pandas.DataFrame.clip_upper¶
-
DataFrame.
clip_upper
(self, threshold, axis=None, inplace=False)[source]¶ 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 : bool, 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