# pandas.Series.array

property Series.array

  The ExtensionArray of the data backing this Series or Index.

  Returns
    ExtensionArray

      An ExtensionArray of the values stored within. For extension types, this is the actual array. For NumPy native types, this is a thin (no copy) wrapper around `numpy.ndarray`.

      `.array` differs `.values` which may require converting the data to a different form.

  See also

  `Index.to_numpy`

    Similar method that always returns a NumPy array.

  `Series.to_numpy`

    Similar method that always returns a NumPy array.

  Notes

  This table lays out the different array types for each extension dtype within pandas.

  dtype | array type
  --- | ---
  category | Categorical
  period | PeriodArray
  interval | IntervalArray
  IntegerNA | IntegerArray
  string | StringArray
  boolean | BooleanArray
  datetime64[ns, tz] | DatetimeArray

  For any 3rd-party extension types, the array type will be an ExtensionArray.

  For all remaining dtypes `.array` will be a `arrays.NumpyExtensionArray` wrapping the actual ndarray stored within. If you absolutely need a NumPy array (possibly with copying / coercing data), then use `Series.to_numpy()` instead.

  Examples

  For regular NumPy types like int, and float, a PandasArray is returned.

      >>> pd.Series([1, 2, 3]).array
      <PandasArray>
      [1, 2, 3]
      Length: 3, dtype: int64

  For extension types, like Categorical, the actual ExtensionArray is returned

      >>> ser = pd.Series(pd.Categorical(['a', 'b', 'a']))
      >>> ser.array
      ['a', 'b', 'a']
      Categories (2, object): ['a', 'b']