Bar Chart

Bar Chart, or Bar Plot or Bar Graph

  • This is a Plot that can be useful for Exploratory Data Analysis
  • It's a graphical representation of Frequency Tables
    • It shows the values of your data set with bars
    • height of the bar is proportional to the value it represents
    • so the variables you plot must be Quantitative Variables


In R

To create a bar chart in R

  • use barplot command
r = dnorm(seq(from=-3, to=3, length=15), mean=0, sd=1)
barplot(r, col="red")

barplot-normal.png


Multivariate Analysis

Bar Charts can also be used for comparing values of two and more variables

There are the following types of bar charts:

  • Side-by-side bar chart
    • bars are put near each other
  • Stacked (Segmented) bar chart
    • shows more information than other types - the total size, the proportion, etc
  • Proportional stacked bar chart
    • standardized version of the stacked bar chart
    • makes it easier to see the Joint Distribution of variables


In R

library(openintro)
data(email)

# stacked
t = table(email$spam, email$number)
pal = c('yellow2', 'skyblue2')
barplot(t, col=pal, beside=F)

# proportional
t.prop = rbind(t[1,] / colSums(t),
               t[2,] / colSums(t))
pal = c('yellow2', 'skyblue2')
barplot(t.prop, col=pal, beside=F)

# side-by-side
barplot(t, col=pal, beside=T)

9c426982b95f4067bd7bca7f6d8cdca0.png 85998f4188884e8b8904dfaab16a3067.png 56810cd554124b3e90a5febbe4ee8ffd.png


Mosaic Plots

They can represent the information about the distribution better than proportional bar charts

  • they use areas to represent the distribution
  • e.g. 14fab1399fb444f58e33a7032a6bef82.png


Sources