pandas.Series.clip_upper — pandas 0.24.0rc1 documentation (original) (raw)
Series. clip_upper(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 thethreshold 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
General purpose method to trim Series values to given threshold(s).
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