Pie Charts and More Data Finagling

Figuring how to put frequencies of multiple response data into a clean format, then creating rough code for a simple pie chart (to be made pretty later).

Finished this for the 3 questions needing pie charts.

Connect Project R Markdown.Rmd

@@ -31,7 +31,7 @@ Note that the `echo = FALSE` parameter was added to the code chunk to prevent pr
 
 ## Upload Data
 ```{r Data Upload}
-connect_data = read.csv("connectDATA.csv")
+connect_data = read.csv("~/Documents/Github/re_connect_survey/data/connectDATA.csv")
 ```
 
 ## Summary of Data
@@ -60,6 +60,25 @@ pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
   # rough draft of piechart
 
 ```{r Q26 bar/pie}
+
+Q26_data <- read.csv("~/Documents/Github/re_connect_survey/data/Q26_data.csv")
+
+Q26_freq_data <- data.frame(c("Other Priorities", "Lack Subject Knowledge", "Lack Confidence", "Current Syllabus", "Pupil Disinterest", "Department Head", "Available Work Schemes", "Unavailable Resources", "Uncertain of Pedagogical Approach"), c(table(Q26_data[,2]) [names(table(Q26_data[,2])) == "TRUE"],
+                table(Q26_data[,3]) [names(table(Q26_data[,3])) == "TRUE"],
+                table(Q26_data[,4]) [names(table(Q26_data[,4])) == "TRUE"],
+                table(Q26_data[,5]) [names(table(Q26_data[,5])) == "TRUE"],
+                table(Q26_data[,6]) [names(table(Q26_data[,6])) == "TRUE"],
+                table(Q26_data[,7]) [names(table(Q26_data[,7])) == "TRUE"],
+                table(Q26_data[,8]) [names(table(Q26_data[,8])) == "TRUE"],
+                table(Q26_data[,9]) [names(table(Q26_data[,9])) == "TRUE"],
+                table(Q26_data[,10]) [names(table(Q26_data[,10])) == "TRUE"]))
+
+head(Q26_freq_data)
+names(Q26_freq_data)[1] <- "Reasons"
+names(Q26_freq_data)[2] <- "Frequency"
+head(Q26_freq_data)
+pie(Q26_freq_data$Frequency, labels = c("Other Priorities", "Lack Subject Knowledge", "Lack Confidence", "Current Syllabus", "Pupil Disinterest", "Department Head", "Available Work Schemes", "Unavailable Resources", "Uncertain of Pedagogical Approach"))
+
 ```
 
 pie(Q26_freq) 
@@ -67,7 +86,39 @@ pie(Q26_freq)
 
 ```{r Q3 bar/pie}
 
-Q3_data <- read.csv("Q3.csv")
+Q3_data <- read.csv("~/Documents/Github/re_connect_survey/data/Q3.csv")
+
+#head(Q3_data)
+#table(Q3_data [,3:7])
+#pie(table(Q3_data [,3:7]))
+
+Q3_data2 <- Q3_data[,3:7]
+#head(Q3_data2)
+#table(Q3_data2)
+#table(Q3_data2[,1])
+
+### want to take only the count of "True" (1) in each column. Then pie chart of the frequencies
+
+#Q3_data3 <- read.csv("~/Documents/Github/re_connect_survey/data/Q3 copydata.csv")
+
+#table(Q3_data3)
+  #count(Q3_data3, 1)
+#table(Q3_data3) [names(table(Q3_data3)) == 1]
+#table(Q3_data3)
+
+table(Q3_data2[,1]) [names(table(Q3_data2[,1])) == "TRUE"]
+
+test2 <- data.frame(c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"), c(table(Q3_data2[,1]) [names(table(Q3_data2[,1])) == "TRUE"],
+                table(Q3_data2[,2]) [names(table(Q3_data2[,2])) == "TRUE"],
+                table(Q3_data2[,3]) [names(table(Q3_data2[,3])) == "TRUE"],
+                table(Q3_data2[,4]) [names(table(Q3_data2[,4])) == "TRUE"],
+                table(Q3_data2[,5]) [names(table(Q3_data2[,5])) == "TRUE"]))
+head(test2)
+names(test2)[1] <- "Subject"
+names(test2)[2] <- "Frequency"
+head(test2)
+pie(test2$Frequency, labels = c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"))
+
 
