Using ggplot2

Load library:

library(ggplot2)

Scatter plot:

data(iris)
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width)) +
  geom_point(aes(colour=Species))

Line graph:

data(EuStockMarkets)
df <- as.data.frame(EuStockMarkets)
df$x <- 1:nrow(df)
library(reshape2)
df_melt <- melt(df, id.vars = 'x')
ggplot(df_melt, aes(x=x, y=value)) +
  geom_line(aes(colour=variable)) +
  xlab('1991 - 1998')

Bar graph:

data(Orange)
library(dplyr)

##
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
##
##     filter, lag

## The following objects are masked from 'package:base':
##
##     intersect, setdiff, setequal, union

ggplot(group_by(Orange, Tree) %>% summarise(max = max(circumference)), aes(x=Tree, y=max)) + geom_bar(stat="identity")

Histogram:

data(randu)
ggplot(randu, aes(x=x)) + geom_histogram(bins = 50)

Density plot:

data(randu)
ggplot(randu, aes(x=x)) + geom_density(adjust=0.1)

Published: January 23 2017

category:
R 1