cudf.DataFrame.reset_index#

DataFrame.reset_index( level=None, drop=False, inplace=False, col_level=0, col_fill='', allow_duplicates: bool = False, names: Hashable | Sequence[Hashable] | None = None, )[source]#

Reset the index of the DataFrame, or a level of it.

Parameters:

levelint, str, tuple, or list, default None: Only remove the given levels from the index. Removes all levels by default.
dropbool, default False: Do not try to insert index into dataframe columns. This resets the index to the default integer index.
inplacebool, default False: Modify the DataFrame in place (do not create a new object).
allow_duplicatesbool, default False: Allow duplicate column labels to be created. Currently not supported.

Returns:

DataFrame or None: DataFrame with the new index or None if inplace=True.

Examples

>>> df = cudf.DataFrame([('bird', 389.0),
...                    ('bird', 24.0),
...                    ('mammal', 80.5),
...                    ('mammal', np.nan)],
...                   index=['falcon', 'parrot', 'lion', 'monkey'],
...                   columns=('class', 'max_speed'))
>>> df
         class max_speed
falcon    bird     389.0
parrot    bird      24.0
lion    mammal      80.5
monkey  mammal       NaN
>>> df.reset_index()
    index   class max_speed
0  falcon    bird     389.0
1  parrot    bird      24.0
2    lion  mammal      80.5
3  monkey  mammal       NaN
>>> df.reset_index(drop=True)
    class max_speed
0    bird     389.0
1    bird      24.0
2  mammal      80.5
3  mammal       NaN

You can also use reset_index with MultiIndex.

>>> index = cudf.MultiIndex.from_tuples([('bird', 'falcon'),
...                                     ('bird', 'parrot'),
...                                     ('mammal', 'lion'),
...                                     ('mammal', 'monkey')],
...                                     names=['class', 'name'])
>>> df = cudf.DataFrame([(389.0, 'fly'),
...                      ( 24.0, 'fly'),
...                      ( 80.5, 'run'),
...                      (np.nan, 'jump')],
...                      index=index,
...                      columns=('speed', 'type'))
>>> df
               speed  type
class  name
bird   falcon  389.0   fly
       parrot   24.0   fly
mammal lion     80.5   run
       monkey    NaN  jump
>>> df.reset_index(level='class')
         class  speed  type
name
falcon    bird  389.0   fly
parrot    bird   24.0   fly
lion    mammal   80.5   run
monkey  mammal    NaN  jump