pyspark.pandas.DataFrame.clip¶
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DataFrame.clip(lower: Union[float, int] = None, upper: Union[float, int] = None) → pyspark.pandas.frame.DataFrame[source]¶ Trim values at input threshold(s).
Assigns values outside boundary-to-boundary values.
- Parameters
- lowerfloat or int, default None
Minimum threshold value. All values below this threshold will be set to it.
- upperfloat or int, default None
Maximum threshold value. All values above this threshold will be set to it.
- Returns
- DataFrame
DataFrame with the values outside the clip boundaries replaced.
Notes
One difference between this implementation and pandas is that running pd.DataFrame({‘A’: [‘a’, ‘b’]}).clip(0, 1) will crash with “TypeError: ‘<=’ not supported between instances of ‘str’ and ‘int’” while ps.DataFrame({‘A’: [‘a’, ‘b’]}).clip(0, 1) will output the original DataFrame, simply ignoring the incompatible types.
Examples
>>> ps.DataFrame({'A': [0, 2, 4]}).clip(1, 3) A 0 1 1 2 2 3