Reputation: 436
ID <- 1:10
group <- c(1,1,1,2,2,2,3,3,3,3)
var1 <- c(6:15)
var2 <- c(7:16)
var3 <- c(6:11, NA, NA, NA, NA)
var4 <- c(4:9, NA, NA, NA, NA)
data <- data.frame(ID, group, var1, var2, var3, var4)
library(dplyr)
data %>% group_by(group) %>% boxplot(var1, var2)
The last line does not work as i wish. The idea is to get 4 boxplots in one graphic. Two for each variable. Maybe i need to use ggplot2?
Upvotes: 8
Views: 27651
Reputation: 7063
Although quite late, a found a great base-R solution here
# Create some data, e.g. from https://en.wikipedia.org/wiki/One-way_analysis_of_variance#Example
df <- as.data.frame(matrix(c(6, 8, 13, 8, 12, 9, 4, 9, 11, 5, 11, 8, 3, 6, 7, 4, 8, 12),ncol = 3, byrow = TRUE))
df <- reshape(data = df, direction = "long", idvar=1:3, varying=1:3, sep = "", timevar = "Treatment")
df$Treatment <- as.factor(df$Treatment)
rownames(df) <- NULL
par(mfrow = c(2, 1))
par(mar=c(1,4,4,2) + 0.1) # mar=c(b,l,t,r)
boxplot(V ~ Treatment, data = df, xlab = NULL, xaxt = "n",
ylab = "V", main = "One-way anova with 3 different levels of one factor")
stripchart(V ~ Treatment, # Points
data = df, # Data
method = "jitter", # Random noise
pch = 19, # Pch symbols
col = 4, # Color of the symbol
vertical = TRUE, # Vertical mode
add = TRUE) # Add it over
par(mar=c(5,4,0,2) + 0.1)
boxplot(V ~ Treatment, data = df, xlab = "Treatment",
ylab = "V", main = NULL)
stripchart(V ~ Treatment, # Points
data = df, # Data
method = "overplot", # Random noise
pch = 19, # Pch symbols
col = 4, # Color of the symbol
vertical = TRUE, # Vertical mode
add = TRUE) # Add it over
par(mfrow = c(1, 1))
Upvotes: 0
Reputation: 13807
You need to reorganize the data if you want to get both variables in the same plot. Here is a ggplot2
solution:
# load library
library(ggplot2)
library(tidyr)
library(ggthemes)
# reorganize data
df <- gather(data, "ID","group")
#rename columns
colnames(df) <- c("ID","group","var","value")
# plot
ggplot(data=df) +
geom_boxplot( aes(x=factor(group), y=value, fill=factor(var)), position=position_dodge(1)) +
scale_x_discrete(breaks=c(1, 2, 3), labels=c("A", "B", "C")) +
theme_minimal() +
scale_fill_grey()
Making boxplots with the same width is a whole different question (solution here), but one simple alternative would be like this:
# recode column `group` in the `data.frame`.
df <- transform(df, group = ifelse(group==1, 'A', ifelse(group==2, 'B', "C")))
# plot
ggplot(data=df) +
geom_boxplot( aes(x=factor(var), y=value, fill=factor((var))), position=position_dodge(1)) +
geom_jitter(aes(x=factor(var), y=value, color=factor((var)))) +
facet_grid(.~group, scales = "free_x") +
theme_minimal()+
scale_fill_grey() +
theme(axis.text.x=element_blank(),
axis.title.x=element_blank(),
axis.ticks=element_blank())
Upvotes: 13
Reputation: 19454
You might try melting the data frame (mentioned in comment by @lukeA) first and then sticking to base graphics. ggplot2
or lattice
are other good options.
library(reshape2)
DF <- melt(data, id.vars = c("ID", "group"), measure.vars = c("var1", "var2"))
boxplot(value ~ group + variable, DF)
Alternate lattice
code, also using DF
:
bwplot(~ value | variable + group, data = DF)
Alternate ggplot2
code, also using DF
:
ggplot(DF, aes(x = factor(group), y = value, fill = variable)) + geom_boxplot()
Upvotes: 5