I am trying to make a chart in ggplot2 (barplot). There are several days in between data points in my data set. I'd like to only graph the dates where variables are and omit the empty dates.
I have been searching for an hour trying to find an answer to this. I found some replies here indicating that the fix is this:
scale_x_date(format = '%d%b', major='days')
However, those arguments inside of scale_x_date don't seem to work anymore. Does anyone have a quick and easy solution?
I would be remiss if I didn't mention the ggplot2 docs which are a fantastic resource, packed full of well-documented examples. They are often the best place to start when you don't know how to do something with ggplot.
The "translation" for the code you quoted above in the current framework is:
scale_x_date(breaks='days', labels=date_format("%d%b"))
which will require the package scales. Unless you have fairly few dates, you probably also would want an adjustment like
theme(axis.text.x = element_text(angle=45))
If you only want to label the dates for which you have data, try
scale_x_date(breaks=df$date, labels = date_format("%m/%d"))
where df$date is the column of your dataframe containing the dates, and of course you can use your preferred date format string.
Related
Hi I am using ggplot2 to create a scatter graph. For some reason it keeps using the y-axis variables to order my scatter graph. I'm new to this so I barely know what I'm doing, so if someoen could help, would be much appreciated!
What I've noticed is that my Rstudio orders the numbers going in order like 1,10,11,12...2,21,22,23 instead of going the standard 1,2,3,4,5,6,7
Diesel_Prices_Jan19 <- ggplot(Prices_4, aes(V4, V1))
Diesel_Prices_Jan19 + geom_point()
As a tip its probably best to give a good reprex. Check the type of that column and maybe try turning it into a factor
I am trying to plot a graph of certain values against time using the plot function.
I am simply trying to change the representation of the dots, using the pch= function. However R is simply ignoring me! I have also tried removing the dots so that I can place labels instead, but when I type in type="n" it ignores that too!
I am using the exact same format of code that I have used for other plots but this time it just isn't cooperating.
If I specify other features such as the title or the x/y axis labels, it will add those in but it simply ignores the pch or type commands.
This is my basic code:
plot(Differences ~ Time, data=subsetH)
But if I run
plot(Differences ~ Time, type="n", data=subsetH)
or
plot(Differences ~ Time, pch=2, data=subsetH)
it keeps plotting the same thing.
Is there something obvious I have missed?
I just came across your question because I encountered the same thing - creating an empty plot did not work, as type='n' was always ignored (as well as other type specifications).
With the help of this entry: Plotting time-series with Date labels on x-axis
I realized that my date format needed to be assigned as "date" class (as.Date()).
I know your entry dates back a little bit already, but maybe it's still useful.
I am currently trying to plot some data and don't manage to obtain a nice result. I have a set of 51 individuals with each a specific value (Pn) and split within 14 groups. The closest thing I end up with is this kind of plot. I obtain it thanks to the simple code bellow, starting by ordering my values for the Individuals :
Individuals <- factor(Individuals,levels=Individuals[order(Pn)])
dotchart(Pn,label=Individuals,color=Groups)
The issue is that I only have 9 colors on this plot (so I lost information somehow) and I can't manage to find a way to apply manually one color per group.
I've also try to use the ggplot2 package by reading it could give nice looking things. In that case I can't manage to order properly the Individuals (the previous sorting doesn't seem to have any effect here), plus I end up with only different type of blue for the group representation which is not an efficient way to represent the information given by my data set. The plot I get is accessible here and I used the following code:
ggplot(data=gps)+geom_point(mapping=aes(x=Individuals, y=Pn, color=Groups))
I apologize if this question seems redundant but I couldn't figure a solution on my own, even following some answer given to others...
Thank you in advance!
EDIT: Using the RColorBrewer as suggested bellow sorted out the issue with the colors when I use the ggplot2 package.
I believe you are looking for the scale_color_manual() function within ggplot2. You didn't provide a reproducible example, but try something along the lines of this:
ggplot(data=gps, mapping=aes(x=Individuals, y=Pn, color=Groups))+
geom_point() +
scale_color_manual(values = c('GROUP1' = 'color_value_1',
'GROUP2' = 'color_value_2',
'GROUP3' = 'color_value_3'))
Replace GROUPX with the values inside your Group column, and replace color_value_x with whatever colors you want to use.
A good resource for further learning about ggplot2 is chapter 3 of R For Data Science, which you can read here: http://r4ds.had.co.nz/data-visualisation.html
I can't be sure without looking at your data, but it looks like Groups may be a numeric value. Try this:
gps$Groups <- as.factor(gps$Groups)
library(RColorBrewer)
ggplot(data=gps)+
geom_point(mapping=aes(x=Individuals, y=Pn, color=Groups))+
scale_colour_brewer(palette = "Set1")
I'm using the excellent dygraphs R package. One thing that I don't seem to find in the documentation is the possibility of passing a formatting function to dyLegend in the same way it's possible for dyAxis (e.g. valueAxisFormatter). The legend defaults to scientific notation for values in the millions, which most of my audience does not like.
Does anyone know of a way to pass a JS formatting function?
Thank you.
I have the following plot:
plot.ts(returns)
I have another dataframe ma_sd which contains the rolling SD from moving averages of the above returns. The df is structured exactly like returns. Is there a simple way to add each line to the corresponding plots?
lines(1:N, ma_sd) seemed intuitive, but it does not work.
Thanks
The only way I can see you doing this is to plot them separately. This code is a bit clunky but will allow you full flexibility to be able to specify labels and axis ranges. You can build on this.
par(mfrow=c(3,1),oma=c(5,4,4,2),mar=c(0,0,0,0))
time<-as.data.frame(matrix(c(1:length(returns[,1])),length(returns[,1]),3))
plot(time[,1],returns[,1],type='l',xaxt='n')
points(time[,1],ma_sd[,1],type='l',col='red')
plot(time[,2],returns[,2],type='l',xaxt='n')
points(time[,2],ma_sd[,2],type='l',col='red')
plot(time[,3],returns[,3],type='l')
points(time[,3],ma_sd[,3],type='l',col='red')