\NormalTok{(}\AttributeTok{fill =} \StringTok{"blue"}\NormalTok{, }\AttributeTok{stat =} \StringTok{"count"}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{geom\_text}\NormalTok{(}\AttributeTok{stat =} \StringTok{"count"}\NormalTok{, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{label =}\NormalTok{ scales}\SpecialCharTok{::}\FunctionTok{percent}\NormalTok{(}\FunctionTok{after\_stat}\NormalTok{(count }\SpecialCharTok{/} \FunctionTok{sum}\NormalTok{(count)))), }\AttributeTok{vjust =} \SpecialCharTok{{-}}\FloatTok{0.5}\NormalTok{, }\AttributeTok{size=}\FloatTok{2.5}\NormalTok{) }\SpecialCharTok{+}  
-  \FunctionTok{labs}\NormalTok{(}\AttributeTok{title =} \StringTok{"Respondent Religion"}\NormalTok{, }\AttributeTok{x =} \StringTok{"Religion"}\NormalTok{, }\AttributeTok{y =} \StringTok{""}\NormalTok{) }\SpecialCharTok{+}
-  \FunctionTok{theme}\NormalTok{(}\AttributeTok{axis.text.x =} \FunctionTok{element\_text}\NormalTok{(}\AttributeTok{angle =} \DecValTok{90}\NormalTok{, }\AttributeTok{hjust =} \DecValTok{1}\NormalTok{, }\AttributeTok{vjust =} \FloatTok{0.5}\NormalTok{), }\AttributeTok{text =} \FunctionTok{element\_text}\NormalTok{(}\AttributeTok{size =} \DecValTok{10}\NormalTok{)) }\SpecialCharTok{+}
-  \FunctionTok{scale\_x\_discrete}\NormalTok{(}\AttributeTok{labels =} \FunctionTok{labels}\NormalTok{(q18\_labels))}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{figure}[H]
-
-{\centering \includegraphics{final_draft_files/figure-pdf/religion-1.pdf}
-
-}
-
-\end{figure}
-
-and
-
-When you click the \textbf{Render} button a document will be generated
-that includes both content and the output of embedded code. You can
-embed code like this:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\DecValTok{1} \SpecialCharTok{+} \DecValTok{1}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{verbatim}
-[1] 2
-\end{verbatim}
-
-You can add options to executable code like this
-
-\begin{verbatim}
-[1] 4
-\end{verbatim}
-
-The \texttt{echo:\ false} option disables the printing of code (only
-output is displayed).
-
-\hypertarget{appendix-a-instrument}{%
-\section{Appendix A: Instrument}\label{appendix-a-instrument}}
-
-
-
-\end{document}
diff --git a/final_draft_files/figure-pdf/age-1.pdf b/final_draft_files/figure-pdf/age-1.pdf
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diff --git a/final_draft_files/figure-pdf/ethnicity-1.pdf b/final_draft_files/figure-pdf/ethnicity-1.pdf
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diff --git a/final_draft_files/figure-pdf/gender-1.pdf b/final_draft_files/figure-pdf/gender-1.pdf
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diff --git a/final_draft_files/figure-pdf/religion-1.pdf b/final_draft_files/figure-pdf/religion-1.pdf
deleted file mode 100644
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diff --git a/tsr_survey_analysis.Rmd b/tsr_survey_analysis.Rmd
deleted file mode 100644
index 10a6494..0000000
--- a/tsr_survey_analysis.Rmd
+++ /dev/null
@@ -1,1305 +0,0 @@
----
-title: "RMarkdown Admissions_Survey2021"
-output: html_document
----
-
-```{r setup, include=FALSE}
-knitr::opts_chunk$set(echo = TRUE)
-library(ggplot2)
-library(usethis)
-library(devtools)
-library(likert)
-library(RColorBrewer)
-library("readxl")
-library(haven)
-
-# Define colour palettes for plots below
-coul3 <- brewer.pal(3, "RdYlBu") # Using RdYlBu range to generate 3 colour palette: https://colorbrewer2.org/#type=diverging&scheme=RdYlBu&n=5
-
-TSR_data <- read.csv("./data/TSR data complete.csv")
-subject_data <- read.csv("./data/Subject data.csv")
-admissions_data <- read_excel("./data/TSR_data_numbers.xlsx", sheet = "Raw data - completes")
-
-# Set up local workspace, as needed:
-
-if (dir.exists("data") == FALSE) {
-  dir.create("data") 
-}
-
-# These paths are excluded from github as it is best practice for end-user to generate their own
-
-if (dir.exists("figures") == FALSE) {
-  dir.create("figures") 
-}
-if (dir.exists("derivedData") == FALSE) {
-  dir.create("derivedData")
-}
-
-# Refactor data
-q2_labels <- c("15 or under" = 1, "16" = 2, "17" = 3, "18" = 4, "19" = 5, "20" = 6, "21 or over" = 7, "Prefer not to say" = 8)
-admissions_data$Q2 <- labelled(admissions_data$Q2, q2_labels, label = "How old are you?")
-
-admissions_data$Q3 <- labelled(admissions_data$Q3, c("Year 11/S4/Year 12(NI)" = 1, "Year 12/S5/Year 13(NI)" = 2, "Year 13/S6/Year 14(NI)" = 3, "I am currently on a gap year" = 4, "I am currently on an undergraduate/HE college course" = 5, "I am in full-time employment" = 6, "I am unemployed" = 7, "Other" = 8, "Prefer not to say" = 9), label = "Which of the following best describes your MOST RECENT year of study?")
-
-admissions_data$Q4 <- labelled(admissions_data$Q4, c("Yes, definitely" = 1, "Yes, probably" = 2, "I haven’t ruled it out" = 3), label = "Are you considering or planning to go to university in the future?")
-
-common_labels <- c(
-  "Strongly agree" = 1,
-  "Agree" = 2,
-  "Neither/Nor" = 3,
-  "Disagree" = 4,
-  "Strongly disagree" = 5,
-  "Prefer not to say" = 0
-)
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q5_")), ~ labelled(., common_labels, label = "I have a good understanding of what this subject involves"))
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q6_")), ~ labelled(., common_labels, label = "I would be interested in studying this subject at University"))
-
-common_labels2 <- c(
-  "Good employability prospects" = 1,
-  NULL = 2,
-  NULL = 3,
-  NULL = 4,
-  "Poor employability prospects" = 5,
-  "Prefer not to say" = 0
-)
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q7_")), ~ labelled(., common_labels2, label = "This subject has… employability prospects"))
-
-admissions_data$Q8 <- labelled(admissions_data$Q8, c("Theology is a subject for religious people" = 1, NULL = 2, NULL = 3, NULL = 4, "Theology is a subject for religious and non-religious people" = 5, "Prefer not to say" = 0), label = "Thinking about Theology, please select an option on the scale from 1 to 5 which best represents your opinion")
-
-admissions_data$Q9 <- labelled(admissions_data$Q9, c("Religion is a subject for religious people" = 1, NULL = 2, NULL = 3, NULL = 4, "Religion is a subject for religious and non-religious people" = 5, "Prefer not to say" = 0), label = "Thinking about Religion, please select an option on the scale from 1 to 5 which best represents your opinion")
-
-common_labels3 <- c(
-  "Psychology" = 1, "Arts" = 2, "Sociology" = 3, "Politics" = 4, "History" = 5, "Philosophy" = 6, "Ethics" = 7, "Archaeology" = 8, "Textual studies" = 9, "Literature" = 10, "Law" = 11, "Economics" = 12, "Science" = 13, "Prefer not to say" = 0)
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q10_")), ~ labelled(., common_labels3, label = "I think that a theology degree would include..."))
