pandas.core.resample.Resampler.nearest#

final Resampler.nearest(limit=None)[source]#

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:

limitint, optional: Limit of how many values to fill.

Returns:

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

See also

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: 15min, 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: 15min, dtype: float64