Select data from external data frame for aesthetics?

[naught101]

Here is some R code, to explain what I want to do:

library(ggplot2)
# Create a dataframe that has a column mean per species:
iris_types <- by(iris[, c('Sepal.Length', 'Sepal.Width', 'Petal.Length', 'Petal.Width')], iris$Species, colMeans)
iris_types_df <-do.call(rbind, iris_types)
# Plot the original data, using the species averages as aesthetics:
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, colour=iris_types_df[iris$Species,'Petal.Length'])) + geom_point()

Which results in:

Is there a way to do the above with python ggplot? I tried doing the same, but it gives an error:

from pandas import rpy
from ggplot import *
iris = rpy.load_data('iris')
iris_types_df = iris.groupby('Species').mean()
ggplot(iris, aes(x='Sepal.Length', y='Sepal.Width', 
                 colour=iris_types_df.ix[iris.Species,'Petal.Length'])) + geom_point()
...
TypeError: 'Series' objects are mutable, thus they cannot be hashed

Obviously, this is a pretty useless example, and I could have just put the means in the original data frame. But some of the data I'm plotting is really big, so putting a handful of cluster means into the original data frame leads to massive data redundancy, requiring lots of extra memory.

[has2k1]

To break it down, there are two issues hidden in this. Being unable to accomplish the same objective by

either

ggplot(iris, aes(x='Sepal.Length', y='Sepal.Width', color=[5]*len(iris))) + geom_point()

or

ggplot(iris, aes(x='Sepal.Length', y='Sepal.Width')) + geom_point(aes(color=[5]*len(iris)))

There is some re-factoring going on -- the conclusion of which should have this both sides of this issue resolved or more straight forward to fix.

[naught101]

So, the two issues are that:

1. aesthetics should accept a list (or Series?) with length equal to the number of rows in the DataFrame, (as opposed to a string specifying a column) and
2. ? that the subsetting is difficult if you're trying to do it via a string?

is #252 the refactoring you're talking about?

[has2k1]

Yes for 1, as long as aesthetics do accept a list or more generally an array-type then your situation should work. The 2nd on has to do with the current state, in that all aes() mappings have to be put in the ggplot call.

#252 is done and the continuation is #266. However, I think it should end up being covered by the refactoring done by @JanSchulz. Somewhere in the comments at #221 is some structure of the refactorings although this issue isn't mentioned explicitly.

[jankatins]

The "accept a list of values" should be easy: that's another if-case in ggplot.ggplot._apply_transforms().

[jankatins]

this will probably be handled in #285

[jankatins]

fun example: :

from pandas import rpy
from ggplot import *
iris = rpy.load_data('iris')
iris_types_df = iris.groupby('Species').mean()
ggplot(iris, aes(x='Sepal.Length', y='Sepal.Width', 
                 colour=iris_types_df.ix[iris.Species,'Petal.Length'])) + geom_point()

I that case len(iris) > len(iris_types_df) but len(iris_types_df.ix[iris.Species,'Petal.Length']) == len(iris)

This is the case from @has2k1, where one specifies a series as a mapping (aes(..., color=[....])) and will be handled in 285.