pyspark.pandas.DataFrame.isin#

DataFrame.isin(values)[source]#

Whether each element in the DataFrame is contained in values.

Parameters:

valuesiterable or dict: The sequence of values to test. If values are a dict, the keys must be the column names, which must match. Series and DataFrame are not supported.

Returns:

DataFrame: DataFrame of booleans showing whether each element in the DataFrame is contained in values.

Examples

>>> df = ps.DataFrame({'num_legs': [2, 4], 'num_wings': [2, 0]},
...                   index=['falcon', 'dog'],
...                   columns=['num_legs', 'num_wings'])
>>> df
        num_legs  num_wings
falcon         2          2
dog            4          0

When values is a list check whether every value in the DataFrame is present in the list (which animals have 0 or 2 legs or wings)

>>> df.isin([0, 2])
        num_legs  num_wings
falcon      True       True
dog        False       True

When values is a dict, we can pass values to check for each column separately:

>>> df.isin({'num_wings': [0, 3]})
        num_legs  num_wings
falcon     False      False
dog        False       True