ggplot for loop outputs all the same graph - r

I've written a for loop which goes through the columns of a dataframe and produces a graph for each column using ggplot. The problem is the graphs that are output are all the same - they're all graphs of the final column.
The code I've used is:
library(gridExtra)
library(ggplot2)
test1 <- c("Person1","Person2","Person3","Person4","Person5")
test2 <- as.data.frame(c(1,2,3,4,5))
test3 <- as.data.frame(c(2,2,2,2,2))
test4 <- as.data.frame(c(1,3,5,3,1))
test5 <- as.data.frame(c(5,4,3,2,1))
test <- cbind(test1,test2,test3,test4,test5)
rm(test1,test2,test3,test4,test5)
colnames(test) <- c("Person","var1","var2","var3","var4")
for(i in 2:5){
nam <- paste0("graph", i-1)
graph_temp <- ggplot(test, aes(Person, test[,i])) + geom_bar(stat = "identity")
assign(nam, graph_temp)
}
grid.arrange(graph1, graph2, graph3, graph4, ncol=2)
What I'm aiming for is the plot from this code:
library(gridExtra)
library(ggplot2)
test1 <- c("Person1","Person2","Person3","Person4","Person5")
test2 <- as.data.frame(c(1,2,3,4,5))
test3 <- as.data.frame(c(2,2,2,2,2))
test4 <- as.data.frame(c(1,3,5,3,1))
test5 <- as.data.frame(c(5,4,3,2,1))
test <- cbind(test1,test2,test3,test4,test5)
rm(test1,test2,test3,test4,test5)
colnames(test) <- c("Person","var1","var2","var3","var4")
graph1 <- ggplot(test, aes(Person, test[,2])) + geom_bar(stat = "identity")
graph2 <- ggplot(test, aes(Person, test[,3])) + geom_bar(stat = "identity")
graph3 <- ggplot(test, aes(Person, test[,4])) + geom_bar(stat = "identity")
graph4 <- ggplot(test, aes(Person, test[,5])) + geom_bar(stat = "identity")
grid.arrange(graph1, graph2, graph3, graph4, ncol=2)
I know there's a similar question on saving ggplots in a for loop, but I've not managed to get that one to work for this problem.

Here's a more concise way to produce your example:
df <- data.frame(
Person = paste0("Person", 1:5),
var1 = c(1,2,3,4,5),
var2 = c(2,2,2,2,2),
var3 = c(1,3,5,3,1),
var4 = c(5,4,3,2,1)
)
Now, about your plots.
Best solution
Reshape the data frame to 'long' format, and then use facets:
library(ggplot2)
library(tidyr)
gather(df, var, value, -Person) %>%
ggplot(aes(Person, value)) +
geom_bar(stat = "identity") +
facet_wrap(~ var)
Otherwise…
If you gotta stick with a data structure that looks like what you posted, then use aes_string:
library(ggplot2)
library(gridExtra)
g <- lapply(1:4, function(i) {
ggplot(df, aes_string("Person", paste0("var", i))) +
geom_bar(stat = "identity")
})
grid.arrange(grobs = g, ncol = 2)

Related

How to display the charts row-wise instead of column wise

marrangeGrob apparently displays the charts by column first. How to arrange these charts row-wise instead?
library(gridExtra)
library(tidyr)
library(ggplot2)
dat <- c(2,3,4,5,6,7,8,9,0,1)
time <- 1:10
data <- tibble(dat, time)
p1 <- ggplot(data, aes(x= time, y=dat)) +
geom_point(color="orange")
p2 <- ggplot(data, aes(x= time, y=dat)) +
geom_point(color="blue")
clist <- list(p1,p2)
marrangeGrob(clist, nrow=2, ncol=2, as.table=F )
Using the layout_matrix argument you could specify to add the plots by row (byrow=TRUE):
library(gridExtra)
library(ggplot2)
dat <- c(2,3,4,5,6,7,8,9,0,1)
time <- 1:10
data <- data.frame(dat, time)
p1 <- ggplot(data, aes(x= time, y=dat)) +
geom_point(color="orange")
p2 <- ggplot(data, aes(x= time, y=dat)) +
geom_point(color="blue")
clist <- list(p1,p2)
marrangeGrob(clist, nrow=2, ncol=2,
layout_matrix = matrix(seq_len(4), nrow = 2, byrow = TRUE))

