Healthy Algorithms

The Python Pandas DataFrame object has become the mainstay of my data manipulation work over the last two years. One thing that I like about it is the `.describe()` method, that computes lots of interesting things about columns of a table. I often want those results stratified, and `.groupby(col)` + `.describe()` is a powerful combination for doing that.

*But* today, and many days, I don’t want all of the things that `.describe()` describes. And the ones that I do want, I want as columns. Here is the recipe for that:

import pandas as pd

df = pd.DataFrame({'A': [0,0,0,0,1,1],
                   'B': [1,2,3,4,5,6],
                   'C': [8,9,10,11,12,13]})

df.groupby('A').describe().unstack()\
    .loc[:,(slice(None),['count','mean']),]

and out comes just what I wanted:

       B            C
   count  mean  count  mean
A
0      4   2.5      4   9.5
1      2   5.5      2  12.5

It took me a while to figure this out, and these docs helped:
http://pandas.pydata.org/pandas-docs/stable/reshaping.html#reshaping-by-stacking-and-unstacking
http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-xs

Here it is as a ipython notebook.

(Note: this requires Pandas version at least 0.14.)