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pandas.Panel.clip_upper

Panel.clip_upper(threshold, axis=None, inplace=False)[source]

Trim values above a given threshold.

Elements above the threshold will be changed to match the threshold value(s). Threshold can be a single value or an array, in the latter case it performs the truncation element-wise.

Parameters:

threshold : numeric or array-like

Maximum value allowed. All values above threshold will be set to this value.

  • float : every value is compared to threshold.
  • array-like : The shape of threshold should match the object it’s compared to. When self is a Series, threshold should be the length. When self is a DataFrame, threshold should 2-D and the same shape as self for axis=None, or 1-D and the same length as the axis being compared.

axis : {0 or ‘index’, 1 or ‘columns’}, default 0

Align object with threshold along the given axis.

inplace : boolean, default False

Whether to perform the operation in place on the data.

New in version 0.21.0.

Returns:

clipped

Original data with values trimmed.

See also

DataFrame.clip
General purpose method to trim DataFrame values to given threshold(s)
DataFrame.clip_lower
Trim DataFrame values below given threshold(s)
Series.clip
General purpose method to trim Series values to given threshold(s)
Series.clip_lower
Trim Series values below given threshold(s)

Examples

>>> s = pd.Series([1, 2, 3, 4, 5])
>>> s
0    1
1    2
2    3
3    4
4    5
dtype: int64
>>> s.clip_upper(3)
0    1
1    2
2    3
3    3
4    3
dtype: int64
>>> t = [5, 4, 3, 2, 1]
>>> t
[5, 4, 3, 2, 1]
>>> s.clip_upper(t)
0    1
1    2
2    3
3    2
4    1
dtype: int64
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