Creating graphs in a loop: one graph different from the others

I have an elaborate code to create a series of graphs. I would like to put a vertical line in one of the many graphs I create.
Consider the following simple code:
library(ggplot2)
library(grid)
library(gridExtra)
plots <- list()
for (i in 1:4) {
V1 <- rnorm(1000)
V2 <- seq(1000)
df <- data.frame(V1, V2)
plots[[i]] <- ggplot(df, aes(x= V2, y=V1)) +
geom_point()+
geom_vline(xintercept = 500, color="red")
}
grid.arrange(grobs=plots, nrow=2)
I would like to have the red vertical line for graph 4 but not the others. How would I do this efficiently?
You don't need a for-loop and if-statement for this matter. You can use faceting;
library(ggplot2)
library(grid)
library(gridExtra)
library(dplyr)
set.seed(123) ## set the seed for random numbers to be reproducible
df <- bind_rows(lapply(1:4, function(x)
data.frame(V1=rnorm(1000), V2=seq(1000))), .id = 'facet')
ggplot(df, aes(x= V2, y=V1)) +
geom_point() +
facet_wrap(~facet) +
geom_vline(data=data.frame(xint=500,facet=4), aes(xintercept = xint), color = "red")
just split your plot production and set a condition :)
library(ggplot2)
library(grid)
library(gridExtra)
plots <- list()
for (i in 1:4) {
V1 <- rnorm(1000)
V2 <- seq(1000)
df <- data.frame(V1, V2)
plots[[i]] <- ggplot(df, aes(x= V2, y=V1)) +
geom_point()
if (i == 4) plots[[i]] <- plots[[i]] + geom_vline(xintercept = 500, color="red")
}
grid.arrange(grobs=plots, nrow=2)

Question about ggplot, for loop and marrangeGrob. Does anyone know how to fix the code when all plots are the same? [duplicate]

I've written a for loop which goes through the columns of a dataframe and produces a graph for each column using ggplot. The problem is the graphs that are output are all the same - they're all graphs of the final column.
The code I've used is:
library(gridExtra)
library(ggplot2)
test1 <- c("Person1","Person2","Person3","Person4","Person5")
test2 <- as.data.frame(c(1,2,3,4,5))
test3 <- as.data.frame(c(2,2,2,2,2))
test4 <- as.data.frame(c(1,3,5,3,1))
test5 <- as.data.frame(c(5,4,3,2,1))
test <- cbind(test1,test2,test3,test4,test5)
rm(test1,test2,test3,test4,test5)
colnames(test) <- c("Person","var1","var2","var3","var4")
for(i in 2:5){
nam <- paste0("graph", i-1)
graph_temp <- ggplot(test, aes(Person, test[,i])) + geom_bar(stat = "identity")
assign(nam, graph_temp)
}
grid.arrange(graph1, graph2, graph3, graph4, ncol=2)
What I'm aiming for is the plot from this code:
library(gridExtra)
library(ggplot2)
test1 <- c("Person1","Person2","Person3","Person4","Person5")
test2 <- as.data.frame(c(1,2,3,4,5))
test3 <- as.data.frame(c(2,2,2,2,2))
test4 <- as.data.frame(c(1,3,5,3,1))
test5 <- as.data.frame(c(5,4,3,2,1))
test <- cbind(test1,test2,test3,test4,test5)
rm(test1,test2,test3,test4,test5)
colnames(test) <- c("Person","var1","var2","var3","var4")
graph1 <- ggplot(test, aes(Person, test[,2])) + geom_bar(stat = "identity")
graph2 <- ggplot(test, aes(Person, test[,3])) + geom_bar(stat = "identity")
graph3 <- ggplot(test, aes(Person, test[,4])) + geom_bar(stat = "identity")
graph4 <- ggplot(test, aes(Person, test[,5])) + geom_bar(stat = "identity")
grid.arrange(graph1, graph2, graph3, graph4, ncol=2)
I know there's a similar question on saving ggplots in a for loop, but I've not managed to get that one to work for this problem.
Here's a more concise way to produce your example:
df <- data.frame(
Person = paste0("Person", 1:5),
var1 = c(1,2,3,4,5),
var2 = c(2,2,2,2,2),
var3 = c(1,3,5,3,1),
var4 = c(5,4,3,2,1)
)
Now, about your plots.
Best solution
Reshape the data frame to 'long' format, and then use facets:
library(ggplot2)
library(tidyr)
gather(df, var, value, -Person) %>%
ggplot(aes(Person, value)) +
geom_bar(stat = "identity") +
facet_wrap(~ var)
Otherwise…
If you gotta stick with a data structure that looks like what you posted, then use aes_string:
library(ggplot2)
library(gridExtra)
g <- lapply(1:4, function(i) {
ggplot(df, aes_string("Person", paste0("var", i))) +
geom_bar(stat = "identity")
})
grid.arrange(grobs = g, ncol = 2)

ggplot: how to align two time-series plots on the x axis?

