Bar Chart

plots r

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

```text only r = dnorm(seq(from=-3, to=3, length=15), mean=0, sd=1) barplot(r, col=”red”)

<img src="https://raw.githubusercontent.com/alexeygrigorev/wiki-figures/master/crs/da/barplot-normal.png" alt="Image">


## Multivariate Analysis
Bar Charts can also be used for comparing values of two and more variables
- typically, they are graphical representation of [Contingency Tables](Contingency_Tables)

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](Joint_Distribution) of variables


In R
```carbon
library(openintro)
data(email)

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

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

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

Mosaic Plots

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

they use areas to represent the distribution
e.g.

Sources

Statistics: Making Sense of Data (coursera)
Data Analysis (coursera)
OpenIntro Statistics (book)
http://en.wikipedia.org/wiki/Bar_chart

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