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Classe « DataFrame »

Méthode pandas.DataFrame.itertuples

Signature de la méthode itertuples

def itertuples(self, index: 'bool' = True, name: 'str | None' = 'Pandas') -> 'Iterable[tuple[Any, ...]]' 

Description

help(DataFrame.itertuples)

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.

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)

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