bigframes.pandas.DatetimeIndex.to_series#

DatetimeIndex.to_series(index: Index | None = None, name: Hashable | None = None) → Series#

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

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

Examples:

>>> idx = bpd.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: string

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: string

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: string

Parameters:

index (Index, optional) – Index of resulting Series. If None, defaults to original index.
name (str, optional) – Name of resulting Series. If None, defaults to name of original index.

Returns:

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

Return type:

bigframes.pandas.Series