I wonder how to animate geom_bar from ggplot2 with gganimate in such a way that previously shown bar stay and next come.
library(ggplot2)
library(gganimate)
a <- data.frame(group=c("A","B","C"), values=c(3,2,4), frame=rep('a',3))
b <- data.frame(group=c("A","B","C"), values=c(5,3,7), frame=rep('b',3))
df1 <- rbind(a,b)
Plot1 <-
ggplot(data= df1, aes(x = group, y = values, fill = group)) +
geom_bar(stat='identity') +
theme_bw() +
transition_states(
states = group
, transition_length = 2
, state_length = 1
)
Plot1
The above given code shows bar one by one but fade the previously shown. However, I want to retain already shown bars. Any thoughts.
Check out ?shadow_mark() from the gganimate package. I think this achieves what you are looking to accomplish:
library(ggplot2)
library(gganimate)
a <- data.frame(group=c("A","B","C"), values=c(3,2,4), frame=rep('a',3))
b <- data.frame(group=c("A","B","C"), values=c(5,3,7), frame=rep('b',3))
df1 <- rbind(a,b)
Plot1 <-
ggplot(data= df1, aes(x = group, y = values, fill = group)) +
geom_bar(stat='identity') +
theme_bw() +
transition_states(
states = group
, transition_length = 2
, state_length = 1
) +
shadow_mark() # keeps past data displayed
Plot1
Related
I need to plot two bars and one line. I have 3 data frames as this:
require(ggplot2)
df.0 <- data.frame(x = c(1:5), y = rnorm(5))
df.1 <- data.frame(x = c(1:5), y = rnorm(5))
df.2 <- data.frame(x = c(1:5), y = runif(5))
ggplot(df.0, aes(x=x, y=y)) +
geom_line(aes(x=x, y=y))+
geom_bar(data=df.1, aes(x=x, y=y),stat = "identity",position="dodge")+
geom_bar(data=df.2, aes(x=x, y=y),stat = "identity",position="dodge")
I can't manage to plot the bars and the line in the correct way. It should look as the image below.
I'm not familiar with ggplot2. I've read a lot of links, and I can't find a post similar to my question.
Thanks for your time and interest.
Combine the data frames - at least the two for the bar plot. Dodging is done within a single geom_bar layer, not between two separate ones.
df_bar = rbind(df.1, df.2)
df_bar$id = rep(c("df.1", "df.2"), times = c(nrow(df.1), nrow(df.2)))
ggplot(df.0, aes(x = x, y = y)) +
geom_line() +
geom_col(data = df_bar, aes(fill = id), position="dodge")
Other changes: no need to repeat aes(x = x, y = y) in every layer. If it's in the original ggplot() it will be inherited. Also geom_col is a nice way of geom_bar(stat = 'identity').
This question already has an answer here:
Setting individual y axis limits with facet wrap NOT with scales free_y
(1 answer)
Closed 4 years ago.
I'm trying to create a facet_wrap() where the unit of measure remains identical across the different plots, while allowing to slide across the y axis.
To clearify with I mean, I have created a dataset df:
library(tidyverse)
df <- tibble(
Year = c(2010,2011,2012,2010,2011,2012),
Category=c("A","A","A","B","B","B"),
Value=c(1.50, 1.70, 1.60, 4.50, 4.60, 4.55)
)
with df, we can create the following plot using facet_wrap:
ggplot(data = df, aes(x=Year, y=Value)) + geom_line() + facet_wrap(.~ Category)
Plot 1
To clarify the differences between both plots, one can use scale = "free_y":
ggplot(data = df, aes(x=Year, y=Value)) + geom_line()
+ facet_wrap(.~ Category, scale="free_y")
Plot 2
Although it's more clear, the scale on the y-axis in plot A isequal to 0.025, while being 0.0125 in B. This could be misleading to someone who's comparing A & B next to each other.
So my question right now is to know whether there exist an elegant way of plotting something like the graph below (with y-scale = 0.025) without having to plot two seperate plots into a grid?
