Solved – questionnaire stacked bar plot with R

data visualizationrsurvey

I have a file containing questionnaire data (categorical data, 4 possible values). I have imported this to R to get the corresponding data frame. Now I've done some messy things with the table function to obtain a new data frame which contains instead of the whole data listing only the frequency counts in right order of every variable, i.e. question in the questionnaire (maybe someone could tell me a good way to do this too).

What I would like to obtain a graphical visualisation of the frequencies as a stacked bar plot. That's what it should look like: for each question, for stacked bars, the size of each bar corresponding to the frequency count (the frequency data in the transformed data frame that I constructed is already ordered).
Is this possible?
Thanks in advance!

Best Answer

take a look at Hadley Wickam's ggplot2 package. With it, all the munging you did to get frequencies may have been wasted. See his examples on the page I linked. If you want to use your pre-generated frequencies, use stat='identity'.

Making up some sample data....

dat<-data.frame(sample(letters[1:4],1000,replace=T),question=rep(c('q1','q2','q3','q4'),each=250))
qplot(question,data=dat,geom='bar',fill=answer)

Related Solutions

Solved – Stacked bar plot

With 60 distinct categories, I feel you may have a hard time making that an effective graphic. You may want to consider a regular bar-chart that is sorted in ascending or descending order. Whether or not these are counts or percentages is up to you. Maybe something like this:

library(ggplot2)
df$names <- reorder(df$names, -df$freq) #Reorders into ascending order
qplot(x = names, y = freq, data = df, geom = "bar") + coord_flip()

EDIT:

To make a stacked bar chart with ggplot, we set the x = 1 since we will have only one column. We will use the fill argument to add color:

qplot(x = factor(1), y = freq, data = df, geom = "bar", fill = names)

Also of interest: a stacked bar chart is pretty darn close to being a pie chart. You can transform the coordinate system of ggplot charts with + coord_polar(theta = "y") to make a pie chart from the stacked bar chart above.

Solved – Casting multidimensional data in R into a data frame

I'm not sure I followed the PS part of your question, but maybe this will get you on the right path. The trick is to use melt() to get the data into long format, then use ddply() to group by:

library(plyr)
library(reshape2)
iw <- read.csv("http://dl.dropbox.com/u/1156404/wightCrimRecords.csv")
iw.m <- melt(iw, id.vars = "sex", measure.vars = "Offence_type")
ddply(iw.m, "sex", function(x) as.data.frame(prop.table(table(x$value))))

Gives us:

          sex                                      Var1        Freq
1      Female                                  Burglary 0.004950495
2      Female                 Criminal Damage and Arson 0.017326733
3      Female                          Driving Offences 0.371287129
...
50      Other                           Supply of drugs 0.000000000
51      Other                             Vehicle Crime 0.000000000
52      Other                             Violent Crime 0.000000000

EDIT - after reading the PS again, I think this is what you had in mind:

iw.m <- melt(iw, id.vars = c("sex", "AGE"), measure.vars = "Offence_type")
ddply(iw.m, c("sex", "AGE"), function(x) as.data.frame(prop.table(table(x$value))))

           sex   AGE                                      Var1        Freq
1       Female 18-24                                  Burglary 0.011764706
2       Female 18-24                 Criminal Damage and Arson 0.047058824
3       Female 18-24                          Driving Offences 0.188235294
....

You can obviously continue to add ID variables which then get passed into plyr to group on to any level of detail that is sufficient for your purposes.

Best Answer

Related Solutions

Solved – Stacked bar plot

Solved – Casting multidimensional data in R into a data frame

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