pandas.Series.array¶
-
Series.
array
¶ The ExtensionArray of the data backing this Series or Index.
New in version 0.24.0.
Returns: - array : 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 aarrays.NumpyExtensionArray
wrapping the actual ndarray stored within. If you absolutely need a NumPy array (possibly with copying / coercing data), then useSeries.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]