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q11_")), ~ labelled(., common_labels3, label = "I think that a religious studies degree would include..."))
-
-common_labels4 <- c(
-  "Politics" = 1, "History" = 2, "Ethics" = 3, "Theology" = 4, "Religion" = 5, "Law" = 6, "Economics" = 7, "Maths" = 8, "Logic" = 9, "Prefer not to say" = 0)
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q12_")), ~ labelled(., common_labels4, label = "I think that a philosophy degree would include..."))
-
-common_labels5 <- c("Yes" = 1, "No" = 2, "Prefer not to say" = 0)
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q13")), ~ labelled(., common_labels5, label = "Are you currently studying A level Religious Studies, or intending to?"))
-
-admissions_data <- admissions_data %>%
-  mutate_at(vars(starts_with("Q14")), ~ labelled(., common_labels5, label = "Are you studying or did you previously study GCSE Religious Studies?"))
-
-admissions_data$Q16 <- labelled(admissions_data$Q16, c("Male"=1, "Female"=2, "I identify my gender in another way"=3, "Prefer not to say"=4), label = "I identify my gender as…")
-
-admissions_data$Q17 <- labelled(admissions_data$Q17, c("Arab"=1, "Indian"=2, "Pakistani"=3, "Bangladeshi"=4, "Chinese"=5, "Any other Asian background"=6, "Black - African"=7, "Black - Caribbean"=8, "Any other Black background"=9, "Mixed - White and Black Caribbean"=10, "Mixed - White and Black African"=11, "Mixed - White and Black Asian"=12, "Any other Mixed/Multiple Ethnic background"=13, "White - British"=14, "White - Irish"=15, "Gypsy or Irish Traveller"=16, "Any other White background"=17, "Other Ethnic group"=18, "Prefer not to say OR Other"=0), label = "What is your ethnic group?")
-
-admissions_data$Q18 <- labelled(admissions_data$Q18, c("Agnostic"=1, "Atheist"=2, "Baha'i"=3, "Buddhist"=4, "Christian"=5, "Confucian"=6, "Jain"=7, "Jewish"=8, "Hindu"=9, "Indigenous Traditional Religious"=10, "Muslim"=11, "Pagan"=12, "Shinto"=13, "Sikh"=14, "Spiritual but not religious"=15, "Zoroastrian"=16, "No religion"=17, "Prefer not to say OR Other"=0), label = "What is your religion?")
-
-# Create bins:
-
-# For Q5 - understanding
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q5_Theology = ifelse(Q5_Theology == 0, NA, Q5_Theology),
-    understanding_theology_bin = case_when(
-      Q5_Theology < 3 ~ "high",
-      Q5_Theology > 3 ~ "low",
-      Q5_Theology == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("low", "neutral", "high"))
-  )
-# For Q5 - understanding
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q5_Religious_Studies = ifelse(Q5_Religious_Studies == 0, NA, Q5_Religious_Studies),
-    understanding_religion_bin = case_when(
-      Q5_Religious_Studies < 3 ~ "high",
-      Q5_Religious_Studies > 3 ~ "low",
-      Q5_Religious_Studies == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("low", "neutral", "high"))
-  )
-# For Q6 - interest
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q6_Theology = ifelse(Q6_Theology == 0, NA, Q6_Theology),
-    interest_theology_bin = case_when(
-      Q6_Theology < 3 ~ "high",
-      Q6_Theology > 3 ~ "low",
-      Q6_Theology == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("low", "neutral", "high"))
-  )
-
-# For Q6 - interest
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q6_Religious_Studies = ifelse(Q6_Religious_Studies == 0, NA, Q6_Religious_Studies),
-    interest_religion_bin = case_when(
-      Q6_Religious_Studies < 3 ~ "high",
-      Q6_Religious_Studies > 3 ~ "low",
-      Q6_Religious_Studies == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("low", "neutral", "high"))
-  )
-
-# For Q7 - employability prospects
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q7_Theology = ifelse(Q7_Theology == 0, NA, Q7_Theology),
-    employability_optimism_theology_bin = case_when(
-      Q7_Theology < 3 ~ "high",
-      Q7_Theology > 3 ~ "low",
-      Q7_Theology == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("low", "neutral", "high"))
-  )
-
-# For Q7 - employability prospects
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q7_Religious_Studies = ifelse(Q7_Religious_Studies == 0, NA, Q7_Religious_Studies),
-    employability_optimism_religion_bin = case_when(
-      Q7_Religious_Studies < 3 ~ "high",
-      Q7_Religious_Studies > 3 ~ "low",
-      Q7_Religious_Studies == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("low", "neutral", "high"))
-  )
-
-# For Q8 - employability prospects
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q8 = ifelse(Q8 == 6, NA, Q8),
-    theology_for_bin = case_when(
-      Q8 < 3 ~ "religious",
-      Q8 > 3 ~ "all_people",
-      Q8 == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("all_people", "neutral", "religious"))
-  )
-
-admissions_data <- admissions_data %>%
-  mutate(
-    Q9 = ifelse(Q9 == 6, NA, Q9),
-    religion_for_bin = case_when(
-      Q9 < 3 ~ "religious",
-      Q9 > 3 ~ "all_people",
-      Q9 == 3 ~ "neutral",
-      TRUE ~ NA
-    ) %>% factor(levels = c("all_people", "neutral", "religious"))
-  )
-
-# Q17 non-white / white ethnicity bins
-admissions_data <- admissions_data %>%
-  mutate(
-    Q17 = ifelse(Q17 == 0, NA, Q17),
-    ethnicity_bin = case_when(
-      Q17 > 13 | Q17 < 18 ~ "white",
-      TRUE ~ "non-white"
-    ) %>% factor(levels = c("white", "non-white"))
-  )
-
-# Q18 non-religious / institutioal bins
-admissions_data <- admissions_data %>%
-  mutate(
-      Q18 = ifelse(Q18 == 0, NA, Q18),
-      religion_bin = case_when(
-      Q18 %in% c(1, 2, 5, 17) ~ "non-religious",
-      TRUE ~ "religious"
-    ) %>% factor(levels = c("non-religious", "religious"))
-  )
-
-```
-
-```{r correlations}
-Q5_data <- select(admissions_data, Q5_Philosophy:Q5_Business)
-cor(admissions_data$Q5_Philosophy, admissions_data$Q6_Philosophy)
-
-```
-
-# Basic demographic summary visualisations:
-```{r demographic_summaries}
-
-# 1. Calculate for age of respondent:
-
-age <- factor(admissions_data$Q2), levels = c(1, 2, 3, 4, 5, 6, 7, 8), labels = c("15 or under", "16", "17", "18", "19", "20", "21 or over", "Prefer not to say"))
-age_pie <- pie(table(admissions_data$Q2), col=coul3, cex = 0.8)
-# JK note: adding in a bar chart here, as according to the interwebs it's (apparently?) more accurate to visualise than bar charts
-
-ggplot(admissions_data, aes(factor(Q2))) + 
-  geom_bar() +
-  geom_text(stat = "count", aes(label = after_stat(count)), vjust = -0.5) +
-  labs(title = "Respondent Age Distribution", x = "Age", y = "") +
-  scale_x_discrete(labels = labels(q2_labels))
-
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_age.png")
-```
-
-```{r}
-# 2. Calculate for year of study:
-
-TSR_data_summaries_yos <- factor(TSR_data$MOSTRECENTyearofstudy, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9), labels = c("Year 11/S4/Year 12(NI)", "Year 12/S5/Year 13(NI)", "Year 13/S6/Year 14(NI)", "I am currently on a gap year", "I am currently on an undergraduate/HE college course", "I am in full-time employment", "I am unemployed", "Other", "Prefer not to say"))
