My dataset looks like this:
| V1 | V2 | V3 | V4 |
|---|---|---|---|
| 1 | 0 | 0 | 1 |
| 0 | 1 | 0 | 0 |
| 0 | 1 | 1 | 0 |
| 1 | 0 | 1 | 1 |
| 0 | 0 | 0 | 0 |
| 1 | 0 | 1 | 1 |
I want to plot a count of the occurrences of 1s per variable, but on one single bar chart (4 bars). I can plot this for each individual variable using ggplot:
ggplot(df,aes(x = v1)) +
geom_bar(stat = 'count')
, but to plot them all on one graph I seem to need to turn my dataframe sideways, but then I can't figure out how to calculate the count of 1s.
Any help would be much appreciated!
We get the sum by column with summarise/across, reshape to long with pivot_longer and then use ggplot
library(dplyr)
library(tidyr)
library(ggplot2)
df %>%
summarise(across(everything(), sum)) %>%
pivot_longer(cols = everything()) %>%
ggplot(aes(x = name, y = value, fill = name)) +
geom_col() +
coord_flip()
df <- structure(list(V1 = c(1L, 0L, 0L, 1L, 0L, 1L), V2 = c(0L, 1L,
1L, 0L, 0L, 0L), V3 = c(0L, 0L, 1L, 1L, 0L, 1L), V4 = c(1L, 0L,
0L, 1L, 0L, 1L)), class = "data.frame", row.names = c(NA, -6L
))
A base R option using barplot + stack + colSums
barplot(values ~ ind, stack(colSums(df)))
or a more concise way (thank @akrun for the comments)
barplot(colSums(df))
