mirror of
https://github.com/kidwellj/re_connect_survey.git
synced 2025-01-08 22:22:21 +00:00
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.
This commit is contained in:
parent
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dd66f2f923
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@ -31,7 +31,7 @@ Note that the `echo = FALSE` parameter was added to the code chunk to prevent pr
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## Upload Data
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```{r Data Upload}
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connect_data = read.csv("connectDATA.csv")
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connect_data = read.csv("~/Documents/Github/re_connect_survey/data/connectDATA.csv")
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```
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## Summary of Data
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@ -60,6 +60,25 @@ pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
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# rough draft of piechart
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```{r Q26 bar/pie}
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Q26_data <- read.csv("~/Documents/Github/re_connect_survey/data/Q26_data.csv")
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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"],
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table(Q26_data[,3]) [names(table(Q26_data[,3])) == "TRUE"],
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table(Q26_data[,4]) [names(table(Q26_data[,4])) == "TRUE"],
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table(Q26_data[,5]) [names(table(Q26_data[,5])) == "TRUE"],
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table(Q26_data[,6]) [names(table(Q26_data[,6])) == "TRUE"],
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table(Q26_data[,7]) [names(table(Q26_data[,7])) == "TRUE"],
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table(Q26_data[,8]) [names(table(Q26_data[,8])) == "TRUE"],
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table(Q26_data[,9]) [names(table(Q26_data[,9])) == "TRUE"],
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table(Q26_data[,10]) [names(table(Q26_data[,10])) == "TRUE"]))
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head(Q26_freq_data)
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names(Q26_freq_data)[1] <- "Reasons"
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names(Q26_freq_data)[2] <- "Frequency"
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head(Q26_freq_data)
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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"))
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```
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pie(Q26_freq)
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@ -67,7 +86,39 @@ pie(Q26_freq)
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```{r Q3 bar/pie}
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Q3_data <- read.csv("Q3.csv")
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Q3_data <- read.csv("~/Documents/Github/re_connect_survey/data/Q3.csv")
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#head(Q3_data)
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#table(Q3_data [,3:7])
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#pie(table(Q3_data [,3:7]))
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Q3_data2 <- Q3_data[,3:7]
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#head(Q3_data2)
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#table(Q3_data2)
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#table(Q3_data2[,1])
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### want to take only the count of "True" (1) in each column. Then pie chart of the frequencies
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#Q3_data3 <- read.csv("~/Documents/Github/re_connect_survey/data/Q3 copydata.csv")
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#table(Q3_data3)
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#count(Q3_data3, 1)
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#table(Q3_data3) [names(table(Q3_data3)) == 1]
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#table(Q3_data3)
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table(Q3_data2[,1]) [names(table(Q3_data2[,1])) == "TRUE"]
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test2 <- data.frame(c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"), c(table(Q3_data2[,1]) [names(table(Q3_data2[,1])) == "TRUE"],
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table(Q3_data2[,2]) [names(table(Q3_data2[,2])) == "TRUE"],
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table(Q3_data2[,3]) [names(table(Q3_data2[,3])) == "TRUE"],
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table(Q3_data2[,4]) [names(table(Q3_data2[,4])) == "TRUE"],
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table(Q3_data2[,5]) [names(table(Q3_data2[,5])) == "TRUE"]))
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head(test2)
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names(test2)[1] <- "Subject"
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names(test2)[2] <- "Frequency"
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head(test2)
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pie(test2$Frequency, labels = c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"))
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```
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pie(Q3_freq)
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#also not optimal as pie...perhaps bar
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#sum(Q3_data2)
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Q3_1factor = as.factor(Q3_data2$Religion)
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table(Q3_1factor)
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#count(Q3_1factor, "TRUE")
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#test = replace(Q3_1factor, "TRUE", 1)
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#test
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#Q3_1factor
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- RH: display summaries of responses to key questions for Q22 (syllabus evaluation), Q23, Q24, Q25, Q26, Q27, with subsetting by:
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- Q8 (school type)
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@ -113,4 +172,4 @@ pie(Q3_freq)
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```{r Correlation 1}
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```
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- RH: test for correlation between responses to religion questions: Q12-14, Q15-16 and Q21 and responses to Q22, Q23, Q24, Q25, Q27, Q30
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- RH: test for correlation between responses to religion questions: Q12-14, Q15-16 and Q21 and responses to Q22, Q23, Q27, [Q24, Q25, Q30]
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@ -1,64 +1,14 @@
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connect_data = read.csv("connectDATA.csv")
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connect_data = read.csv("connectDATA.csv")
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head(connect_data)
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View(connect_data)
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table(connect_data$Q25)
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Q25_frequencies = table(connect_data$Q25)
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Q25_frequencies = table(connect_data$Q25)
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Q26_freq = table(connect_data$Q26)
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Q25_frequencies = table(connect_data$Q25)
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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connect_data = read.csv("connectDATA.csv")
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head(connect_data)
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connect_data = read.csv("connectDATA.csv")
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connect_data = read.csv("connectDATA.csv")
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view(connect_data)
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View(connect_data)
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Q25_frequencies = table(connect_data$Q25)
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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Q25_frequencies = table(connect_data$Q25)
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Q_25_frequencies
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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Q25_frequencies = table(connect_data$Q25)
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Q_25frequencies
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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Q_25frequencies
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Q25_frequencies = table(connect_data$Q25)
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Q25_25frequencies
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Q25_frequencies
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test3 = as.factor(connect_data$Q3, levels = c(1, 2, 3, 4, 5), labels = c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"))
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pie(connect_data$Q25, labels = names(connect_data$Q25))
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pie(Q25_frequencies, labels = names(connect_data$Q25))
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pie(Q25_frequencies, labels = names(c("maybe", "yes", "no")))
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pie(Q25_frequencies, labels = names(connect_data$Q25))
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names(Q25_frequencies = c("Maybe", "No", "Yes"))
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pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
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pie(Q26_freq)
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Q25_frequencies = table(connect_data$Q25)
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Q25_frequencies
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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Q3_freq = table(connect_data$Q3)
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Q25_frequencies = table(connect_data$Q25)
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Q25_frequencies
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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Q3_freq = table(connect_data$Q3)
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Q3_freq
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pie(Q3_freq)
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knitr::opts_chunk$set(echo = TRUE)
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pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
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cor(Q_20, Q_22, data=connect_data)
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cor(connect_data$Q_20, connect_dataQ_22)
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cor(connect_data$Q_20, connect_data$Q_22)
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Q3_data <- read.csv("Q3.csv")
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connect_data = read.csv("connectDATA.csv")
