cudf.DataFrame.reset_index

DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='')

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).

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      <NA>
>>> 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      <NA>
>>> df.reset_index(drop=True)
    class max_speed
0    bird     389.0
1    bird      24.0
2  mammal      80.5
3  mammal      <NA>

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   <NA>  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   <NA>  jump