I have a data frame like this:
__________
| | sums |
|---+------|
| a | 122 |
|---+------|
| b | 23 |
|---+------|
| c | 321 |
|__________|
*Notice "a","b" and "c" are row names.
I would like to see a plot like this:
___
300 -| | |
200 -| ___ | |
100 -| | | ___ | |
0 -|_|___|_|___|_|___|______
a b c
How can I accomplish that?
Add the rownames as a column in the data frame and then plot. Here's an example with the built-in mtcars data frame:
library(tibble)
library(ggplot2)
ggplot(rownames_to_column(mtcars[1:3,], var="Model"),
aes(x=Model, y=mpg)) +
geom_bar(stat="identity") +
theme(axis.text.x=element_text(angle=-90, vjust=0.5, hjust=0))
ggplot(df.m, aes(value)) + geom_histogram(aes(fill=variable), position="dodge") How can I combine the two?
ggplot(cbind(Model = rownames(mtcars), mtcars)[1:3, ], ... not sufficient?
tidyverse, so I thought I'd drop in on tibble before heading back to my own dimension.Just try this:
df
sums
a 122
b 23
c 321
library(ggplot2)
ggplot(df, aes(x=rownames(df), sums)) + geom_bar(stat='identity')
