This question already has answers here:
ggplot2 line chart gives "geom_path: Each group consist of only one observation. Do you need to adjust the group aesthetic?"
(6 answers)
Closed 12 months ago.
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library(ggplot2)
x=letters[1:3]
y=1:3
qplot(x, y)
qplot(x, y, geom=c('point', 'line'))
geom_path: Each group consists of only one observation. Do you need to adjust
the group aesthetic?
I want to connect lines between the points. But when the x is a string, the above commands won't work. It works when the x is numeric. I'd think qplot should be made more user-friendly in this case.
How to make it connect the points with lines when x is a string?
One solution is provided by #stefan. Another one could be the following.
Sample data:
x=letters[1:3]
y=1:3
Sample code:
d <- data.frame(x, y) %>%
mutate(x = x %>%
factor(levels = x))
library(ggplot2)
ggplot(data = d, aes(x = x, y = y, group = 1)) +
geom_line() +
scale_x_discrete(labels = x, breaks = x)
Plot:
Related
This question already has answers here:
Add legend to ggplot2 line plot
(4 answers)
Closed 4 months ago.
I have a graph that I'm trying to add a legend to but I can't find any answers.
Here's what the graph looks like
I made a dataframe containing my x-axis as a colum and several othe columns containing y values that I graphed against x (fixed) in order to get these curves. I want a legend to appear on the side saying column 1, ...column 11 and corresponding to the color of the graph
How do I do this? I feel like I'm missing something obvious
Here's what my code looks like:(sorry for the pic. I keep getting errors that my code is not formatted correctly even though I'm using the code button)
interval is just 2:100 and aaaa etc... is a vector the same length as interval.
As Peter says, you will need to convert your data into "long" format. Here is an example using reshape2::melt:
library(reshape2)
library(ggplot2)
n <- 20
df <- data.frame(x = seq(n))
tmp <- as.data.frame(do.call("cbind", lapply(seq(5), FUN = function(x){rnorm(n)})))
names(tmp) <- paste0("aaaa", letters[1:5])
df <- cbind(df, tmp)
head(df)
df2 <- melt(df, id.vars = "x")
head(df2)
ggplot(data = df2) + aes(x = x, y = value, color = variable) +
geom_point() +
geom_line()
This question already has answers here:
Plot two graphs in same plot in R
(17 answers)
Plotting two variables as lines using ggplot2 on the same graph
(5 answers)
Closed 3 years ago.
I want to show graphically how the summation of two different sin curves looks like.
So, I am trying to make a single graph that shows two different sin function and their sum. So, three curves on one graph.
How can I do it with ggplot layers?
I am defing two sin functions (y and z)
x <- seq(0, 16*pi, 0.01)
y <- 2*sin(3*(x-1))
z <- sin(x)
summing up the two curves:
t <- y + z
I can see the three separately with:
plot(x,y,type="l")
plot(x,z,type="l")
plot(x,t,type="l")
But how can I plot the three functions?
I tried this but it does not work
ggplot(x,
qplot(y,x,geom="path", xlab="time", ylab="Sine wave") +
qplot(z,x,geom="path", xlab="time", ylab="Sine wave"))
Store everything in a data.frame, reshape from wide to long, and plot:
library(tidyverse)
data.frame(x = x, y = y, z = z, t = y + z) %>%
pivot_longer(-x) %>%
ggplot(aes(x, value, colour = name)) +
geom_line()
Sample data
x <- seq(0, 16*pi, 0.01)
y <- 2*sin(3*(x-1))
z <- sin(x)
This question already has answers here:
ggplot2 - Boxplot Whiskers at Min/Max
(2 answers)
Closed 7 years ago.
I have some data that I'm trying to build some boxplots with, but I'm getting this error:
Warning message: Removed 1631 rows containing non-finite values
(stat_boxplot).
There are no NA values and all the data seems fine. How can I fix this as these are certainly valuable points in my data and should be extended by the whiskers?
Data
The data is fairly large, and I couldn't get a smaller subsample to produce the errors, so I'll just post the original data.
dat.rds
ggplot2
dat <- readRDS("./dat.rds")
ggplot(dat, aes(x = factor(year), y = dev)) + geom_boxplot() + ylim(-40, 260)
Edit
I was able to get it to work in boxplot with `range = 6'. Is there a way to do this in ggplot?
boxplot(dev~year, data = d, range = 6)
Remove the ylim restriction and use the coef argument of geom_boxplot, then it works fine:
library(ggplot2)
download.file(url = "https://www.dropbox.com/s/5mgogyclhim6hom/dat.rds?dl=1", tf <- tempfile(fileext = ".rds"))
dat <- readRDS(tf)
ggplot(dat, aes(x = factor(year), y = dev)) +
geom_boxplot(coef = 6)
This question already has answers here:
Plot multiple columns on the same graph in R [duplicate]
(4 answers)
Closed 4 years ago.
