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pandas.Series.reset_index

Series.reset_index(level=None, drop=False, name=None, inplace=False)[source]

Analogous to the pandas.DataFrame.reset_index() function, see docstring there.

Parameters:

level : int, str, tuple, or list, default None

Only remove the given levels from the index. Removes all levels by default

drop : boolean, default False

Do not try to insert index into dataframe columns

name : object, default None

The name of the column corresponding to the Series values

inplace : boolean, default False

Modify the Series in place (do not create a new object)

Returns:

resetted : DataFrame, or Series if drop == True

Examples

>>> s = pd.Series([1, 2, 3, 4], index=pd.Index(['a', 'b', 'c', 'd'],
...                                            name = 'idx'))
>>> s.reset_index()
     idx  0
0      0  1
1      1  2
2      2  3
3      3  4
>>> arrays = [np.array(['bar', 'bar', 'baz', 'baz', 'foo',
...                     'foo', 'qux', 'qux']),
...           np.array(['one', 'two', 'one', 'two', 'one', 'two',
...                     'one', 'two'])]
>>> s2 = pd.Series(
...     np.random.randn(8),
...     index=pd.MultiIndex.from_arrays(arrays,
...                                     names=['a', 'b']))
>>> s2.reset_index(level='a')
       a         0
b
one  bar -0.286320
two  bar -0.587934
one  baz  0.710491
two  baz -1.429006
one  foo  0.790700
two  foo  0.824863
one  qux -0.718963
two  qux -0.055028
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