Suppose I generate a multi-index data frame as follows:
arrays = [np.array(['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux']),
np.array(['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two'])]
df = pd.DataFrame(np.random.randn(8, 4), index=arrays)
0 1 2 3
bar one -0.155088 -0.177214 -0.761230 -0.106045
two 1.930298 -0.309573 -0.051878 -0.388760
baz one 0.111287 1.374426 0.408575 1.555659
two -0.809201 -0.168658 0.055037 1.871289
foo one 0.286833 -0.988538 0.918153 0.841016
two 0.348741 0.403747 0.584992 -1.838409
qux one 1.212017 -0.224872 0.616604 1.080590
two 0.494800 -0.089214 0.829222 2.005217
How do I create a new column, which is the ratio between group 'one' and 'two' on the their #3 column value (e.g. first element would be -0.106045 / -0.388760)?
How can I show it in conjunction with the current data frame?
With different random numbers. Use a transform:
In [11]: df.groupby(level=0)[3].transform(lambda x: x[0]/ x[1])
Out[11]:
bar one -1.391651
two -1.391651
baz one -1.688734
two -1.688734
foo one -1.128344
two -1.128344
qux one -2.170493
two -2.170493
Name: 3, dtype: float64
to show this, set it as a column:
In [12]: df["ratio"] = df.groupby(level=0)[3].transform(lambda x: x[0]/ x[1])
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