-
-data_summaries_yos <- ggplot(TSR_data, aes(TSR_data_summaries_yos)) + geom_bar()
-data_summaries_yos + labs(title = "Respondent Most Recent Year of Study", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_yos.png")
-```
-
-```{r}
-# 3. Gender identity:
-
-TSR_data_summaries_gender <- factor(TSR_data$Gender, levels = c(1, 2, 3, 4), labels = c("Male", "Female", "I identify my gender in another way", "Prefer not to say"))
-# JK note: using stringr here to wrap axis titles
-TSR_data_summaries_gender <- str_wrap(TSR_data_summaries_gender, width = 10)
-
-data_summaries_gender <- ggplot(TSR_data, aes(TSR_data_summaries_gender)) + geom_bar()
-data_summaries_gender + labs(title = "Respondent gender self-identification", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_gender.png")
-
-# 4. Ethnic self-identification:
-
-TSR_data_summaries_ethnicity <- factor(TSR_data$Ethnicity, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ,18, 19), labels = c("Arab", "Indian", "Pakistani", "Bangladeshi", "Chinese", "Any other Asian background", "Black - African", "Black - Caribbean", "Any other Black background", "Mixed - White and Black Caribbean", "Mixed - White and Black African", "Mixed - White and Black Asian", "Any other Mixed/Multiple Ethnic background", "White - British", "White - Irish", "Gypsy or Irish Traveller", "Any other White background", "Other Ethnic group", "Prefer not to say"))
-TSR_data_summaries_ethnicity <- str_wrap(TSR_data_summaries_ethnicity, width = 30)
-
-data_summaries_ethnicity <- ggplot(TSR_data, aes(TSR_data_summaries_ethnicity)) + geom_bar() +  xlab(NULL) + coord_flip()
-data_summaries_ethnicity + labs(title = "Respondent ethnic self-identification", x = "", y = "")
-
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_ethnicity.png")
-
-# 5. Religion
-
-TSR_data_summaries_religion <- factor(TSR_data$ReligiousAffliation, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19), labels = c("Agnostic", "Atheist", "Baha'i", "Buddhist", "Christian", "Confucian", "Jain", "Jewish", "Hindu", "Indigenous Traditional Religious", "Muslim", "Pagan", "Shinto", "Sikh", "Spiritual but not religious", "Zoroastrian", "No religion", "Prefer not to say", "Other"))
-
-# Adding a subset for charting out composition of group which specifically marked positive sentiments wrt/ theology or religious studies
-
-TSR_data_theology_positive <- filter(TSR_data, InterestedinstudyingTheology >= 4 & InterestedinstudyingTheology != 0)
-TSR_data_theology_negative <- filter(TSR_data, InterestedinstudyingTheology <= 2 & InterestedinstudyingTheology != 0)
-
-TSR_data_rs_positive <- filter(TSR_data, InterestedinstudyingReligiousStudies >= 4 & InterestedinstudyingReligiousStudies != 0)
-TSR_data_rs_negative <- filter(TSR_data, InterestedinstudyingReligiousStudies <= 2 & InterestedinstudyingReligiousStudies != 0)
-
-TSR_data_theology_positive_summaries_religion <- factor(TSR_data_theology_positive$ReligiousAffliation, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19), labels = c("Agnostic", "Atheist", "Baha'i", "Buddhist", "Christian", "Confucian", "Jain", "Jewish", "Hindu", "Indigenous Traditional Religious", "Muslim", "Pagan", "Shinto", "Sikh", "Spiritual but not religious", "Zoroastrian", "No religion", "Prefer not to say", "Other"))
-
-TSR_data_theology_negative_summaries_religion <- factor(TSR_data_theology_negative$ReligiousAffliation, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19), labels = c("Agnostic", "Atheist", "Baha'i", "Buddhist", "Christian", "Confucian", "Jain", "Jewish", "Hindu", "Indigenous Traditional Religious", "Muslim", "Pagan", "Shinto", "Sikh", "Spiritual but not religious", "Zoroastrian", "No religion", "Prefer not to say", "Other"))
-
-TSR_data_rs_positive_summaries_religion <- factor(TSR_data_rs_positive$ReligiousAffliation, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19), labels = c("Agnostic", "Atheist", "Baha'i", "Buddhist", "Christian", "Confucian", "Jain", "Jewish", "Hindu", "Indigenous Traditional Religious", "Muslim", "Pagan", "Shinto", "Sikh", "Spiritual but not religious", "Zoroastrian", "No religion", "Prefer not to say", "Other"))
-
-TSR_data_rs_negative_summaries_religion <- factor(TSR_data_rs_negative$ReligiousAffliation, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19), labels = c("Agnostic", "Atheist", "Baha'i", "Buddhist", "Christian", "Confucian", "Jain", "Jewish", "Hindu", "Indigenous Traditional Religious", "Muslim", "Pagan", "Shinto", "Sikh", "Spiritual but not religious", "Zoroastrian", "No religion", "Prefer not to say", "Other"))
-
-TSR_data_theology_positive_summaries_ethnicity <- factor(TSR_data_theology_positive$Ethnicity, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ,18, 19), labels = c("Arab", "Indian", "Pakistani", "Bangladeshi", "Chinese", "Any other Asian background", "Black - African", "Black - Caribbean", "Any other Black background", "Mixed - White and Black Caribbean", "Mixed - White and Black African", "Mixed - White and Black Asian", "Any other Mixed/Multiple Ethnic background", "White - British", "White - Irish", "Gypsy or Irish Traveller", "Any other White background", "Other Ethnic group", "Prefer not to say"))
-
-TSR_data_theology_positive_summaries_ethnicity <- str_wrap(TSR_data_theology_positive_summaries_ethnicity, width = 30)
-
-TSR_data_rs_positive_summaries_ethnicity <- factor(TSR_data_rs_positive$Ethnicity, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ,18, 19), labels = c("Arab", "Indian", "Pakistani", "Bangladeshi", "Chinese", "Any other Asian background", "Black - African", "Black - Caribbean", "Any other Black background", "Mixed - White and Black Caribbean", "Mixed - White and Black African", "Mixed - White and Black Asian", "Any other Mixed/Multiple Ethnic background", "White - British", "White - Irish", "Gypsy or Irish Traveller", "Any other White background", "Other Ethnic group", "Prefer not to say"))
-
-TSR_data_rs_positive_summaries_ethnicity <- str_wrap(TSR_data_rs_positive_summaries_ethnicity, width = 30)
-
-TSR_data_theology_positive_summaries_gender <- factor(TSR_data_theology_positive$Gender, levels = c(1, 2, 3, 4), labels = c("Male", "Female", "I identify my gender in another way", "Prefer not to say"))
-# JK note: using stringr here to wrap axis titles
-TSR_data_theology_positive_summaries_gender <- str_wrap(TSR_data_theology_positive_summaries_gender, width = 10)
-
-TSR_data_rs_positive_summaries_gender <- factor(TSR_data_rs_positive$Gender, levels = c(1, 2, 3, 4), labels = c("Male", "Female", "I identify my gender in another way", "Prefer not to say"))
-# JK note: using stringr here to wrap axis titles
-TSR_data_rs_positive_summaries_gender <- str_wrap(TSR_data_rs_positive_summaries_gender, width = 10)
-
-
-# Calculate graphs
-
-Religious_affiliation_bar <- ggplot(TSR_data, aes(TSR_data_summaries_religion)) + geom_bar() + coord_flip()
