pandas.DataFrame.isin¶
-
DataFrame.
isin
(values)[source]¶ Whether each element in the DataFrame is contained in values.
Parameters: - values : iterable, Series, DataFrame or dict
The result will only be true at a location if all the labels match. If values is a Series, that’s the index. If values is a dict, the keys must be the column names, which must match. If values is a DataFrame, then both the index and column labels must match.
Returns: - DataFrame
DataFrame of booleans showing whether each element in the DataFrame is contained in values.
See also
DataFrame.eq
- Equality test for DataFrame.
Series.isin
- Equivalent method on Series.
Series.str.contains
- Test if pattern or regex is contained within a string of a Series or Index.
Examples
>>> df = pd.DataFrame({'num_legs': [2, 4], 'num_wings': [2, 0]}, ... index=['falcon', 'dog']) >>> 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
When
values
is a Series or DataFrame the index and column must match. Note that ‘falcon’ does not match based on the number of legs in df2.>>> other = pd.DataFrame({'num_legs': [8, 2],'num_wings': [0, 2]}, ... index=['spider', 'falcon']) >>> df.isin(other) num_legs num_wings falcon True True dog False False