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DOC: update pandas.core.resample.Resampler.nearest docstring #20381

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52 changes: 46 additions & 6 deletions pandas/core/resample.py
Original file line number Diff line number Diff line change
Expand Up @@ -418,23 +418,63 @@ def pad(self, limit=None):

def nearest(self, limit=None):
"""
Fill values with nearest neighbor starting from center
Resample by using the nearest value.

When resampling data, missing values may appear (e.g., when the
resampling frequency is higher than the original frequency).
The `nearest` method will replace ``NaN`` values that appeared in
the resampled data with the value from the nearest member of the
sequence, based on the index value.
Missing values that existed in the original data will not be modified.
If `limit` is given, fill only this many values in each direction for
each of the original values.

Parameters
----------
limit : integer, optional
limit of how many values to fill
limit : int, optional
Limit of how many values to fill.

.. versionadded:: 0.21.0

Returns
-------
an upsampled Series
Series or DataFrame
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@datapythonista do we have a convention for saying same-type-as-input?

An upsampled Series or DataFrame with ``NaN`` values filled with
their nearest value.

See Also
--------
Series.fillna
DataFrame.fillna
backfill : Backward fill the new missing values in the resampled data.
pad : Forward fill ``NaN`` values.

Examples
--------
>>> s = pd.Series([1, 2],
... index=pd.date_range('20180101',
... periods=2,
... freq='1h'))
>>> s
2018-01-01 00:00:00 1
2018-01-01 01:00:00 2
Freq: H, dtype: int64

>>> s.resample('15min').nearest()
2018-01-01 00:00:00 1
2018-01-01 00:15:00 1
2018-01-01 00:30:00 2
2018-01-01 00:45:00 2
2018-01-01 01:00:00 2
Freq: 15T, dtype: int64

Limit the number of upsampled values imputed by the nearest:

>>> s.resample('15min').nearest(limit=1)
2018-01-01 00:00:00 1.0
2018-01-01 00:15:00 1.0
2018-01-01 00:30:00 NaN
2018-01-01 00:45:00 2.0
2018-01-01 01:00:00 2.0
Freq: 15T, dtype: float64
"""
return self._upsample('nearest', limit=limit)

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