The ExtensionArray of the data backing this Series or Index.

New in version 0.24.0.


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

Similar method that always returns a NumPy array.
Similar method that always returns a NumPy array.


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
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.


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

>>> pd.Series([1, 2, 3]).array
[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]
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