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DOC: adapt example of groupby filter and transform #15624

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DOC: adapt example of groupby filter and transform #15624

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6b681e1
Make example running example
stijnvanhoey Mar 8, 2017
ee90944
Make groupby filter running example
stijnvanhoey Mar 8, 2017
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27 changes: 26 additions & 1 deletion pandas/core/groupby.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2871,7 +2871,22 @@ def transform(self, func, *args, **kwargs):

Examples
--------
>>> import pandas as pd
>>> df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
... 'foo', 'bar'],
... 'B' : ['one', 'one', 'two', 'three',
... 'two', 'two'],
... 'C' : [1, 5, 5, 2, 5, 5],
... 'D' : [2.0, 5., 8., 1., 2., 9.]})
>>> grouped = df.groupby('A')
>>> grouped.transform(lambda x: (x - x.mean()) / x.std())
C D
0 -1.154701 -0.577350
1 0.577350 0.000000
2 0.577350 1.154701
3 -1.154701 -1.000000
4 0.577350 -0.577350
5 0.577350 1.000000

Returns
-------
Expand Down Expand Up @@ -2948,7 +2963,17 @@ def filter(self, func, dropna=True, *args, **kwargs): # noqa

Examples
--------
>>> grouped.filter(lambda x: x.mean() > 0)
>>> import pandas as pd
>>> df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
... 'foo', 'bar'],
... 'B' : [1, 2, 3, 4, 5, 6],
... 'C' : [2.0, 5., 8., 1., 2., 9.]})
>>> grouped = df.groupby('A')
>>> grouped.filter(lambda x: x['B'].mean() > 3.)
A B C
1 bar 2 5.0
3 bar 4 1.0
5 bar 6 9.0

Returns
-------
Expand Down