```
## Title: plot-barplot-1
## Author: Paul Johnson <pauljohn at ku.edu>
## Date posted: 2013-02-05
## Description. Basic exploration of barplot
## One big hassle is that R barplot() assumes we
## provide the table of bar heights. We get one
## "set" of bars for each row in the table.
## Start easy:
## Suppose we know how high we want the bars.
##
myBars <- c(0.2, 0.4, 0.5)
barplot(height = myBars)
```

```
## fiddle the width of the bars
barplot(height = myBars, width = c(0.2, 1, 0.3))
```

```
## Sometimes we have 2 rows of data to plot. That
## is a matrix
myBars <- matrix(c(0.2, 0.4, 0.5, 0.33, 0.7, 0.1), nrow = 2, byrow = TRUE)
barplot(height = myBars)
```

```
## I rather have side-by-side plot
barplot(height = myBars, beside = TRUE)
```

```
## We will play games with barplot, but first
## "HOW DO WE GET THE NUMBERS WE WANT TO PLOT?"
## Well, it depends on what you are trying to show.
## Answer: I usually use a 2 step process.
## Step 1. table() gets the counts
## Step 2. prop.table() converts that to proportions.
## Let's make up some categorical variables for testing
## Here is 100 scores for x1
set.seed(234234)
x1 <- sample(c("Red","Black","Blue"), size = 100, replace = TRUE)
x2 <- sample(c("male","female"), size = 100, replace = TRUE)
x1 <- as.factor(x1)
x2 <- as.factor(x2)
plot(x2, x1)
```

```
## I want a side-by-side barplot instead.
## So we have to manufacture the data ourselves
table(x2, x1)
```

```
## x1
## x2 Black Blue Red
## female 21 13 15
## male 20 17 14
```

```
t1 <- table(x2, x1)
t1.prop <- prop.table(t1, margin = 2)
## See: column proportions.
t1.prop
```

```
## x1
## x2 Black Blue Red
## female 0.5122 0.4333 0.5172
## male 0.4878 0.5667 0.4828
```

```
barplot(height = t1.prop, beside = TRUE)
```

```
## Sometimes you want the average value of a variable
## to serve as the height of the bars. R leaves us (too) many
## different ways to get that. I like "aggregate".
## Lets make up a numeric variable
x3 <- rnorm(100, m = 40, s = 20)
## We need the result to be a table, with one column for male, one
## for female, and rows for Red Black Blue
## My first instinct was to calculate like this
aggregate(x3, by = list(x1,x2), mean)
```

```
## Group.1 Group.2 x
## 1 Black female 37.00
## 2 Blue female 44.43
## 3 Red female 45.39
## 4 Black male 44.82
## 5 Blue male 50.72
## 6 Red male 43.63
```

```
## But the data is not formatted in a way that easily
## goes into a table.
## The gdata package has a nice function that does it
## called aggregate.table, but if you run it like so:
## library(gdata)
## aggregate.table(x3, by1 = x1, by2 = x2, mean)
##
## it says the function is deprecated, and instead it
## suggests:
tapply(X = x3, INDEX = list(x1, x2), FUN = mean)
```

```
## female male
## Black 37.00 44.82
## Blue 44.43 50.72
## Red 45.39 43.63
```

```
## That looks ok
myBars <- tapply(X = x3, INDEX = list(x1, x2), FUN = mean)
barplot(height = myBars)
```

```
barplot(height = myBars, beside = TRUE)
## Lets fiddle with the bar labels
##
barplot(height = myBars, beside = TRUE, names.arg = colnames(myBars))
```

```
##
barplot(height = myBars, beside = TRUE, names.arg = c(row.names(myBars),row.names(myBars)))
## I'd like to get both labels.
## Unfortunately, if we want to add labels for the groups.
## But we don't know where to place the labels. For example
mtext(colnames(myBars), side = 1, line = 2, at = c(1,2))
## This is no good as well.
mtext(colnames(myBars), side = 1, line = 2, at = c(4,8))
```

```
## So, we have to ask the barplot for its coordinate system,
## like this:
bp1 <- barplot(height = myBars, beside = TRUE, names.arg = c(row.names(myBars),row.names(myBars)))
## Inspect bp1, it is just positions on the horizontal scale
bp1
```

```
## [,1] [,2]
## [1,] 1.5 5.5
## [2,] 2.5 6.5
## [3,] 3.5 7.5
```

```
## The positions of the bars are there, but you have to look at the layout
## for a while to make sense of it.
## The numbers indicate that the "center" for each group of bars is found at
## positions 2.5 and 6.5.
mtext(colnames(myBars), side = 1, line = 3, at = c(2.5, 6.5))
```

