3 Barplot

In this chapter, we introduce the barplot in ggplot2 style.

3.1 basic barplot

We use diamonds dataset for illustration.

library(ggplot2)
library(dplyr)
library(patchwork)

data("diamonds")
diamonds

## # A tibble: 53,940 × 10
##    carat cut       color clarity depth table price     x     y     z
##    <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
##  1  0.23 Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
##  2  0.21 Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
##  3  0.23 Good      E     VS1      56.9    65   327  4.05  4.07  2.31
##  4  0.29 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
##  5  0.31 Good      J     SI2      63.3    58   335  4.34  4.35  2.75
##  6  0.24 Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
##  7  0.24 Very Good I     VVS1     62.3    57   336  3.95  3.98  2.47
##  8  0.26 Very Good H     SI1      61.9    55   337  4.07  4.11  2.53
##  9  0.22 Fair      E     VS2      65.1    61   337  3.87  3.78  2.49
## 10  0.23 Very Good H     VS1      59.4    61   338  4     4.05  2.39
## # … with 53,930 more rows

Count the number of diamonds in each cut group.

df1 <- diamonds %>% 
  count(cut)
df1

## # A tibble: 5 × 2
##   cut           n
##   <ord>     <int>
## 1 Fair       1610
## 2 Good       4906
## 3 Very Good 12082
## 4 Premium   13791
## 5 Ideal     21551

We use stat="identity" mode to generate barplot

ggplot(df1, aes(x=cut, y=n)) +
  geom_bar(stat="identity")

3.2 With color

ggplot(df1, aes(x=cut, y=n)) +
  geom_bar(aes(fill=cut), stat="identity")

Using fill as grouping variable

df2 <- diamonds %>% 
  count(cut, clarity)
df2

## # A tibble: 40 × 3
##    cut   clarity     n
##    <ord> <ord>   <int>
##  1 Fair  I1        210
##  2 Fair  SI2       466
##  3 Fair  SI1       408
##  4 Fair  VS2       261
##  5 Fair  VS1       170
##  6 Fair  VVS2       69
##  7 Fair  VVS1       17
##  8 Fair  IF          9
##  9 Good  I1         96
## 10 Good  SI2      1081
## # … with 30 more rows

ggplot(df2, aes(x=cut, y=n)) +
  geom_bar(aes(fill=clarity), stat="identity", position="identity")

3.2.1 adjust position

There are two other more position options: “fill” and “dodge”

p1 <- ggplot(df2, aes(x=cut, y=n)) +
  geom_bar(aes(fill=clarity), stat="identity", position="fill")

p2 <- ggplot(df2, aes(x=cut, y=n)) +
  geom_bar(aes(fill=clarity), stat="identity", position="dodge")

p1 + p2

3.3 Horizontal barplot

ggplot(df1, aes(x=cut, y=n)) +
  geom_bar(aes(fill=cut), stat="identity") +
  coord_flip()

3.4 Circular barplot

ggplot(df1, aes(x=cut, y=n)) +
  geom_bar(aes(fill=cut), stat="identity", width=1) +
  theme(aspect.ratio = 1) +
  labs(x = NULL, y = NULL) +
  coord_polar()