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updating simd section

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Jeremy Kidwell 2019-01-30 18:59:05 +00:00
parent 45ef133438
commit 4bc31337ea
1 changed files with 26 additions and 24 deletions
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mapping_draft.Rmd
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@ -680,42 +680,43 @@ dtas@data=cbind(dtas@data,over(dtas,simd))
# STAGE 2, extract NULL cells from each data set to prevent errors in stage 3
# convert back to data frame for null cell extraction
ecs<-data.frame(ecs)
ecs_df<-data.frame(ecs)
# split out null and normal cells
ecs_clean<-ecs[complete.cases(ecs),]
ecs_null<-ecs[!complete.cases(ecs),]
# convert back to spatialpointdataframe
coordinates(ecs) <- c("X", "Y")
proj4string(ecs) <- proj4string(admin_lev1)
ecs_clean<-ecs_df[complete.cases(ecs_df),]
ecs_null<-ecs_df[!complete.cases(ecs_df),]
# convert back to data frame for null cell extraction
transition<-data.frame(transition)
transition_df<-data.frame(transition)
# split out null and normal cells
transition_clean<-transition[complete.cases(transition),]
transition_null<-transition[!complete.cases(transition),]
# convert back to spatialpointdataframe
coordinates(transition) <- c("X", "Y")
proj4string(transition) <- proj4string(admin_lev1)
transition_clean<-transition_df[complete.cases(transition_df),]
transition_null<-transition_df[!complete.cases(transition_df),]
# convert back to data frame for null cell extraction
permaculture<-data.frame(permaculture)
permaculture_df<-data.frame(permaculture)
# split out null and normal cells
permaculture_clean<-permaculture[complete.cases(permaculture),]
permaculture_null<-permaculture[!complete.cases(permaculture),]
# convert back to spatialpointdataframe
coordinates(permaculture) <- c("X", "Y")
proj4string(permaculture) <- proj4string(admin_lev1)
permaculture_clean<-permaculture_df[complete.cases(permaculture_df),]
permaculture_null<-permaculture_df[!complete.cases(permaculture_df),]
# convert back to data frame for null cell extraction
dtas<-data.frame(dtas)
dtas_df<-data.frame(dtas)
# split out null and normal cells
dtas_clean<-dtas[complete.cases(dtas),]
dtas_null<-dtas[!complete.cases(dtas),]
# convert back to spatialpointdataframe
coordinates(dtas) <- c("X", "Y")
proj4string(dtas) <- proj4string(admin_lev1)
dtas_clean<-dtas_df[complete.cases(dtas_df),]
dtas_null<-dtas_df[!complete.cases(dtas_df),]
# TODO: change names to match simd2016 conventions
# Overal_SIMD16_Rank
# SIMD_2016_Quintile
# SIMD_2016_Decile
#
# Income_Domain_2016_Rank
# Employment_Domain_2016_Rank
# Health_Domain_2016_Rank
# Education_Domain_2016_Rank
# Geographic_Access_Domain_2016_Rank
# Crime_Domain_2016_Rank
# Housing_Domain_2016_Rank
# STAGE 3a, calculate sums based on SIMD12R columns and generate new integer sets with quintile count data
simd_rownames = c("Quintile 1","Quintile 2","Quintile 3","Quintile 4","Quintile 5")
simdr12_ecs = c((sum(ecs_clean$SIMDR12<1301)), (sum(ecs_clean$SIMDR12 > 1300 & ecs_clean$SIMDR12 < 2602)), (sum(ecs_clean$SIMDR12 > 2601 & ecs_clean$SIMDR12 < 3903)), (sum(ecs_clean$SIMDR12 > 3902 & ecs_clean$SIMDR12 < 5204)), (sum(ecs_clean$SIMDR12 > 5203 & ecs_clean$SIMDR12 < 6505)))
@ -728,6 +729,7 @@ simdr12_dtas = c((sum(dtas_clean$SIMDR12<1301)), (sum(dtas_clean$SIMDR12 > 1300
# names(simdr12_dtas) <- simd_rownames
# STAGE 3b, calculate sums based on INCR12 columns and generate new integer sets with quintile count data
incr12_ecs = c((sum(ecs_clean$INCR12<1301)), (sum(ecs_clean$INCR12 > 1300 & ecs_clean$INCR12 < 2602)), (sum(ecs_clean$INCR12 > 2601 & ecs_clean$INCR12 < 3903)), (sum(ecs_clean$INCR12 > 3902 & ecs_clean$INCR12 < 5204)), (sum(ecs_clean$INCR12 > 5203 & ecs_clean$INCR12 < 6505)))
incr12_transition = c((sum(transition_clean$INCR12<1301)), (sum(transition_clean$INCR12 > 1300 & transition_clean$INCR12 < 2602)), (sum(transition_clean$INCR12 > 2601 & transition_clean$INCR12 < 3903)), (sum(transition_clean$INCR12 > 3902 & transition_clean$INCR12 < 5204)), (sum(transition_clean$INCR12 > 5203 & transition_clean$INCR12 < 6505)))
incr12_permaculture = c((sum(permaculture_clean$INCR12<1301)), (sum(permaculture_clean$INCR12 > 1300 & permaculture_clean$INCR12 < 2602)), (sum(permaculture_clean$INCR12 > 2601 & permaculture_clean$INCR12 < 3903)), (sum(permaculture_clean$INCR12 > 3902 & permaculture_clean$INCR12 < 5204)), (sum(permaculture_clean$INCR12 > 5203 & permaculture_clean$INCR12 < 6505)))