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# pandas.DatetimeIndex.to_series

DatetimeIndex.to_series(index=None, name=None)

  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:
    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:
    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: str

  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: str

  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: str