Using cdata To Created Faceted Plots

Nina Zumel shows how to use the cdata package to create faceted ggplot2 plots:

First, load the packages and data:

library("ggplot2")library("cdata")
iris <- data.frame(iris)

Now define the data-shaping transform, or control table. The control table is basically a picture that sketches out the final data shape that I want. I want to specify the x and y columns of the plot (call these the value columns of the data frame) and the column that I am faceting by (call this the key column of the data frame). And I also need to specify how the key and value columns relate to the existing columns of the original data frame.

Read on to see how you can use cdata to tie together different faceted plots.

Related Posts

Predicting Intermittent Demand

Bruno Rodrigues shows one technique for forecasting intermittent data: Now, it is clear that this will be tricky to forecast. There is no discernible pattern, no trend, no seasonality… nothing that would make it “easy” for a model to learn how to forecast such data. This is typical intermittent demand data. Specific methods have been […]

Read More

Learning R Versus Python

Andy Kirk shares the results of a rather informal Twitter poll: Yesterday I ran a simple Twitter poll about the relative ease of learning R vs. Python. Although a correct answer to this query will ALWAYS have to be based on nuances like pre-existing skills and the scope of need, this originates from people telling […]

Read More

Categories

October 2018
MTWTFSS
« Sep Nov »
1234567
891011121314
15161718192021
22232425262728
293031