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DOC: Improve the docstring of pandas.core.window.Rolling.median #20260

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Merged
merged 9 commits into from
Mar 13, 2018
Merged

DOC: Improve the docstring of pandas.core.window.Rolling.median #20260

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2032776
added docstring to core.window median
mehemken Mar 10, 2018
afb9515
using np.arange instead of np.random.randn
mehemken Mar 10, 2018
ad3572c
Merge remote-tracking branch 'upstream/master' into docstring-update-…
mehemken Mar 10, 2018
6a1106a
new docstring for pandas.core.window.Rolling.median
mehemken Mar 10, 2018
80ce2fc
proofreading led to changes.
mehemken Mar 10, 2018
6280b68
including suggested edits by dukebody and JoanMartin
mehemken Mar 12, 2018
6ee9acd
Example copy paste was mean. Changed it ot median.
mehemken Mar 12, 2018
1794aca
Update kwargs description
TomAugspurger Mar 13, 2018
702abc4
Grammar
TomAugspurger Mar 13, 2018
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38 changes: 35 additions & 3 deletions pandas/core/window.py
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Original file line number Diff line number Diff line change
Expand Up @@ -850,7 +850,41 @@ def mean(self, *args, **kwargs):
return self._apply('roll_mean', 'mean', **kwargs)

_shared_docs['median'] = dedent("""
%(name)s median
Calculate the %(name)s median.

Parameters
----------
**kwargs
Under Review.

Returns
-------
Series or DataFrame
Returned object type is determined by the caller of the %(name)s
object.

See Also
--------
Series.%(name)s : Calling object with Series data
DataFrame.%(name)s : Calling object with DataFrames
Series.median : Equivalent method for Series
DataFrame.median : Equivalent method for DataFrame

Examples
--------
The below example will show a rolling calculation with a window size of
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I'd be more direct and say "Compute the rolling mean of a series with a window size of 3:".

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I agree... but this is median. Copy paste has failed me!

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Ah yes median, sorry.

three.

>>> import pandas as pd
>>> import numpy as np
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Import pandas and numpy is not necessary in the examples.

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Good to know. I've removed them.

>>> s = pd.Series(np.arange(5))
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Perhaps construct the series manually to avoid the reader having to think about arange:

s = pd.Series([0, 1, 2, 3, 4])

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That make sense. I've changed it from arange to a simple list

>>> s.rolling(3).median()
0 NaN
1 NaN
2 1.0
3 2.0
4 3.0
dtype: float64
""")

def median(self, **kwargs):
Expand Down Expand Up @@ -1244,7 +1278,6 @@ def mean(self, *args, **kwargs):
return super(Rolling, self).mean(*args, **kwargs)

@Substitution(name='rolling')
@Appender(_doc_template)
@Appender(_shared_docs['median'])
def median(self, **kwargs):
return super(Rolling, self).median(**kwargs)
Expand Down Expand Up @@ -1483,7 +1516,6 @@ def mean(self, *args, **kwargs):
return super(Expanding, self).mean(*args, **kwargs)

@Substitution(name='expanding')
@Appender(_doc_template)
@Appender(_shared_docs['median'])
def median(self, **kwargs):
return super(Expanding, self).median(**kwargs)
Expand Down