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Classe « DataFrame »

Méthode pandas.DataFrame.isin

Signature de la méthode isin

def isin(self, values: 'Series | DataFrame | Sequence | Mapping') -> 'DataFrame' 

Description

help(DataFrame.isin)

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

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 'falcon' 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

Vous êtes un professionnel et vous avez besoin d'une formation ? Deep Learning avec Python
et Keras et Tensorflow Voir le programme détaillé