Bar chart with X axis divided by observations under same variable?

isla42 · January 8, 2023, 7:59pm

I've used the predict() function to estimate the value of the dependent variable, for two groups, with a few other conditions specified. I want to represent values for these two groups side-by-side in a graph and guess a bar chart is the best way to go:

barplot(brazil$reelected, brazil$corruption,
        names.arg = c("Not reelected", "Reelected"),
        main = "Corruption level by whether not mayor reelected",
        xlab = "Whether not mayor reelected",
        xlim = c(0,20),
        ylab = "Corruption")

brazil is the dataset name. I would like the Y axis to be the dependent variable (corruption) and the two bars to represent levels of corruption for two groups - one is 'not reelected' (or reelected == 0) and 'reelected' (or reelected == 1). When I run this, I get the error message:

Error in barplot.default(brazil$reelected, brazil$corruption, names.arg = c("Not reelected",  : 
  incorrect number of names

Any thoughts on how I go about this?

Thank you!

jrkrideau · January 8, 2023, 8:40pm

Can you supply a bit of sample data? A handy way to supply some sample data is the dput() function. In the case of a large dataset something like dput(head(mydata, 100)) should supply the data we need. Just do dput(mydata) where mydata is your data. Copy the output and paste it here.

M_AcostaCH · January 9, 2023, 5:26am

This said that the number of arguments in names.arg()is different. Maybe more of 2 argument.
Is better help if you put a reproducible example.

isla42 · January 9, 2023, 10:47am

My apologies, just learning about the forum - knowing how to ask for help feels essential here

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jrkrideau · January 9, 2023, 4:10pm

It can help. It gets easier after the first 50 years.

Here are a couple of useful sources: Minimal Reproducible Example and Tips for writing questions.

I am not sure that I understand what you want but I reduced the data set to a 4 X 3 table and plotted that.

dat3 structure(list(status = c("No", "No", "Yes", "Yes"), corrupt = c("No", 
"Yes", "No", "Yes"), N = c(33L, 39L, 9L, 19L)), row.names = c(NA, 
4L), class = "data.frame")

Isla1

However I did this using the data.table package which is just a bit different than most of the rest of R so my code may [will?] look very weird to you. If I am on the right track, I can translate the code into standard and/or tidyverse code or leave you to explore data.table which has some very interesting features.

I named your original sample data set dat1

# read in data as data.frame called "dat1"

library(ggplot2)
library(data.table)

setDT(dat1) # convert to data.table. 

# Create two new binary variables based on "reelected" & "corruption" variables
dat1[ , status := fifelse( reelected == 1, "Yes", "No")]
dat1[ , corrupt := fifelse(corruption == 0, "No", "Yes")]

 # This can be done as one step
dat2  <- dat1[, .(status, corrupt)]
dat3  <- dat2[, .N, by = .(status, corrupt)]

## plot
ggplot(dat3, aes(status, N, fill = corrupt)) + geom_bar(stat = "identity", position=position_dodge()) +
  ggtitle( "Corruption level by whether or not mayor reelected") + xlab("Reelection Status") +
  ylab("Number of Mayors")

nirgrahamuk · January 9, 2023, 4:29pm

I am simply assuming that corruption is some quantity that you desire to sum up for each group (0/1)

I believe in base R, one would do :

(braz_smry <- aggregate(corruption ~ reelected,
                        data=brazil,
                        FUN = sum))

barplot(height = braz_smry$corruption,
        names.arg = c("Not reelected", "Reelected"),
        main = "Corruption level by whether not mayor reelected",
        xlab = "Whether not mayor reelected",
        ylab = "Corruption",
        ylim=c(0,2000))

system · February 20, 2023, 4:29pm

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