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Fixed Error in Q26 Freq data

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Fixed the error in the code creating data for Q 26 frequencies - correct columns now extracted.
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rehughes07 2022-01-28 10:20:59 +00:00
parent 89a5ee72dd
commit 89b723bd6b
1 changed files with 33 additions and 3 deletions
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36
Connect Project R Markdown.Rmd
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@ -46,15 +46,16 @@ pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"), col = coul3)
Q26_data <- read.csv("./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"],
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[,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"]))
table(Q26_data[,10]) [names(table(Q26_data[,10])) == "TRUE"],
table(Q26_data[,11]) [names(table(Q26_data[,11])) == "TRUE"]))
head(Q26_freq_data)
names(Q26_freq_data)[1] <- "Reasons"
@ -66,7 +67,36 @@ pie(Q26_freq_data$Frequency, labels = c("Other Priorities", "Lack Subject Knowle
```
#```{r test why error in lines above}
Q26_data <- read.csv("./data/Q26_data.csv")
name_test <- c("Other Priorities", "Lack Subject Knowledge", "Lack Confidence", "Current Syllabus", "Pupil Disinterest", "Department Head", "Available Work Schemes", "Unavailable Resources", "Uncertain of Pedagogical Approach")
extractQ26_test <- 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"])
table(Q26_data[,2]) [names(table(Q26_data[,2])) == "TRUE"]
table(Q26_data[,3]) [names(table(Q26_data[,3])) == "TRUE"]
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"]))
```
pie(Q26_freq)
#very messy as a pie chart - split by type? Or is it important to see crossover