-Religious_affiliation_bar + labs(title = "Respondent religious self-identification", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_religion.png")
-
-# Additional graphs for theology/rs positive sentiment cohorts
-
-# Theology - religious identification 
-
-# JK note: need to add percentages to each line, as per https://stackoverflow.com/questions/52373049/display-percentage-on-ggplot-bar-chart-in-r
-
-Religious_affiliation_bar2 <- ggplot(TSR_data_theology_positive, aes(TSR_data_theology_positive_summaries_religion)) + geom_bar() + coord_flip()
-Religious_affiliation_bar2 + labs(title = "Respondent religious self-identification, positive sentiment towards theology", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_religion_theologypositive.png")
-
-# RS
-
-Religious_affiliation_bar3 <- ggplot(TSR_data_rs_positive, aes(TSR_data_rs_positive_summaries_religion)) + geom_bar() + coord_flip()
-Religious_affiliation_bar3 + labs(title = "Respondent religious self-identification, positive sentiment towards rs", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_religion_rspositive.png")
-
-# Theology positive - gender 
-
-gender_bar2 <- ggplot(TSR_data_theology_positive, aes(TSR_data_theology_positive_summaries_gender)) + geom_bar()
-gender_bar2 + labs(title = "Respondent gender self-identification, theology positive", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_gender2.png")
-
-# Religion positive - gender
-
-gender_bar3 <- ggplot(TSR_data_rs_positive, aes(TSR_data_rs_positive_summaries_gender)) + geom_bar()
-gender_bar3 + labs(title = "Respondent gender self-identification, rs positive", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_gender3.png")
-
-# Theology positive - ethnicity
-
-data_summaries_theology_positive_ethnicity <- ggplot(TSR_data_theology_positive, aes(TSR_data_theology_positive_summaries_ethnicity)) + geom_bar() +  xlab(NULL) + coord_flip()
-data_summaries_theology_positive_ethnicity + labs(title = "Respondent ethnic self-identification - theology positive", x = "", y = "")
-
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_ethnicity2.png")
-
-# Religion positive - ethnicity
-
-data_summaries_rs_positive_ethnicity <- ggplot(TSR_data_rs_positive, aes(TSR_data_rs_positive_summaries_ethnicity)) + geom_bar() +  xlab(NULL) + coord_flip()
-data_summaries_ethnicity + labs(title = "Respondent ethnic self-identification - religion positive", x = "", y = "")
-
-# save to png file for reports
-ggsave("figures/TSR_data_summaries_ethnicity3.png")
-
-```
-
-# Visualisations of LIKERT responses (RH):
-- For questions Q6 (subject interest) / Q5 (subject knowledge) / Q7 employability prospects: 
-	- visualisation as summaries for all subjects LIKERT data as stacked bar chart (colours for bar segments from cool to warm)
-	
-```{r Visualization by Subject}
-
-## Files have been reverse scored - Higher score now indicates more agreement
-
-#Q5 Subject Knowledge/Understanding
-subject_data$Subject <- factor(subject_data$Subject, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12), labels = c("Philosophy", "Sociology", "Psychology", "History", "Ethics", "Theology", "Religious Studies", "Politics", "English", "Math", "Computer Science", "Business"))
-
-understanding_mean <- aggregate(Understanding ~ Subject, data = subject_data, mean)
-
-understanding_bar <- ggplot(understanding_mean, aes(x = Subject, y = Understanding)) + stat_summary(fun = "mean", geom = "bar") + coord_flip()
-understanding_bar + labs(title = "I have a good understanding of what this subject involves?", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_subject_understanding.png")
-
-
-#Q6 Subject Interest
-interest_mean <- aggregate(Interest ~ Subject, data = subject_data, mean)
-
-interest_bar <- ggplot(interest_mean, aes(x = Subject, y = Interest)) + stat_summary(fun = "mean", geom = "bar") + coord_flip()
-interest_bar + labs(title = "I would be interested in studying this subject at University?", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_subject_interest.png")
-
-#Q7 Employability Prospects
-
-employability_mean <- aggregate(Employability ~ Subject, data = subject_data, mean)
-
-employability_bar <- ggplot(employability_mean, aes(x = Subject, y = Employability)) + stat_summary(fun = "mean", geom = "bar") + coord_flip()
-employability_bar + labs(title = "please rate ... employability prospects", x = "", y = "")
-# save to png file for reports
-ggsave("figures/TSR_data_subject_employability.png")
-```
-
-```{r}
-### Likert Stacked Bar Chart ###
-
-# Take selection of data re: understanding
-Understanding_data <- TSR_data[, 6:17]
-# Convert each column to factors
-Understanding_data$GoodunderstandingofPhilosophy = factor(Understanding_data$GoodunderstandingofPhilosophy,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofSociology = factor(Understanding_data$GoodunderstandingofSociology,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofPsychology = factor(Understanding_data$GoodunderstandingofPsychology,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofHistory = factor(Understanding_data$GoodunderstandingofHistory,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofEthics = factor(Understanding_data$GoodunderstandingofEthics,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofTheology = factor(Understanding_data$GoodunderstandingofTheology,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofReligiousStudies = factor(Understanding_data$GoodunderstandingofReligiousStudies,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofPolitics = factor(Understanding_data$GoodunderstandingofPolitics,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofEnglish = factor(Understanding_data$GoodunderstandingofEnglish,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofMath = factor(Understanding_data$GoodunderstandingofMath,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofComputerScience = factor(Understanding_data$GoodunderstandingofComputerScience,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Understanding_data$GoodunderstandingofBusiness = factor(Understanding_data$GoodunderstandingofBusiness,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-names(Understanding_data) <- c("Philosophy", "Sociology", "Psychology", "History", "Ethics", "Theology", "Religious Studies", "Politics", "English", "Math", "Computer Science", "Business")
-
-str(Understanding_data)
-levels(Understanding_data)
-summary(Understanding_data)
-likert_test_understand <- likert(Understanding_data)
-Understanding_data <- Q5_data
-likert_test_understand <- likert(Q5_data)
-plot(likert_test_understand)
-# save to png file for reports
-ggsave("figures/understanding_likert.png")
-```
-
-```{r}
-Interest_data <- TSR_data[, 18:29]
-# Convert each column to factors