I need to plot the following dataset in the same graph.
Bin1,Bin2,Bin3,Cat
4,3,5,S
6,4,5,M
3,5,4,M
1,4,5,M
,5, ,M
In each bin, first data point belongs to a different category than the rest. (So I added the Cat column)
I need to plot these as points (different colors for the different categories)
Following lines of code achieve what I need for a single bin
p <- ggplot(data,aes(Bin1,1))
p + geom_point(aes(color=Cat, size=Cat))
How do I do this for the entire dataset ?
Here is a related question?
What if I need to use a bunch of columns to color the points. Color Bin1 points according to Cat1 and so on..
Bin1,Cat1,Bin2,Cat2
4,S,5,S
6,L,5,M
3,M,4,L
1,M,5,L
3,M
How do I do this??
library(reshape2)
library(ggplot2)
ggplot(melt(df, id.vars = "Cat"), aes(value, variable, colour = Cat)) +
geom_point(size = 4)
Just melt the data.frame and plot it.
library(reshape2)
dataM <- melt(data, id.vars = "Cat")
p <- ggplot(dataM, aes(value, variable, colour = Cat, size = Cat) + geom_point()
Environment: Win 7 HP, R v2.15.1
What I wish to get to:
Plot y (numeric) vs x (date) with
labels month-year abbrev, sorted mon+year, las2 vertically aligned
colours filled by year
facet-grid by year
I have tried different approaches after reading up different threads in this forum, but unable to get what I need. Need help. Attaching sample data and results.
MySample Data
x <- c("04-01-10","05-01-10","06-01-10","07-01-10","08-01-10","09-01-10","10-01-10","11-01-10","12-01-10","01-01-11","02-01-11","03-01-11","04-01-11","05-01-11","06-01-11","07-01-11","08-01-11","09-01-11","10-01-11","11-01-11","12-01-11","01-01-12","02-01-12","03-01-12","04-01-12","05-01-12","06-01-12")
y <- c(120,210,130,160,190,210,80,70,110,120,140,160,130,200,110,180,210,200,90,60,100,100,120,170,100,180,120)
x is date (character) in mm-dd-yy format tz:IST (Calcutta / Asia)
data has only single y value per month which is on the start date of the month
Convert to Data Frame
MySample <- data.frame(x) ## convert to dataframe
MySample$y <- y
load required libraries
require(lubridate)
require(ggplot2)
MySample Base Plot
1) Plot x vs y
ggplot(MySample, aes(MySample$x, MySample$y)) +
geom_bar(y=MySample$y,stat="identity")
Gave me base plot results
2) Plot x vs y + fill=year
ggplot(MySample, aes(MySample$x, MySample$y, fill=year(MySample$x))) +
geom_bar(y=MySample$y,stat="identity")
gave me fills but have 5 fill years with 2010,2010.5,2011,2011.5,2012
I have tried different approaches but running into one error or another.
3) Plot x vs y + fill=year + facet_grid(year)
ggplot(MySample, aes(x, y, fill=year(x))) +
geom_bar(y=MySample$y,stat="identity") +
facet_grid(. ~ year(MySample$x))
Get : Error in layout_base(data, cols, drop = drop) :
At least one layer must contain all variables used for facetting
4) Plot x vs y + fill=year + facet_grid(year) + labels-month (abbr)
ggplot(MySample, aes(x, y, fill=year(x))) +
geom_bar(y=MySample$y,stat="identity") +
scale_x_date(labels=month(MySample$x,label=TRUE,abbr=TRUE))
Get : Error in scale_labels.continuous(scale, major) : Breaks and labels are different lengths
I'm stuck and need help to move forward.
Need solutions to address the following requirements:
3 fill years only - 2010,2011,2012
xlabels - %b%y format; sorted on month-year sequence; las2 positioned (vertical)
facet_grid by year with only that year's xlabels and bars in the appropriate facet-grid
To answer your 3 points:
use scale_fill_gradient(breaks=unique(MySample$year))
use the standard built-in date system instead of lubridate. you can specify the format in ggplot2 with date_format.
use: +facet_grid(. ~ year, scales = "free")
The following code will do it:
MySample$date <- as.Date(MySample$x, "%m-%d-%y")
MySample$year <- year(MySample$date)
ggplot(MySample, aes(date, y, fill = year)) +
geom_bar(y=y,stat="identity") +
facet_grid(. ~ year, scales = "free") +
scale_x_date(labels = date_format("%b/%y")) +
scale_fill_gradient(breaks=unique(MySample$year))