 ```
 
@@ -75,7 +126,15 @@ Q3_data <- read.csv("Q3.csv")
 pie(Q3_freq)
   #also not optimal as pie...perhaps bar
 
+  #sum(Q3_data2)
   
+Q3_1factor = as.factor(Q3_data2$Religion)
+table(Q3_1factor)
+   #count(Q3_1factor, "TRUE")
+
+  #test = replace(Q3_1factor, "TRUE", 1)
+  #test
+  #Q3_1factor
 
   - RH: display summaries of responses to key questions for Q22 (syllabus evaluation), Q23, Q24, Q25, Q26, Q27, with subsetting by:
     - Q8 (school type)
@@ -113,4 +172,4 @@ pie(Q3_freq)
 ```{r Correlation 1}
 
 ```
-  - RH: test for correlation between responses to religion questions: Q12-14, Q15-16 and Q21 and responses to Q22, Q23, Q24, Q25, Q27, Q30
+  - RH: test for correlation between responses to religion questions: Q12-14, Q15-16 and Q21 and responses to Q22, Q23, Q27,  [Q24, Q25, Q30]

data/.Rhistory

@@ -1,64 +1,14 @@
-connect_data = read.csv("connectDATA.csv")
-connect_data = read.csv("connectDATA.csv")
-head(connect_data)
-View(connect_data)
-table(connect_data$Q25)
-Q25_frequencies = table(connect_data$Q25)
-Q25_frequencies = table(connect_data$Q25)
-Q26_freq = table(connect_data$Q26)
-Q25_frequencies = table(connect_data$Q25)
-Q26_freq = table(connect_data$Q26)
-Q26_freq
-connect_data = read.csv("connectDATA.csv")
-head(connect_data)
-connect_data = read.csv("connectDATA.csv")
-connect_data = read.csv("connectDATA.csv")
-view(connect_data)
-View(connect_data)
-Q25_frequencies = table(connect_data$Q25)
-Q26_freq = table(connect_data$Q26)
-Q26_freq
-Q25_frequencies = table(connect_data$Q25)
-Q_25_frequencies
-Q26_freq = table(connect_data$Q26)
-Q26_freq
-Q25_frequencies = table(connect_data$Q25)
-Q_25frequencies
-Q26_freq = table(connect_data$Q26)
-Q26_freq
-Q_25frequencies
-Q25_frequencies = table(connect_data$Q25)
-Q25_25frequencies
-Q25_frequencies
-test3 = as.factor(connect_data$Q3, levels = c(1, 2, 3, 4, 5), labels = c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"))
-pie(connect_data$Q25, labels = names(connect_data$Q25))
-pie(Q25_frequencies, labels = names(connect_data$Q25))
-pie(Q25_frequencies, labels = names(c("maybe", "yes", "no")))
-pie(Q25_frequencies, labels = names(connect_data$Q25))
-names(Q25_frequencies = c("Maybe", "No", "Yes"))
-pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
-pie(Q26_freq)
-Q25_frequencies = table(connect_data$Q25)
-Q25_frequencies
-Q26_freq = table(connect_data$Q26)
-Q26_freq
-Q3_freq = table(connect_data$Q3)
-Q25_frequencies = table(connect_data$Q25)
-Q25_frequencies
-Q26_freq = table(connect_data$Q26)
-Q26_freq
-Q3_freq = table(connect_data$Q3)
-Q3_freq
-pie(Q3_freq)
 knitr::opts_chunk$set(echo = TRUE)
-pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
+connect_data = read.csv("connectDATA.csv")
-cor(Q_20, Q_22, data=connect_data)
+read.csv("connectDATA.csv")
-cor(connect_data$Q_20, connect_dataQ_22)
+## Summary of Data
-cor(connect_data$Q_20, connect_data$Q_22)
+Data summary/visualisation with subsetting:
-Q3_data <- read.csv("Q3.csv")
+- RH: display simple summary of data (bar/pie chart) to Q25/26, Q3
+read.csv("connectDATA.csv")
 setwd("~/Documents/GitHub/re_connect_survey/data")
-Q3_data <- read.csv("Q3.csv")
+setwd("~/Documents/GitHub/re_connect_survey/data")
-read.csv("Q3.csv)
+connect_data = read.csv("connectDATA.csv")
-data=read.csv("Q3.csv)
+setwd("~/Documents/GitHub/re_connect_survey/data")
-Q3_data <- read.csv("Q3.csv")
+connect_data = read.csv("connectDATA.csv")
-Q3_data <- read.csv("Q3.csv")
+Q3data = read.csv("Q3.csv")
+connect_data = read.csv("~/gits/re_connect_survey/data/connectDATA.csv")

