I am trying to create a heat map, where each tile is a month. If I use the dates as a data date type, I get lines over my image that are not acceptable.
So my solution has been to to treat the date as a factor
The problem is that the axis is not presentable. Is there a way to merge the two plots with the x axis from the first plot, but the tiles from the second plot?
ggplot(df, aes(x = factor(Var2),
y = factor(desc(Var1)),
fill = value)) +
As a reproducible example:
df <- read.table("","Var1","Var2","value","Col"
"1",2001-01-31,2001-01-31,-0.0118511587908436,"blue"
"2",2001-02-28,2001-01-31,0,"white"
"3",2001-03-30,2001-01-31,0,"white"
"4",2001-04-30,2001-01-31,0,"white"
"5",2001-05-31,2001-01-31,0,"white"
"6",2001-06-29,2001-01-31,0,"white")
ggplot(dff, aes(x = factor(Var2),
y = factor(desc(Var1)),
fill = Col)) +
geom_tile() +
scale_x_discrete(breaks=pretty(p$Var2))
Output from example
Use dates but manually remove the grid. You can do it by adding + theme(panel.grid = element_blank()) to the plot.
Related
I have an example data, which does not have x- and y-axis information. I would like to make a bubble plot using R package ggplot2, and arrange the bubbles in a circled manner.
data <- data.frame(group = paste("Group", letters[1:11]),
value = sample(seq(1,100),11))
Thanks a lot.
You can just put a dummy value for y and make group your x values in aes.
ggplot(data, aes(x = group, y = 0, size = value)) +
coord_polar() +
geom_point()
I have a dataframe with ~37000 rows that contains 'name' in string format and 'UTCDateTime' in posixct format and am using it to produce a facet wrapped density plot of time grouped by the names:
I also have a separate density plot of posixct datetime data from an entirely different dataframe:
I want to overlay this second density plot on each individual facet_wrapped plot in the first density plot. Is there a way to do that? In general, if I have plots of any kind that are facet wrapped and another plot of the same type but different data that I want to overlay on each facet of the facet wrap, how do I do so?
This should in theory be as simple as not having the column that you're facetting by in the second dataframe. Example below:
library(ggplot2)
ggplot(iris, aes(Sepal.Width)) +
geom_density(aes(fill = Species)) +
geom_density(data = faithful,
aes(x = eruptions)) +
facet_wrap(~ Species)
Created on 2020-08-12 by the reprex package (v0.3.0)
EDIT: To get the densities on the same scale for the two types of data, you can use the computed variables using after_stat()*:
ggplot(iris, aes(Sepal.Width)) +
geom_density(aes(y = after_stat(scaled),
fill = Species)) +
geom_density(data = faithful,
aes(x = eruptions,
y = after_stat(scaled))) +
facet_wrap(~ Species)
* Prior to ggplot2 v3.3.0 also stat(variable) or ...variable....
I'd like to make a path plot in ggplot2, with the path based on a timeseries, and a continuous color aesthetic to show this path. The legend should associate the color with timeseries. The legend is nice when the color aesthetic is defined in the original call to ggplot:
library(tidyverse)
times <- seq.POSIXt(from = as.POSIXct("2017-10-01 02:00:00"),
to = as.POSIXct("2017-10-03 12:34:00"),
by = "min")
values <- rnorm(length(times))
dat <- data.frame(times = times,
values1 = sin(values[order(values)]),
values2 = cos(values[order(-values)]))
ggplot(dat, aes(values1, values2, color=times)) +
geom_path()
However, I want to use a different color scale than the default. When using scale_color_gradientn, or scale_color_continuous, the legend entries seem to get converted from POSIXct to integers:
ggplot(dat, aes(x = values1, y = values2, color = times)) +
geom_path() +
scale_color_gradientn(colors = rainbow(4))
How do I either (1) specify a custom color scale in the first plot, or (2) maintain POSIXct legend entries in the 2nd plot?
Looking at scale_colour_datetime() which is used by default, all it does is:
scale_colour_continuous(trans = "time")
So adding trans = "time" to your desired colour scale works:
ggplot(dat, aes(values1, values2, color=times)) +
geom_path() +
scale_color_gradientn(colors = rainbow(4), trans = "time")
Output:
I want to make a line chart in plotly so that it does not have the same color on its whole length. The color is given continuous scale. It is easy in ggplot2 but when I translate it to plotly using ggplotly function the variable determining color behaves like categorical variable.
require(dplyr)
require(ggplot2)
require(plotly)
df <- data_frame(
x = 1:15,
group = rep(c(1,2,1), each = 5),
y = 1:15 + group
)
gg <- ggplot(df) +
aes(x, y, col = group) +
geom_line()
gg # ggplot2
ggplotly(gg) # plotly
ggplot2 (desired):
plotly:
I found one work-around that, on the other hand, behaves oddly in ggplot2.
df2 <- df %>%
tidyr::crossing(col = unique(.$group)) %>%
mutate(y = ifelse(group == col, y, NA)) %>%
arrange(col)
gg2 <- ggplot(df2) +
aes(x, y, col = col) +
geom_line()
gg2
ggplotly(gg2)
I also did not find a way how to do this in plotly directly. Maybe there is no solution at all. Any ideas?
