Classe « DataFrame »

Méthode pandas.DataFrame.itertuples

Signature de la méthode itertuples

def itertuples(self, index: 'bool' = True, name: 'Optional[str]' = 'Pandas') 

Description

itertuples.__doc__

        Iterate over DataFrame rows as namedtuples.

        Parameters
        ----------
        index : bool, default True
            If True, return the index as the first element of the tuple.
        name : str or None, default "Pandas"
            The name of the returned namedtuples or None to return regular
            tuples.

        Returns
        -------
        iterator
            An object to iterate over namedtuples for each row in the
            DataFrame with the first field possibly being the index and
            following fields being the column values.

        See Also
        --------
        DataFrame.iterrows : Iterate over DataFrame rows as (index, Series)
            pairs.
        DataFrame.items : Iterate over (column name, Series) pairs.

        Notes
        -----
        The column names will be renamed to positional names if they are
        invalid Python identifiers, repeated, or start with an underscore.
        On python versions < 3.7 regular tuples are returned for DataFrames
        with a large number of columns (>254).

        Examples
        --------
        >>> df = pd.DataFrame({'num_legs': [4, 2], 'num_wings': [0, 2]},
        ...                   index=['dog', 'hawk'])
        >>> df
              num_legs  num_wings
        dog          4          0
        hawk         2          2
        >>> for row in df.itertuples():
        ...     print(row)
        ...
        Pandas(Index='dog', num_legs=4, num_wings=0)
        Pandas(Index='hawk', num_legs=2, num_wings=2)

        By setting the `index` parameter to False we can remove the index
        as the first element of the tuple:

        >>> for row in df.itertuples(index=False):
        ...     print(row)
        ...
        Pandas(num_legs=4, num_wings=0)
        Pandas(num_legs=2, num_wings=2)

        With the `name` parameter set we set a custom name for the yielded
        namedtuples:

        >>> for row in df.itertuples(name='Animal'):
        ...     print(row)
        ...
        Animal(Index='dog', num_legs=4, num_wings=0)
        Animal(Index='hawk', num_legs=2, num_wings=2)