pandas.Series.reset_index — pandas 2.2.3 documentation (original) (raw)
Series.reset_index(level=None, *, drop=False, name=<no_default>, inplace=False, allow_duplicates=False)[source]#
Generate a new DataFrame or Series with the index reset.
This is useful when the index needs to be treated as a column, or when the index is meaningless and needs to be reset to the default before another operation.
Parameters:
levelint, str, tuple, or list, default optional
For a Series with a MultiIndex, only remove the specified levels from the index. Removes all levels by default.
dropbool, default False
Just reset the index, without inserting it as a column in the new DataFrame.
nameobject, optional
The name to use for the column containing the original Series values. Uses self.name
by default. This argument is ignored when drop is True.
inplacebool, default False
Modify the Series in place (do not create a new object).
allow_duplicatesbool, default False
Allow duplicate column labels to be created.
Added in version 1.5.0.
Returns:
Series or DataFrame or None
When drop is False (the default), a DataFrame is returned. The newly created columns will come first in the DataFrame, followed by the original Series values. When drop is True, a Series is returned. In either case, if inplace=True
, no value is returned.
Examples
s = pd.Series([1, 2, 3, 4], name='foo', ... index=pd.Index(['a', 'b', 'c', 'd'], name='idx'))
Generate a DataFrame with default index.
s.reset_index() idx foo 0 a 1 1 b 2 2 c 3 3 d 4
To specify the name of the new column use name.
s.reset_index(name='values') idx values 0 a 1 1 b 2 2 c 3 3 d 4
To generate a new Series with the default set drop to True.
s.reset_index(drop=True) 0 1 1 2 2 3 3 4 Name: foo, dtype: int64
The level parameter is interesting for Series with a multi-level index.
arrays = [np.array(['bar', 'bar', 'baz', 'baz']), ... np.array(['one', 'two', 'one', 'two'])] s2 = pd.Series( ... range(4), name='foo', ... index=pd.MultiIndex.from_arrays(arrays, ... names=['a', 'b']))
To remove a specific level from the Index, use level.
s2.reset_index(level='a') a foo b one bar 0 two bar 1 one baz 2 two baz 3
If level is not set, all levels are removed from the Index.
s2.reset_index() a b foo 0 bar one 0 1 bar two 1 2 baz one 2 3 baz two 3