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() index 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