pandas.DatetimeIndex.to_series#

DatetimeIndex.to_series(index=None, name=None)[source]#

Create a Series with both index and values equal to the index keys.

Useful with map for returning an indexer based on an index.

Parameters:
indexIndex, optional

Index of resulting Series. If None, defaults to original index.

namestr, optional

Name of resulting Series. If None, defaults to name of original index.

Returns:
Series

The dtype will be based on the type of the Index values.

See also

Index.to_frame

Convert an Index to a DataFrame.

Series.to_frame

Convert Series to DataFrame.

Examples

>>> idx = pd.Index(['Ant', 'Bear', 'Cow'], name='animal')

By default, the original index and original name is reused.

>>> idx.to_series()
animal
Ant      Ant
Bear    Bear
Cow      Cow
Name: animal, dtype: object

To enforce a new index, specify new labels to index:

>>> idx.to_series(index=[0, 1, 2])
0     Ant
1    Bear
2     Cow
Name: animal, dtype: object

To override the name of the resulting column, specify name:

>>> idx.to_series(name='zoo')
animal
Ant      Ant
Bear    Bear
Cow      Cow
Name: zoo, dtype: object