data/Q26_data.csv

@@ -0,0 +1,86 @@
+Q26,Other Priorities,Lack Subject Knowledge,Lack Confidence,Current Syllabus,Pupil Disinterest,Department Head,Available Work Schemes,Unavailable Resources,Uncertain of Pedagogical Approach
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"7,8,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,3,8,9",TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+"1,5,9",TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+"4,7,9",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE
+"7,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,7",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"3,4",FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"2,4,7,8",FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
+"4,6,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE
+"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
+"1,7,8,9",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"2,3",FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,2",TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"4,6,7",FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE
+"2,7,8",FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"7,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+"7,8,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"4,9",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+"4,7,9",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE
+"2,4,6",FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+"1,7,8",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+"4,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+"4,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
+6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,2,3,8",TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+"4,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+"2,3,4,8",FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"1,7",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"3,8,9",FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+"2,3,4,7",FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+"2,4,7",FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
+"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
+3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+"3,4,7,8",FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
+4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+"2,3,4,7,8,9",FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE
+"4,7",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE

data/Q3 copydata.csv

@@ -0,0 +1,86 @@
+Worldviews,Religion,Theology,Ethics,Philosophy
+2,1,1,1,1
+1,1,1,1,1
+1,1,1,1,1
+2,1,2,2,1
+1,1,1,1,1
+1,1,1,2,1
+1,1,1,1,1
+2,1,1,1,1
+1,1,1,1,1
+1,1,1,1,1
+1,1,1,2,1
+1,1,1,1,1
+1,1,1,1,1
+2,1,2,1,1
+1,1,1,1,1
+2,1,2,2,2
+1,1,1,1,1
+1,1,2,1,1
+2,1,2,2,2
+1,1,1,1,1
+1,1,1,1,1
+1,1,1,1,1
+2,1,1,1,1
+1,1,1,1,1
+1,1,1,1,1
+2,1,2,2,2
+1,1,2,2,2
+1,1,2,2,2
+1,1,2,2,2
+1,1,1,1,1
+2,1,2,2,2
+1,1,1,1,1
+1,1,1,1,2
+1,1,1,1,1
+1,1,1,1,1
+1,1,2,2,2
+1,1,1,1,1
+1,1,1,1,1
+2,1,1,2,1
+1,1,1,1,1
+2,1,2,2,2
+2,1,2,2,2
+2,1,2,2,2
+1,1,2,2,2
+1,1,1,1,1
+1,1,1,1,1
+1,1,1,1,1
+2,1,2,2,2
+2,1,2,2,2
+2,1,2,2,2
+1,1,2,2,2
+2,1,2,2,2
+2,1,2,1,1
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