It looks like ggplotly is treating group as a factor, even though it's numeric. You could use geom_segment as a workaround to ensure that segments are drawn between each pair of points:
gg2 = ggplot(df, aes(x,y,colour=group)) +
geom_segment(aes(x=x, xend=lead(x), y=y, yend=lead(y)))
gg2
ggplotly(gg2)
Regarding #rawr's (now deleted) comment, I think it would make sense to have group be continuous if you want to map line color to a continuous variable. Below is an extension of the OP's example to a group column that's continuous, rather than having just two discrete categories.
set.seed(49)
df3 <- data_frame(
x = 1:50,
group = cumsum(rnorm(50)),
y = 1:50 + group
)
Plot gg3 below uses geom_line, but I've also included geom_point. You can see that ggplotly is plotting the points. However, there are no lines, because no two points have the same value of group. If we hadn't included geom_point, the graph would be blank.
gg3 <- ggplot(df3, aes(x, y, colour = group)) +
geom_point() + geom_line() +
scale_colour_gradient2(low="red",mid="yellow",high="blue")
gg3
ggplotly(gg3)
Switching to geom_segment gives us the lines we want with ggplotly. Note, however, that line color will be based on the value of group at the first point in the segment (whether using geom_line or geom_segment), so there might be cases where you want to interpolate the value of group between each (x,y) pair in order to get smoother color gradations:
gg4 <- ggplot(df3, aes(x, y, colour = group)) +
geom_segment(aes(x=x, xend=lead(x), y=y, yend=lead(y))) +
scale_colour_gradient2(low="red",mid="yellow",high="blue")
ggplotly(gg4)
Is there any way to line up the points of a line plot with the bars of a bar graph using ggplot when they have the same x-axis? Here is the sample data I'm trying to do it with.
library(ggplot2)
library(gridExtra)
data=data.frame(x=rep(1:27, each=5), y = rep(1:5, times = 27))
yes <- ggplot(data, aes(x = x, y = y))
yes <- yes + geom_point() + geom_line()
other_data = data.frame(x = 1:27, y = 50:76 )
no <- ggplot(other_data, aes(x=x, y=y))
no <- no + geom_bar(stat = "identity")
grid.arrange(no, yes)
Here is the output:
The first point of the line plot is to the left of the first bar, and the last point of the line plot is to the right of the last bar.
Thank you for your time.
Extending #Stibu's post a little: To align the plots, use gtable (Or see answers to your earlier question)
library(ggplot2)
library(gtable)
data=data.frame(x=rep(1:27, each=5), y = rep(1:5, times = 27))
yes <- ggplot(data, aes(x = x, y = y))
yes <- yes + geom_point() + geom_line() +
scale_x_continuous(limits = c(0,28), expand = c(0,0))
other_data = data.frame(x = 1:27, y = 50:76 )
no <- ggplot(other_data, aes(x=x, y=y))
no <- no + geom_bar(stat = "identity") +
scale_x_continuous(limits = c(0,28), expand = c(0,0))
gYes = ggplotGrob(yes) # get the ggplot grobs
gNo = ggplotGrob(no)
plot(rbind(gNo, gYes, size = "first")) # Arrange and plot the grobs
Edit To change heights of plots:
g = rbind(gNo, gYes, size = "first") # Combine the plots
panels <- g$layout$t[grepl("panel", g$layout$name)] # Get the positions for plot panels
g$heights[panels] <- unit(c(0.7, 0.3), "null") # Replace heights with your relative heights
plot(g)
I can think of (at least) two ways to align the x-axes in the two plots:
The two axis do not align because in the bar plot, the geoms cover the x-axis from 0.5 to 27.5, while in the other plot, the data only ranges from 1 to 27. The reason is that the bars have a width and the points don't. You can force the axex to align by explicitly specifying an x-axis range. Using the definitions from your plot, this can be achieved by
yes <- yes + scale_x_continuous(limits=c(0,28))
no <- no + scale_x_continuous(limits=c(0,28))
grid.arrange(no, yes)
limits sets the range of the x-axis. Note, though, that the alginment is still not quite perfect. The y-axis labels take up a little more space in the upper plot, because the numbers have two digits. The plot looks as follows:
The other solution is a bit more complicated but it has the advantage that the x-axis is drawn only once and that ggplot makes sure that the alignment is perfect. It makes use of faceting and the trick described in this answer. First, the data must be combined into a single data frame by
all <- rbind(data.frame(other_data,type="other"),data.frame(data,type="data"))
and then the plot can be created as follows:
ggplot(all,aes(x=x,y=y)) + facet_grid(type~.,scales = "free_y") +
geom_bar(data=subset(all,type=="other"),stat="identity") +
geom_point(data=subset(all,type=="data")) +
geom_line(data=subset(all,type=="data"))
The trick is to let the facets be constructed by the variable type which was used before to label the two data sets. But then each geom only gets the subset of the data that should be drawn with that specific geom. In facet_grid, I also used scales = "free_y" because the two y-axes should be independent. This plot looks as follows:
You can change the labels of the facets by giving other names when you define the data frame all. If you want to remove them alltogether, then add the following to your plot:
+ theme(strip.background = element_blank(), strip.text = element_blank())