How to annotate subplots with ggplot from rpy2?

Question

I'm using Rpy2 to plot dataframes with ggplot2. I make the following plot:

p = ggplot2.ggplot(iris) + \
    ggplot2.geom_point(ggplot2.aes_string(x="Sepal.Length", y="Sepal.Width")) + \
    ggplot2.facet_wrap(Formula("~Species"))
p.plot()
r["dev.off"]()

I'd like to annotate each subplot with some statistics about the plot. For example, I'd like to compute the correlation between each x/y subplot and place it on the top right corner of the plot. How can this be done? Ideally I'd like to convert the dataframe from R to a Python object, compute the correlations and then project them onto the scatters. The following conversion does not work, but this is how I'm trying to do it:

# This does not work 
#iris_df = pandas.DataFrame({"Sepal.Length": rpy2.robjects.default_ri2py(iris.rx("Sepal.Length")),
#                            "Sepal.Width": rpy2.robjects.default_ri2py(iris.rx("Sepal.Width")),
#                            "Species": rpy2.robjects.default_ri2py(iris.rx("Species"))})
# So we access iris using R to compute the correlation
x = iris_py.rx("Sepal.Length")
y = iris_py.rx("Sepal.Width")
# compute r.cor(x, y) and divide up by Species
# Assume we get a vector of length Species saying what the
# correlation is for each Species' Petal Length/Width
p = ggplot2.ggplot(iris) + \
    ggplot2.geom_point(ggplot2.aes_string(x="Sepal.Length", y="Sepal.Width")) + \
    ggplot2.facet_wrap(Formula("~Species")) + \
    # ...
    # How to project correlation?
p.plot()
r["dev.off"]()

But assuming I could actually access the R dataframe from Python, how could I plot these correlations? thanks.

user248237 · Accepted Answer · 2013-02-18 04:40:37Z

1

The solution is to create a dataframe with a label for each sample plotted. The dataframe's column should match the corresponding column name of the dataframe with the original data. Then this can be plotted with:

p += ggplot2.geom_text(data=labels_df, mapping=ggplot2.aes_string(x="1", y="1", mapping="labels"))

where labels_df is the dataframe containing the labels and labels is the column name of labels_df with the labels to be plotted. (1,1) in this case will be the coordinate position of the label in each subplot.

answered Feb 18, 2013 at 4:40

user248237

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ganong · Accepted Answer · 2016-06-28 19:51:48Z

I found that @user248237dfsf's answer didn't work for me. ggplot got confused between the data frame I was plotting and the data frame I was using for labels.

Instead, I used ggplot2_env = robjects.baseenv'as.environment'

class GBaseObject(robjects.RObject):
  @classmethod
  def new(*args, **kwargs):
    args_list = list(args)
    cls = args_list.pop(0)
    res = cls(cls._constructor(*args_list, **kwargs))
    return res

class Annotate(GBaseObject):
  _constructor = ggplot2_env['annotate']
annotate = Annotate.new

Now, I have something that works just like the standard annotate.

annotate(geom = "text", x = 1, y = 1, label = "MPC")

One minor comment: I don't know if this will work with faceting.

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