I am struggling with the following problem. Consider this (simple) example
library(grid)
library(gridExtra)
library(gtable)
library(dplyr)
library(lubridate)
options("digits.secs"=3)
time1 = c('2013-01-03 22:04:21.549', '2013-01-03 22:04:22.549', '2013-01-03 22:04:23.559', '2013-01-03 22:04:24.559' )
value1 = c(1,2,3,4)
data1 <- data_frame(time1, value1)
data1 <- data1 %>% mutate(time1 = ymd_hms(time1))
time2 = c('2013-01-03 22:04:21.800', '2013-01-03 22:04:22.549', '2013-01-03 22:04:25.559', '2013-01-03 22:04:26.559' )
value2 = c(1,2,3,4)
data2 <- data_frame(time2, value2)
data2 <- data2 %>% mutate(time2 = ymd_hms(time2))
g1 <- ggplot(data1, aes(x = time1, y = value1)) +geom_point()
g2 <- ggplot(data2, aes(x = time2, y = value2)) +geom_point()
graph_1 <- arrangeGrob(g1, g2, ncol=1)
grid.draw(graph_1)
which gives
as you can see the x- axis is not properly aligned.
Any ideas how to do that? Alternative solutions like How to align two plots with ggplot? do not work here.
Many thanks!!
You can either use the same limit for both plots (first) or use the facet_grid to align the range for plots (second).
# first method
mx <- ymd_hms("2013-01-03 22:04:21.000")
mn <- ymd_hms("2013-01-03 22:04:27.000")
grid.arrange(g1 + scale_x_datetime(limits=c(mx, mn)),
g2 + scale_x_datetime(limits=c(mx, mn)))
# second method
names(data1) <- c("time", "value")
names(data2) <- c("time", "value")
df <- bind_rows(first=data1, second=data2, .id="group")
ggplot(df, aes(x=time, y=value)) + geom_point() + facet_grid(group ~ .)
You can set the limits of both plots to the range of the data:
xmin <- ymd_hms(min(time1,time2))
xmax <- ymd_hms(max(time1,time2))
g1 <- ggplot(data1, aes(x = time1, y = value1)) + geom_point() +
theme(axis.title.x = element_blank()) + xlim(xmin, xmax)
g2 <- ggplot(data2, aes(x = time2, y = value2)) + geom_point() +
xlim(xmin, xmax)

How to use 'facet' to create multiple density plot in GGPLOT

I have the following data created on the fly:
> df <- data.frame( cbind(rnorm(200),rnorm(200, mean=.8),rnorm(200, mean=.9),rnorm(200, mean=1),rnorm(200, mean=.2),rnorm(200, mean=.3)),rnorm(200, mean=4),rnorm(200, mean=.5))
> colnames(df) <- c("w.cancer","w.normal","x.cancer","x.normal","y.cancer","y.normal","z.cancer","z.normal")
> df_log<-log2(df) # ignore the warning with NA
> head(df_log)
What I want to do is to create multiple plots in one panel like the sketch below using 'facet'.
How can I go about it?
You'll have to prepare your data first. I've illustrated this on your data.frame df as it is a proper normal distribution.
require(ggplot2)
require(reshape2)
df$id <- 1:nrow(df)
df.m <- melt(df, "id")
df.m$grp1 <- factor(gsub("\\..*$", "", df.m$variable))
df.m$grp2 <- factor(gsub(".*\\.", "", df.m$variable))
p <- ggplot(data = df.m, aes(x=value)) + geom_density(aes(fill=grp2), alpha = 0.4)
p <- p + facet_wrap( ~ grp1)
p + scale_fill_brewer(palette = "Set1")
Doing the same by replacing df with df_log you'd get something like this:
require(ggplot2)
require(reshape2)
df_log$id <- 1:nrow(df_log)
df.m <- melt(df_log, "id")
df.m$grp1 <- factor(gsub("\\..*$", "", df.m$variable))
df.m$grp2 <- factor(gsub(".*\\.", "", df.m$variable))
p <- ggplot(data = df.m, aes(x=value)) + geom_density(aes(fill=grp2), alpha = 0.5)
p <- p + facet_wrap( ~ grp1)
p

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