pandas.Series.array — pandas 0.24.0rc1 documentation (original) (raw)
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. |
|---|
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 use Series.to_numpy() instead.
Examples
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]