-Interest_data$InterestinstudyingPhilosophy = factor(Interest_data$InterestinstudyingPhilosophy,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestinstudyingSociaology = factor(Interest_data$InterestinstudyingSociaology,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinStudyingPsychology = factor(Interest_data$InterestedinStudyingPsychology,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingHistory = factor(Interest_data$InterestedinstudyingHistory,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingEthics = factor(Interest_data$InterestedinstudyingEthics,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingTheology = factor(Interest_data$InterestedinstudyingTheology,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingReligiousStudies = factor(Interest_data$InterestedinstudyingReligiousStudies,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingPolitics = factor(Interest_data$InterestedinstudyingPolitics,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingEnglish = factor(Interest_data$InterestedinstudyingEnglish,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingMath = factor(Interest_data$InterestedinstudyingMath,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingComputerScience = factor(Interest_data$InterestedinstudyingComputerScience,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Interest_data$InterestedinstudyingBusiness = factor(Interest_data$InterestedinstudyingBusiness,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-names(Interest_data) <- c("Philosophy", "Sociology", "Psychology", "History", "Ethics", "Theology", "Religious Studies", "Politics", "English", "Math", "Computer Science", "Business")
-
-likert_test_interest <- likert(Interest_data)
-plot(likert_test_interest)
-# save to png file for reports
-ggsave("figures/interest_likert.png")
-
-
-Employability_data <- TSR_data[, 30:41]
-# Convert each column to factors
-Employability_data$Philosophyemployability = factor(Employability_data$Philosophyemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Sociologyemployability = factor(Employability_data$Sociologyemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$PsychologyEmployability = factor(Employability_data$PsychologyEmployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Historyemployability = factor(Employability_data$Historyemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Ethicsemployability = factor(Employability_data$Ethicsemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Theologyemployability = factor(Employability_data$Theologyemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$ReligiousStudiesemployability = factor(Employability_data$ReligiousStudiesemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Politicsemployability = factor(Employability_data$Politicsemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Englishemployability = factor(Employability_data$Englishemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Mathemployability = factor(Employability_data$Mathemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$ComputerScienceemployability = factor(Employability_data$ComputerScienceemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-Employability_data$Businessemployability = factor(Employability_data$Businessemployability,
-                       ordered = TRUE,
-                       levels = c("1", "2", "3", "4", "5")
-                       )
-names(Employability_data) <- c("Philosophy", "Sociology", "Psychology", "History", "Ethics", "Theology", "Religious Studies", "Politics", "English", "Math", "Computer Science", "Business")
-
-likert_test_employability <- likert(Employability_data)
-plot(likert_test_employability)
-# save to png file for reports
-ggsave("figures/employability_likert.png")
-
-
-```
-
-	- separate visualisation of summary data as pie chart only for 4 key subjects: Philosophy, Ethics, Theology, Religious Studies, but with data represented as aggregated "Positive" / "Negative" responses
-	
-```{r Visualization for 4 Key Subjects}
-## Subset by "Positive" / "Negative"
-
-# jk note: I've filled in the other fields just for fun
-
-keysubjects_data <- subject_data[subject_data$Subject == "Philosophy" | subject_data$Subject == "Ethics" | subject_data$Subject == "Theology" | subject_data$Subject == "Religious Studies" | subject_data$Subject == "Sociology" | subject_data$Subject == "Psychology" | subject_data$Subject == "History" | subject_data$Subject == "Politics" | subject_data$Subject == "English" | subject_data$Subject == "Math" | subject_data$Subject == "Computer Science" | subject_data$Subject == "Business", ]
-
-recode_interest <- ifelse(2 <= keysubjects_data$Interest & keysubjects_data$Interest >=4, "Positive", "Negative")
-
-keysubjects_data <- cbind(keysubjects_data, recode_interest)
-keysubjects_data$recode_interest <- factor(keysubjects_data$recode_interest)
-
-interest_table <- table(keysubjects_data$recode_interest, keysubjects_data$Subject)
-# export table to csv
-write.csv(interest_table, "derivedData/interest_table.csv", row.names=TRUE)
-
-
-
-```
-	- subsetted visualisations of responses with separate subsetting by response to Q8-9, Q18, Q17, Q16
-- For question Q8 + Q9 (for religious people) 
-	- visualisation summary of responses
-	- show subsetted visualisations of responses by response to, Q18, Q17, Q16, Q13, Q14
-- For responses to Q10-12 (what subjects are involved in...):
-	- represent answer counts as descending bar chart for each Q
-	- subset answers by Q6 (positive / negative) and Q5 (positive / negative)
-
-# Correlation testing:
-- For Q6 (subject interest) / Q5 (subject knowledge) / Q7 employability prospects, test for nature / strength of correlation with responses to:
-	- Q8-9 responses
-	- Q18 responses
-	- Q17
-
-
-```{r Q6 Correlations - Subject Interest}
-#Q8-9 (8 - Theology as subject for religious people; 9 - Religion as study for religious people)
-  # This would be suitable for correlation
-
-#Q17 (Ethnicity)
-  # This would be categorical, so ANOVA
-
-#Q18 (Religion)
-  # This would also be categorical, so ANOVA
-
-```
-
-```{r Q5 Correlations - Subject Knowledge}
-#Q8-9 (8 - Theology as subject for religious people; 9 - Religion as study for religious people)
-  # This would be suitable for correlation
-
-#Q17 (Ethnicity)
-  # This would be categorical, so ANOVA
-
-#Q18 (Religion)
-  # This would also be categorical, so ANOVA
-```
-
-```{r Q7 Correlations - Employability}
-#Q8-9 (8 - Theology as subject for religious people; 9 - Religion as study for religious people)
-  # This would be suitable for correlation
-
-#Q17 (Ethnicity)
-  # This would be categorical, so ANOVA
-
-#Q18 (Religion)
-  # This would also be categorical, so ANOVA
-```
-
-
-```{r testing fun}
-#testcor_data <- subject_data[subject_data$Subject == "Psychology" | subject_data$Subject == "Theology", ]
-
-#t.test(Interest ~ Subject, data = testcor_data)
-
-# testsubset <- TSR_data[TSR_data$Interested.in.Studying.Psychology < 3 & TSR_data$Interested.in.Studying.Psychology != 0, ]
-# as.numeric(testsubset$Interested.in.studying.Theology)
-# mean(testsubset$Interested.in.studying.Theology, na.rm = TRUE)
