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, thatâs 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.
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
To check if values
is not in the DataFrame, use the ~
operator:
>>> ~df.isin([0, 2]) num_legs num_wings falcon False False dog True False
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 âfalconâ does not match based on the number of legs in other.
>>> other = pd.DataFrame({'num_legs': [8, 3], 'num_wings': [0, 2]}, ... index=['spider', 'falcon']) >>> df.isin(other) num_legs num_wings falcon False True dog False False
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