pandas.DataFrame.clip_upper

DataFrame.clip_upper(threshold, axis=None, inplace=False)

Trim values above a given threshold.

Deprecated since version 0.24.0: Use clip(upper=threshold) instead.

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:

Series or DataFrame

Original data with values trimmed.

See also

Series.clip

General purpose method to trim Series values to given threshold(s).

DataFrame.clip

General purpose method to trim DataFrame values to 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

>>> elemwise_thresholds = [5, 4, 3, 2, 1]
>>> elemwise_thresholds
[5, 4, 3, 2, 1]

>>> s.clip(upper=elemwise_thresholds)
0    1
1    2
2    3
3    2
4    1
dtype: int64