-# 
-# mean(as.numeric(testsubset$Interested.in.studying.Theology), na.rm = TRUE)
-# 
-# as.numeric(testsubset$Interested.in.studying.Religious.Studies)
-# mean(testsubset$Interested.in.studying.Religious.Studies, na.rm = TRUE)
-# 
-# testsubset2 <- TSR_data[TSR_data$Interested.in.Studying.Psychology > 3, ]
-# mean(as.numeric(testsubset2$Interested.in.studying.Theology), na.rm = TRUE)
-# mean(as.numeric(testsubset2$Interested.in.studying.Religious.Studies), na.rm = TRUE)
-```
-
-## Mean Interest in Theology and Religious Studies by High/Low Subject Interest
-
-```{r Philosophy}
-# Base mean:
-
-mean(as.numeric(TSR_data$InterestedinstudyingTheology), na.rm = TRUE)
-mean(as.numeric(TSR_data$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-mean(as.numeric(TSR_data$InterestinstudyingPhilosophy), na.rm = TRUE)
-mean(as.numeric(TSR_data$InterestedinStudyingPsychology), na.rm = TRUE)
-
-### Philosophy ###
-Philos_subset_Low <- TSR_data[TSR_data$InterestinstudyingPhilosophy < 3 & TSR_data$InterestinstudyingPhilosophy != 0, ]
-
-Philos_subset_High <- TSR_data[TSR_data$InterestinstudyingPhilosophy > 3, ]
-
-## Theology Interest
-#Low interest in Philosophy
-mean(as.numeric(Philos_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Philosophy
-mean(as.numeric(Philos_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Philosophy
-mean(as.numeric(Philos_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Philosophy
-mean(as.numeric(Philos_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Sociology}
-### Sociology ###
-Soc_subset_Low <- TSR_data[TSR_data$InterestinstudyingSociaology < 3 & TSR_data$InterestinstudyingSociaology != 0, ]
-
-Soc_subset_High <- TSR_data[TSR_data$InterestinstudyingSociaology > 3, ]
-
-## Theology Interest
-#Low interest in Sociology
-mean(as.numeric(Soc_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Sociology
-mean(as.numeric(Soc_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Sociology
-mean(as.numeric(Soc_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Sociology
-mean(as.numeric(Soc_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Psychology}
-### Psychology ###
-Psych_subset_Low <- TSR_data[TSR_data$InterestedinStudyingPsychology < 3 & TSR_data$InterestedinStudyingPsychology != 0, ]
-
-Psych_subset_High <- TSR_data[TSR_data$InterestedinStudyingPsychology > 3, ]
-
-## Theology Interest
-#Low interest in Psychology
-mean(as.numeric(Psych_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Psychology
-mean(as.numeric(Psych_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Psychology
-mean(as.numeric(Psych_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Psychology
-mean(as.numeric(Psych_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r History}
-### History ###
-Hist_subset_Low <- TSR_data[TSR_data$InterestedinstudyingHistory < 3 & TSR_data$InterestedinstudyingHistory != 0, ]
-
-Hist_subset_High <- TSR_data[TSR_data$InterestedinstudyingHistory > 3, ]
-
-## Theology Interest
-#Low interest in History
-mean(as.numeric(Hist_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in History
-mean(as.numeric(Hist_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in History
-mean(as.numeric(Hist_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in History
-mean(as.numeric(Hist_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Ethics}
-### Ethics ###
-Ethics_subset_Low <- TSR_data[TSR_data$InterestedinstudyingEthics < 3 & TSR_data$InterestedinstudyingEthics != 0, ]
-
-Ethics_subset_High <- TSR_data[TSR_data$InterestedinstudyingEthics > 3, ]
-
-## Theology Interest
-#Low interest in Ethics
-mean(as.numeric(Ethics_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Ethics
-mean(as.numeric(Ethics_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Ethics
-mean(as.numeric(Ethics_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Ethics
-mean(as.numeric(Ethics_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Politics}
-### Politics ###
-Polit_subset_Low <- TSR_data[TSR_data$InterestedinstudyingPolitics < 3 & TSR_data$InterestedinstudyingPolitics != 0, ]
-
-Polit_subset_High <- TSR_data[TSR_data$InterestedinstudyingPolitics > 3, ]
-
-## Theology Interest
-#Low interest in Politics
-mean(as.numeric(Polit_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Politics
-mean(as.numeric(Polit_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Politics
-mean(as.numeric(Polit_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Politics
-mean(as.numeric(Polit_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r English}
-### English ###
-Eng_subset_Low <- TSR_data[TSR_data$InterestedinstudyingEnglish < 3 & TSR_data$InterestedinstudyingEnglish != 0, ]
-
-Eng_subset_High <- TSR_data[TSR_data$InterestedinstudyingEnglish > 3, ]
-
-## Theology Interest
-#Low interest in English
-mean(as.numeric(Eng_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in English
-mean(as.numeric(Eng_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in English
-mean(as.numeric(Eng_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in English
-mean(as.numeric(Eng_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Math}
-### Math ###
-Math_subset_Low <- TSR_data[TSR_data$InterestedinstudyingMath < 3 & TSR_data$InterestedinstudyingMath != 0, ]
-
-Math_subset_High <- TSR_data[TSR_data$InterestedinstudyingMath > 3, ]
-
-## Theology Interest
-#Low interest in Math
-mean(as.numeric(Math_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Math
-mean(as.numeric(Math_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Math
-mean(as.numeric(Math_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Math
-mean(as.numeric(Math_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Computer Science}
-### Computer Science ###
-CompSci_subset_Low <- TSR_data[TSR_data$InterestedinstudyingComputerScience < 3 & TSR_data$InterestedinstudyingComputerScience != 0, ]
-
-CompSci_subset_High <- TSR_data[TSR_data$InterestedinstudyingComputerScience > 3, ]
-
-## Theology Interest
-#Low interest in Computer Science
-mean(as.numeric(CompSci_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Computer Science
-mean(as.numeric(CompSci_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Computer Science
-mean(as.numeric(CompSci_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Computer Science
-mean(as.numeric(CompSci_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-```
-
-```{r Business}
-### Business ###
-Busi_subset_Low <- TSR_data[TSR_data$InterestedinstudyingBusiness < 3 & TSR_data$InterestedinstudyingBusiness != 0, ]
-
-Busi_subset_High <- TSR_data[TSR_data$InterestedinstudyingBusiness > 3, ]
-
-## Theology Interest
-#Low interest in Business
-mean(as.numeric(Busi_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
-#High interest in Business
-mean(as.numeric(Busi_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
-
-## Religious Studies Interest
-#Low interest in Business
