pandas.Index.array

Index.array

The ExtensionArray of the data backing this Series or Index.

New in version 0.24.0.

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

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]
Scroll To Top