DataFrame.
isin
Whether each element in the DataFrame is contained in values.
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.
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)
values
>>> 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