Thanks
Desired result:
Code for the grid:
# Grid
## Plot A
df_A <- df %>%
filter(Category == "A")
plot_A <- ggplot(data = df_A, aes(x=Year, y=Value)) + geom_line() + coord_cartesian(ylim = c(1.5,1.7)) + ggtitle("A")
## Plot B
df_B <- df %>%
filter(Category == "B")
plot_B <- ggplot(data = df_B, aes(x=Year, y=Value)) + geom_line() + coord_cartesian(ylim = c(4.4,4.6)) + ggtitle("B")
grid.arrange(plot_A, plot_B, nrow=1)
Based on the info at Setting individual y axis limits with facet wrap NOT with scales free_y you can you use geom_blank() and manually specified y-limits by Category:
# df from above code
df2 <- tibble(
Category = c("A", "B"),
y_min = c(1.5, 4.4),
y_max = c(1.7, 4.6)
)
df <- full_join(df, df2, by = "Category")
ggplot(data = df, aes(x=Year, y=Value)) + geom_line() +
facet_wrap(.~ Category, scales = "free_y") +
geom_blank(aes(y = y_min)) +
geom_blank(aes(y = y_max))
How can I use geom_segment to draw lines on plot, after the data have been melted with reshape2?
# Tiny dataset
facet_group <- c("facet1", "facet1", "facet2", "facet2")
time_group <- c("before", "after", "before", "after")
variable1 <- c(1,5,4,7)
variable2 <- c(2,4,5,8)
variable3 <- c(4,5,6,7)
data <- data.frame(facet_group, time_group, variable1, variable2, variable3)
# Melt data
library(reshape2)
data_melt <- melt(data, id.vars = c("facet_group", "time_group"))
Plot the data:
# Plot 1
library(ggplot2)
ggplot(data_melt, aes(x=variable, y=value, group = time_group)) +
geom_point(aes(color = time_group))
Add faceting:
# Plot 2
ggplot(data_melt, aes(x=variable, y=value, group = time_group)) +
geom_point(aes(color = time_group)) +
facet_grid(facet_group ~ .)
I want to draw a segments from the "before" point to the "after" point for each variable. (see mock up image). How can I do this? I tried some things with geom_segment but I kept having errors. Will casting the data into a new data frame help?? Thanks!
data_cast <- dcast(data_melt, variable + facet_group ~ time_group)
Final "ideal" plot:
You were definitely on the right track with the casted data. Give this a shot:
ggplot(data_melt, aes(x=variable, y=value)) +
geom_point(aes(color = time_group)) +
facet_grid(facet_group ~ .) +
geom_segment(data = data_cast, aes(x = variable, xend = variable,
y = before, yend = after),
arrow = arrow(),
colour = "#FF3EFF",
size = 1.25)
I have a data frame with five columns and five rows. the data frame looks like this:
df <- data.frame(
day=c("m","t","w","t","f"),
V1=c(5,10,20,15,20),
V2=c(0.1,0.2,0.6,0.5,0.8),
V3=c(120,100,110,120,100),
V4=c(1,10,6,8,8)
)
I want to do some plots so I used the ggplot and in particular the geom_bar:
ggplot(df, aes(x = day, y = V1, group = 1)) + ylim(0,20)+ geom_bar(stat = "identity")
ggplot(df, aes(x = day, y = V2, group = 1)) + ylim(0,1)+ geom_bar(stat = "identity")
ggplot(df, aes(x = day, y = V3, group = 1)) + ylim(50,200)+ geom_bar(stat = "identity")
ggplot(df, aes(x = day, y = V4, group = 1)) + ylim(0,15)+ geom_bar(stat = "identity")
My question is, How can I do a grouped ggplot with geom_bar with multiple y axis? I want at the x axis the day and for each day I want to plot four bins V1,V2,V3,V4 but with different range and color. Is that possible?
EDIT
I want the y axis to look like this:
require(reshape)
data.m <- melt(df, id.vars='day')
ggplot(data.m, aes(day, value)) +
geom_bar(aes(fill = variable), position = "dodge", stat="identity") +
facet_grid(variable ~ .)
You can also change the y-axis limits if you like (here's an example).
