I'm looking for an easier way to draw the cumulative distribution line in ggplot.
I have some data whose histogram I can immediately display with
qplot (mydata, binwidth=1);
I found a way to do it at http://www.r-tutor.com/elementary-statistics/quantitative-data/cumulative-frequency-graph but it involves several steps and when exploring data it's time consuming.
Is there a way to do it in a more straightforward way in ggplot, similar to how trend lines and confidence intervals can be added by specifying options?
To create a cumulative sum plot in base R, we can simply use plot function. For cumulative sums inside the plot, the cumsum function needs to be used for the variable that has to be summed up with cumulation.
The cumulative frequency table can be calculated by the frequency table, using the cumsum() method. This method returns a vector whose corresponding elements are the cumulative sums.
If we want to convert our histogram to a cumulative histogram, we can use the cumsum function within the geom_histogram function as shown below: ggplot(data, aes(x)) + # Draw cumulative ggplot2 histogram geom_histogram(aes(y = cumsum(..count..)))
The new version of ggplot2 (0.9.2.1) has a built-in stat_ecdf() function which let's you plot cumulative distributions very easily.
qplot(rnorm(1000), stat = "ecdf", geom = "step")
Or
df <- data.frame(x = c(rnorm(100, 0, 3), rnorm(100, 0, 10)), g = gl(2, 100)) ggplot(df, aes(x, colour = g)) + stat_ecdf()
Code samples from ggplot2 documentation.
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