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DOC: update the docstring of pandas.Series.clip #20256

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88 changes: 57 additions & 31 deletions pandas/core/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -5605,53 +5605,79 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
"""
Trim values at input threshold(s).

Assigns values outside boundary to boundary values. Thresholds
can be singular values or array like, and in the latter case
the clipping is performed element-wise in the specified axis.

Parameters
----------
lower : float or array_like, default None
Minimum threshold value. All values below this
threshold will be set to it.
upper : float or array_like, default None
Maximum threshold value. All values above this
threshold will be set to it.
axis : int or string axis name, optional
Align object with lower and upper along the given axis.
inplace : boolean, default False
Whether to perform the operation in place on the data
.. versionadded:: 0.21.0
Whether to perform the operation in place on the data.

.. versionadded:: 0.21.0
*args, **kwargs
Additional keywords have no effect but might be accepted
for compatibility with numpy.

See Also
--------
clip_lower : Clip values below specified threshold(s).
clip_upper : Clip values above specified threshold(s).

Returns
-------
clipped : Series
Series or DataFrame
Same type as calling object with the values outside the
clip boundaries replaced

Examples
--------
>>> data = {'col_0': [9, -3, 0, -1, 5], 'col_1': [-2, -7, 6, 8, -5]}
>>> df = pd.DataFrame(data)
>>> df
0 1
0 0.335232 -1.256177
1 -1.367855 0.746646
2 0.027753 -1.176076
3 0.230930 -0.679613
4 1.261967 0.570967

>>> df.clip(-1.0, 0.5)
0 1
0 0.335232 -1.000000
1 -1.000000 0.500000
2 0.027753 -1.000000
3 0.230930 -0.679613
4 0.500000 0.500000

col_0 col_1
0 9 -2
1 -3 -7
2 0 6
3 -1 8
4 5 -5

Clips per column using lower and upper thresholds:

>>> df.clip(-4, 6)
col_0 col_1
0 6 -2
1 -3 -4
2 0 6
3 -1 6
4 5 -4

Clips using specific lower and upper thresholds per column element:

>>> t = pd.Series([2, -4, -1, 6, 3])
>>> t
0 -0.3
1 -0.2
2 -0.1
3 0.0
4 0.1
dtype: float64
0 2
1 -4
2 -1
3 6
4 3
dtype: int64

>>> df.clip(t, t + 1, axis=0)
0 1
0 0.335232 -0.300000
1 -0.200000 0.746646
2 0.027753 -0.100000
3 0.230930 0.000000
4 1.100000 0.570967
>>> df.clip(t, t + 4, axis=0)
col_0 col_1
0 6 2
1 -3 -4
2 0 3
3 6 8
4 5 3
"""
if isinstance(self, ABCPanel):
raise NotImplementedError("clip is not supported yet for panels")
Expand Down