Alternately you may have meant grouped like this:
require(reshape)
data.m <- melt(df, id.vars='day')
ggplot(data.m, aes(day, value)) +
geom_bar(aes(fill = variable), position = "dodge", stat="identity")
For the latter examples if you want 2 Y axes then you just create the plot twice (once with a left y axis and once with a right y axis) then use this function:
double_axis_graph <- function(graf1,graf2){
graf1 <- graf1
graf2 <- graf2
gtable1 <- ggplot_gtable(ggplot_build(graf1))
gtable2 <- ggplot_gtable(ggplot_build(graf2))
par <- c(subset(gtable1[['layout']], name=='panel', select=t:r))
graf <- gtable_add_grob(gtable1, gtable2[['grobs']][[which(gtable2[['layout']][['name']]=='panel')]],
par['t'],par['l'],par['b'],par['r'])
ia <- which(gtable2[['layout']][['name']]=='axis-l')
ga <- gtable2[['grobs']][[ia]]
ax <- ga[['children']][[2]]
ax[['widths']] <- rev(ax[['widths']])
ax[['grobs']] <- rev(ax[['grobs']])
ax[['grobs']][[1]][['x']] <- ax[['grobs']][[1]][['x']] - unit(1,'npc') + unit(0.15,'cm')
graf <- gtable_add_cols(graf, gtable2[['widths']][gtable2[['layout']][ia, ][['l']]], length(graf[['widths']])-1)
graf <- gtable_add_grob(graf, ax, par['t'], length(graf[['widths']])-1, par['b'])
return(graf)
}
I believe there's also a package or convenience function that does the same thing.
First I reshaped as described in the documentation in the link below the question.
In general ggplot does not support multiple y-axis. I think it is a philosophical thing. But maybe faceting will work for you.
df <- read.table(text = "day V1 V2 V3 V4
m 5 0.1 120 1
t 10 0.2 100 10
w 2 0.6 110 6
t 15 0.5 120 8
f 20 0.8 100 8", header = TRUE)
library(reshape2)
df <- melt(df, id.vars = 'day')
ggplot(df, aes(x = variable, y = value, fill = variable)) + geom_bar(stat = "identity") + facet_grid(.~day)
If I understand correctly you want to include facets in your plot. You have to use reshape2 to get the data in the right format. Here's an example with your data:
df <- data.frame(
day=c("m","t","w","t","f"),
V1=c(5,10,20,15,20),
V2=c(0.1,0.2,0.6,0.5,0.8),
V3=c(120,100,110,120,100),
V4=c(1,10,6,8,8)
)
library(reshape2)
df <- melt(df, "day")
Then plot with and include facet_grid argument:
ggplot(df, aes(x=day, y=value)) + geom_bar(stat="identity", aes(fill=variable)) +
facet_grid(variable ~ .)
Who can tell me why ggplot can't give me grouped bars?
ggplot(df, aes(x = factor(labels), y = srednia, dodge=factor(group))) +
labs(title = gen, size=3)+ ylab("Fold change")+ xlab("Linnia komórkowa") +
geom_bar(aes(fill=factor(group)),stat="identity",position ="dodge") +
geom_errorbar(aes(ymin=minus, ymax=plus))
Grouped bars I means something like this (paint art):
Thank you in advance!
I guess you can achieve this by changing the scale for the x axis. Here's a reproducible example and a possible solution.
# packages
require(plyr)
require(ggplot2)
# generate data
set.seed(123)
df <- data.frame(labels=LETTERS[1:6],
group=rep(1:3, each=2),
srednia=runif(6))
# limits for x axis
mylims <- head(unlist(dlply(df, .(group), function(x) c(levels(factor(x$labels)), "space"))), -1)
# additional space between groups
ggplot(df, aes(x = factor(labels), y = srednia, dodge=factor(group))) +
geom_bar(aes(fill=factor(group)),stat="identity") +
scale_x_discrete(limits=mylims, breaks=levels(factor(df$labels)))
# removing space within group
ggplot(df, aes(x = factor(labels), y = srednia, dodge=factor(group))) +
geom_bar(aes(fill=factor(group)),stat="identity", width=1) +
scale_x_discrete(limits=mylims, breaks=levels(factor(df$labels)))