-mean(as.numeric(Busi_subset_Low$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-#High interest in Business
-mean(as.numeric(Busi_subset_High$InterestedinstudyingReligiousStudies), na.rm = TRUE)
-
-```
-
-
-## Mean Knowledge in Theology and Religious Studies by High/Low Subject Knowledge
-
-```{r Philosophy}
-# Base calculations
-
-mean(as.numeric(TSR_data$GoodunderstandingofTheology), na.rm = TRUE)
-mean(as.numeric(TSR_data$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-mean(as.numeric(TSR_data$GoodunderstandingofPhilosophy), na.rm = TRUE)
-mean(as.numeric(TSR_data$GoodunderstandingofPsychology), na.rm = TRUE)
-mean(as.numeric(TSR_data$GoodunderstandingofEnglish), na.rm = TRUE)
-mean(as.numeric(TSR_data$GoodunderstandingofMath), na.rm = TRUE)
-
-### Philosophy ###
-
-# Low understanding of philosophy cohort
-Philos_subset_Low <- TSR_data[TSR_data$GoodunderstandingofPhilosophy < 3 & TSR_data$GoodunderstandingofPhilosophy != 0, ]
-
-# High understanding of philosophy cohort
-Philos_subset_High <- TSR_data[TSR_data$GoodunderstandingofPhilosophy > 3, ]
-
-## Theology Knowledge
-#Low knowledge in Philosophy
-mean(as.numeric(Philos_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Philosophy
-mean(as.numeric(Philos_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies Knowledge
-#Low knowledge in Philosophy
-mean(as.numeric(Philos_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Philosophy
-mean(as.numeric(Philos_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Sociology}
-### Sociology ###
-Soc_subset_Low <- TSR_data[TSR_data$GoodunderstandingofSociology < 3 & TSR_data$GoodunderstandingofSociology != 0, ]
-
-Soc_subset_High <- TSR_data[TSR_data$GoodunderstandingofSociology > 3, ]
-
-## Theology knowledge
-#Low knowledge in Sociology
-mean(as.numeric(Soc_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Sociology
-mean(as.numeric(Soc_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Sociology
-mean(as.numeric(Soc_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Sociology
-mean(as.numeric(Soc_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Psychology}
-### Psychology ###
-Psych_subset_Low <- TSR_data[TSR_data$GoodunderstandingofPsychology < 3 & TSR_data$GoodunderstandingofPsychology != 0, ]
-
-Psych_subset_High <- TSR_data[TSR_data$GoodunderstandingofPsychology > 3, ]
-
-## Theology knowledge
-#Low knowledge in Psychology
-mean(as.numeric(Psych_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Psychology
-mean(as.numeric(Psych_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Psychology
-mean(as.numeric(Psych_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Psychology
-mean(as.numeric(Psych_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r History}
-### History ###
-Hist_subset_Low <- TSR_data[TSR_data$GoodunderstandingofHistory < 3 & TSR_data$GoodunderstandingofHistory != 0, ]
-
-Hist_subset_High <- TSR_data[TSR_data$GoodunderstandingofHistory > 3, ]
-
-## Theology knowledge
-#Low knowledge in History
-mean(as.numeric(Hist_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in History
-mean(as.numeric(Hist_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in History
-mean(as.numeric(Hist_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in History
-mean(as.numeric(Hist_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Ethics}
-### Ethics ###
-Ethics_subset_Low <- TSR_data[TSR_data$GoodunderstandingofEthics < 3 & TSR_data$GoodunderstandingofEthics != 0, ]
-
-Ethics_subset_High <- TSR_data[TSR_data$GoodunderstandingofEthics > 3, ]
-
-## Theology knowledge
-#Low knowledge in Ethics
-mean(as.numeric(Ethics_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Ethics
-mean(as.numeric(Ethics_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Ethics
-mean(as.numeric(Ethics_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Ethics
-mean(as.numeric(Ethics_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Politics}
-### Politics ###
-Polit_subset_Low <- TSR_data[TSR_data$GoodunderstandingofPolitics < 3 & TSR_data$GoodunderstandingofPolitics != 0, ]
-
-Polit_subset_High <- TSR_data[TSR_data$GoodunderstandingofPolitics > 3, ]
-
-## Theology knowledge
-#Low knowledge in Politics
-mean(as.numeric(Polit_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Politics
-mean(as.numeric(Polit_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Politics
-mean(as.numeric(Polit_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Politics
-mean(as.numeric(Polit_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r English}
-### English ###
-Eng_subset_Low <- TSR_data[TSR_data$GoodunderstandingofEnglish < 3 & TSR_data$GoodunderstandingofEnglish != 0, ]
-
-Eng_subset_High <- TSR_data[TSR_data$GoodunderstandingofEnglish > 3, ]
-
-## Theology knowledge
-#Low knowledge in English
-mean(as.numeric(Eng_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in English
-mean(as.numeric(Eng_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in English
-mean(as.numeric(Eng_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in English
-mean(as.numeric(Eng_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Math}
-### Math ###
-Math_subset_Low <- TSR_data[TSR_data$GoodunderstandingofMath < 3 & TSR_data$GoodunderstandingofMath != 0, ]
-
-Math_subset_High <- TSR_data[TSR_data$GoodunderstandingofMath > 3, ]
-
-## Theology knowledge
-#Low knowledge in Math
-mean(as.numeric(Math_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Math
-mean(as.numeric(Math_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Math
-mean(as.numeric(Math_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Math
-mean(as.numeric(Math_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Computer Science}
-### Computer Science ###
-CompSci_subset_Low <- TSR_data[TSR_data$GoodunderstandingofComputerScience < 3 & TSR_data$GoodunderstandingofComputerScience != 0, ]
-
-CompSci_subset_High <- TSR_data[TSR_data$GoodunderstandingofComputerScience > 3, ]
-
-## Theology knowledge
-#Low knowledge in Computer Science
-mean(as.numeric(CompSci_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Computer Science
-mean(as.numeric(CompSci_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Computer Science
-mean(as.numeric(CompSci_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Computer Science
-mean(as.numeric(CompSci_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-```
-
-```{r Business}
-### Business ###
-Busi_subset_Low <- TSR_data[TSR_data$GoodunderstandingofBusiness < 3 & TSR_data$GoodunderstandingofBusiness != 0, ]
-
-Busi_subset_High <- TSR_data[TSR_data$GoodunderstandingofBusiness > 3, ]
-
-## Theology knowledge
-#Low knowledge in Business
-mean(as.numeric(Busi_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
-#High knowledge in Business
-mean(as.numeric(Busi_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
-
-## Religious Studies knowledge
-#Low knowledge in Business
-mean(as.numeric(Busi_subset_Low$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-#High knowledge in Business