```
## The end
##
##
##
##
## But wait, there's more. Apparently I wrote the exact same
## example before. And forgot. How silly.
## Anyway, in case more examples help.
## Paul Johnson
## barplot data input. What a Hassle.
## 2011-06-22
## Here's a case where it is best to understand what R wants,
## before trying to work your example. Or end goal is to
## make a grouped barplot.
## Start easy, give barplot one column
x <- c(.14, .23, .66)
barplot(x)
```

```
## table or aggregate can produce same kind of thing
## Get some small integers in a data frame
rawdata <- rpois(200, lambda = 2)
x <- table(rawdata)
## Convert to proportions
x <- x / sum(x)
barplot(x)
```

```
## Now work on richer information
## Suppose the input is a matrix with 2 columns
x <- matrix( c(.14, .23, .66, .44, .53, .55), ncol = 2)
## look at x
x
```

```
## [,1] [,2]
## [1,] 0.14 0.44
## [2,] 0.23 0.53
## [3,] 0.66 0.55
```

```
barplot(x)
```

```
## I hate stacked charts
## I think this would be called a grouped bar plot.
barplot(x, beside = TRUE)
```

```
## That has no names because my input table had no names.
## Think of the columns as sex
colnames(x) <- c("Male","Female")
x
```

```
## Male Female
## [1,] 0.14 0.44
## [2,] 0.23 0.53
## [3,] 0.66 0.55
```

```
## Row represents cities
rownames(x) <- c("NY","LA","SF")
x
```

```
## Male Female
## NY 0.14 0.44
## LA 0.23 0.53
## SF 0.66 0.55
```

```
barplot(x, beside = TRUE)
```

```
## How to decorate that?
## Name individual bars? OK:
barplot(x, beside = TRUE, names.arg = c("A","B","C","D","E","F"))
```

```
## Instead, lets go for two-layered output.
## Grab the output from barplot in order
## to see where bars are positioned.
bp1 <- barplot(x, beside = TRUE)
mtext(text = c("first","second","third"), side = 1, line = 0, at= bp1[,1])
mtext(text = c("fourth","fifth","sixth"), side = 1, line = 0, at = bp1[ ,2])
```

```
## Instead, lets write vertically inside the bars!
## Let's write at one-half of the column's height (that's why
## I have 0.5*x in the text commands
bp1 <- barplot(x, beside = TRUE)
text( bp1[ ,1], 0.5*x[ ,1], c("first","second","third"))
```

```
## srt will rotate text strings by degree
bp1 <- barplot(x, beside = TRUE)
text( bp1[ ,1], 0.5*x[ ,1], c("first","second","third"), srt = 66)
```

```
bp1 <- barplot(x, beside = TRUE)
text( bp1[ ,1], 0.5*x[ ,1], c("first","second","third"), srt = 90)
text( bp1[ ,2], 0.5*x[ ,2], c("first","second","third"), srt = 90)
```

```
### Note problem: Fill colors in legend not correct
bp1 <- barplot(x, beside = TRUE)
legend("topleft", legend = c("first","second","third"), fill = c(1,2,3))
```

```
### Need to figure out what colors barplot uses
### I believe it is drawing colors from the function "gray.colors"
gray.colors(3)
```

```
## [1] "#4D4D4D" "#AEAEAE" "#E6E6E6"
```

```
bp1 <- barplot(x, beside = TRUE)
legend("topleft", legend = c("first","second","third"), fill= gray.colors(3))
```

```
### So, what do you get out of this?
### barplot wants you to give it a matrix, one column per group of bars.
### So if your data is like this
### data
### id sex region iq age
### 01 M W 122 12
### 02 F W 111 08
### 03 M E 89 07
### 04 F S 144 19
### 05 F N 123 44
### You want a barplot that shows this the
## mean "iq" subdivided by sex, then region
## | | |
## | | | |
## | | | | | | | |
## E W N S E W N S
## Male Female
## So we need a matrix with 2 columns, Male and Female,
## Rows for regions and cells are means.
## First, manufacture the data
id <- 1:1000
sex <- sample(x= c("M","F"), size = 1000, replace = T)
region <- sample(x= c("E","W","N","S"), size = 1000, replace = T)
iq <- rnorm(1000, m = 100, sd = 15)
age <- rpois(1000, lambda = 20)
dat <- data.frame(id, sex, region, iq, age)
## Use R's "aggregate" go produce that
aggdat <- aggregate(dat$iq, by = list(sex = sex,region = region), FUN= mean)
aggdat
```

```
## sex region x
## 1 F E 99.36
## 2 M E 100.40
## 3 F N 101.35
## 4 M N 100.23
## 5 F S 96.31
## 6 M S 100.23
## 7 F W 99.07
## 8 M W 99.13
```

```
colnames(aggdat)[3] = "meaniq"
## aggdat is in the "long" format, but we need the "wide" format
x <- unstack(aggdat, meaniq ~ sex )
x <- as.matrix(x)
barplot(x, beside = TRUE)
```

```
## And I think that's all I need to show
```