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read.csv("connectDATA.csv")
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## Summary of Data
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Data summary/visualisation with subsetting:
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- RH: display simple summary of data (bar/pie chart) to Q25/26, Q3
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read.csv("connectDATA.csv")
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setwd("~/Documents/GitHub/re_connect_survey/data")
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Q3_data <- read.csv("Q3.csv")
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read.csv("Q3.csv)
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data=read.csv("Q3.csv)
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Q3_data <- read.csv("Q3.csv")
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Q3_data <- read.csv("Q3.csv")
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setwd("~/Documents/GitHub/re_connect_survey/data")
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connect_data = read.csv("connectDATA.csv")
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setwd("~/Documents/GitHub/re_connect_survey/data")
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connect_data = read.csv("connectDATA.csv")
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Q3data = read.csv("Q3.csv")
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connect_data = read.csv("~/gits/re_connect_survey/data/connectDATA.csv")
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86
data/Q26_data.csv
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86
data/Q26_data.csv
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Q26,Other Priorities,Lack Subject Knowledge,Lack Confidence,Current Syllabus,Pupil Disinterest,Department Head,Available Work Schemes,Unavailable Resources,Uncertain of Pedagogical Approach
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"7,8,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
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3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,3,8,9",TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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"1,5,9",TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
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"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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"4,7,9",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE
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"7,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,7",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"3,4",FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"2,4,7,8",FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
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"4,6,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE
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"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
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"1,7,8,9",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
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1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"2,3",FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,2",TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"4,6,7",FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE
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"2,7,8",FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"7,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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"7,8,9",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
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1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"4,9",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
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"4,7,9",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE
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"2,4,6",FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
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"1,7,8",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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"4,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"7,8",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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"4,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
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"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
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6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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1,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,2,3,8",TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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"4,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
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"2,3,4,8",FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"1,7",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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"1,4",TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"3,8,9",FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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"2,3,4,7",FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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"2,4,7",FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
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"4,7,8",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
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3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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"3,4,7,8",FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE
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4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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"2,3,4,7,8,9",FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE
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"4,7",FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
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86
data/Q3 copydata.csv
Normal file
86
data/Q3 copydata.csv
Normal file
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Worldviews,Religion,Theology,Ethics,Philosophy
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2,1,1,1,1
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1,1,1,1,1
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1,1,1,1,1
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2,1,2,2,1
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1,1,1,1,1
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1,1,1,2,1
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1,1,1,1,1
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2,1,1,1,1
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1,1,1,1,1
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1,1,1,1,1
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1,1,1,2,1
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1,1,1,1,1
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1,1,1,1,1
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2,1,2,1,1
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1,1,1,1,1
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2,1,2,2,2
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1,1,1,1,1
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1,1,2,1,1
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2,1,2,2,2
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||||
1,1,1,1,1
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||||
1,1,1,1,1
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||||
1,1,1,1,1
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||||
2,1,1,1,1
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||||
1,1,1,1,1
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||||
1,1,1,1,1
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||||
2,1,2,2,2
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||||
1,1,2,2,2
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||||
1,1,2,2,2
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||||
1,1,2,2,2
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||||
1,1,1,1,1
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||||
2,1,2,2,2
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||||
1,1,1,1,1
|
||||
1,1,1,1,2
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||||
1,1,1,1,1
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||||
1,1,1,1,1
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||||
1,1,2,2,2
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||||
1,1,1,1,1
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||||
1,1,1,1,1
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||||
2,1,1,2,1
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||||
1,1,1,1,1
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2,1,2,2,2
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2,1,2,2,2
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2,1,2,2,2
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1,1,2,2,2
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1,1,1,1,1
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1,1,1,1,1
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1,1,1,1,1
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2,1,2,2,2
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2,1,2,2,2
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2,1,2,2,2
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1,1,2,2,2
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2,1,2,2,2
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2,1,2,1,1
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1,1,2,1,1
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2,1,1,1,1
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1,1,1,2,2
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2,1,2,2,2
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1,1,1,2,1
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1,1,1,1,1
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2,1,2,2,2
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2,1,1,1,1
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1,1,2,2,2
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1,1,1,1,1
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1,1,1,1,1
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2,1,1,1,1
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1,1,2,2,2
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1,1,2,2,2
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2,2,2,1,2
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1,1,1,1,1
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2,1,2,2,2
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1,1,2,1,1
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1,1,2,2,2
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1,1,2,2,2
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1,1,2,2,2
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2,1,2,2,2
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2,1,1,1,1
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1,1,2,2,2
|
||||
2,1,2,2,2
|
||||
2,1,2,2,2
|
||||
2,1,2,2,2
|
||||
1,1,2,1,2
|
||||
1,2,2,2,1
|
||||
1,1,2,2,2
|
||||
1,1,2,1,1
|
||||
2,1,2,2,2
|
|
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Reference in a new issue