-mean(as.numeric(Busi_subset_High$GoodunderstandingofReligiousStudies), na.rm = TRUE)
-
-```
-
-
-## Mean Employability in Theology and Religious Studies by High/Low Subject Employability
-
-```{r Philosophy}
-# Base Calculations
-
-mean(as.numeric(TSR_data$Theologyemployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$ReligiousStudiesemployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$Philosophyemployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$PsychologyEmployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$Englishemployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$Mathemployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$Businessemployability), na.rm = TRUE)
-mean(as.numeric(TSR_data$ComputerScienceemployability), na.rm = TRUE)
-
-### Philosophy ###
-Philos_subset_Low <- TSR_data[TSR_data$Philosophyemployability < 3 & TSR_data$Philosophyemployability != 0, ]
-
-Philos_subset_High <- TSR_data[TSR_data$Philosophyemployability > 3, ]
-
-## Theology employability
-#Low employability in Philosophy
-mean(as.numeric(Philos_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Philosophy
-mean(as.numeric(Philos_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Philosophy
-mean(as.numeric(Philos_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Philosophy
-mean(as.numeric(Philos_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Sociology}
-### Sociology ###
-Soc_subset_Low <- TSR_data[TSR_data$Sociologyemployability < 3 & TSR_data$Sociologyemployability != 0, ]
-
-Soc_subset_High <- TSR_data[TSR_data$Sociologyemployability > 3, ]
-
-## Theology employability
-#Low employability in Sociology
-mean(as.numeric(Soc_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Sociology
-mean(as.numeric(Soc_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Sociology
-mean(as.numeric(Soc_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Sociology
-mean(as.numeric(Soc_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Psychology}
-### Psychology ###
-Psych_subset_Low <- TSR_data[TSR_data$PsychologyEmployability < 3 & TSR_data$PsychologyEmployability != 0, ]
-
-Psych_subset_High <- TSR_data[TSR_data$PsychologyEmployability > 3, ]
-
-## Theology employability
-#Low employability in Psychology
-mean(as.numeric(Psych_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Psychology
-mean(as.numeric(Psych_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Psychology
-mean(as.numeric(Psych_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Psychology
-mean(as.numeric(Psych_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r History}
-### History ###
-Hist_subset_Low <- TSR_data[TSR_data$Historyemployability < 3 & TSR_data$Historyemployability != 0, ]
-
-Hist_subset_High <- TSR_data[TSR_data$Historyemployability > 3, ]
-
-## Theology employability
-#Low employability in History
-mean(as.numeric(Hist_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in History
-mean(as.numeric(Hist_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in History
-mean(as.numeric(Hist_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in History
-mean(as.numeric(Hist_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Ethics}
-### Ethics ###
-Ethics_subset_Low <- TSR_data[TSR_data$Ethicsemployability < 3 & TSR_data$Ethicsemployability != 0, ]
-
-Ethics_subset_High <- TSR_data[TSR_data$Ethicsemployability > 3, ]
-
-## Theology employability
-#Low employability in Ethics
-mean(as.numeric(Ethics_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Ethics
-mean(as.numeric(Ethics_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Ethics
-mean(as.numeric(Ethics_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Ethics
-mean(as.numeric(Ethics_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Politics}
-### Politics ###
-Polit_subset_Low <- TSR_data[TSR_data$Politicsemployability < 3 & TSR_data$Politicsemployability != 0, ]
-
-Polit_subset_High <- TSR_data[TSR_data$Politicsemployability > 3, ]
-
-## Theology employability
-#Low employability in Politics
-mean(as.numeric(Polit_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Politics
-mean(as.numeric(Polit_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Politics
-mean(as.numeric(Polit_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Politics
-mean(as.numeric(Polit_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r English}
-### English ###
-Eng_subset_Low <- TSR_data[TSR_data$Englishemployability < 3 & TSR_data$Englishemployability != 0, ]
-
-Eng_subset_High <- TSR_data[TSR_data$Englishemployability > 3, ]
-
-## Theology employability
-#Low employability in English
-mean(as.numeric(Eng_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in English
-mean(as.numeric(Eng_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in English
-mean(as.numeric(Eng_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in English
-mean(as.numeric(Eng_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Math}
-### Math ###
-Math_subset_Low <- TSR_data[TSR_data$Mathemployability < 3 & TSR_data$Mathemployability != 0, ]
-
-Math_subset_High <- TSR_data[TSR_data$Mathemployability > 3, ]
-
-## Theology employability
-#Low employability in Math
-mean(as.numeric(Math_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Math
-mean(as.numeric(Math_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Math
-mean(as.numeric(Math_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Math
-mean(as.numeric(Math_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Computer Science}
-### Computer Science ###
-CompSci_subset_Low <- TSR_data[TSR_data$ComputerScienceemployability < 3 & TSR_data$ComputerScienceemployability != 0, ]
-
-CompSci_subset_High <- TSR_data[TSR_data$ComputerScienceemployability > 3, ]
-
-## Theology employability
-#Low employability in Computer Science
-mean(as.numeric(CompSci_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Computer Science
-mean(as.numeric(CompSci_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Computer Science
-mean(as.numeric(CompSci_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Computer Science
-mean(as.numeric(CompSci_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-```
-
-```{r Business}
-### Business ###
-Busi_subset_Low <- TSR_data[TSR_data$Businessemployability < 3 & TSR_data$Businessemployability != 0, ]
-
-Busi_subset_High <- TSR_data[TSR_data$Businessemployability > 3, ]
-
-## Theology employability
-#Low employability in Business
-mean(as.numeric(Busi_subset_Low$Theologyemployability), na.rm = TRUE)
-#High employability in Business
-mean(as.numeric(Busi_subset_High$Theologyemployability), na.rm = TRUE)
-
-## Religious Studies employability
-#Low employability in Business
-mean(as.numeric(Busi_subset_Low$ReligiousStudiesemployability), na.rm = TRUE)
-#High employability in Business
-mean(as.numeric(Busi_subset_High$ReligiousStudiesemployability), na.rm = TRUE)
-
-```