pandas.arrays.StringArray#
- class pandas.arrays.StringArray(values, copy=False)[source]#
Extension array for string data.
Warning
StringArray is considered experimental. The implementation and parts of the API may change without warning.
- Parameters:
- valuesarray-like
The array of data.
Warning
Currently, this expects an object-dtype ndarray where the elements are Python strings or nan-likes (
None
,np.nan
,NA
). This may change without warning in the future. Usepandas.array()
withdtype="string"
for a stable way of creating a StringArray from any sequence.Changed in version 1.5.0: StringArray now accepts array-likes containing nan-likes(
None
,np.nan
) for thevalues
parameter in addition to strings andpandas.NA
- copybool, default False
Whether to copy the array of data.
See also
pandas.array()
The recommended function for creating a StringArray.
Series.str
The string methods are available on Series backed by a StringArray.
Notes
StringArray returns a BooleanArray for comparison methods.
Examples
>>> pd.array(['This is', 'some text', None, 'data.'], dtype="string") <StringArray> ['This is', 'some text', <NA>, 'data.'] Length: 4, dtype: string
Unlike arrays instantiated with
dtype="object"
,StringArray
will convert the values to strings.>>> pd.array(['1', 1], dtype="object") <NumpyExtensionArray> ['1', 1] Length: 2, dtype: object >>> pd.array(['1', 1], dtype="string") <StringArray> ['1', '1'] Length: 2, dtype: string
However, instantiating StringArrays directly with non-strings will raise an error.
For comparison methods, StringArray returns a
pandas.BooleanArray
:>>> pd.array(["a", None, "c"], dtype="string") == "a" <BooleanArray> [True, <NA>, False] Length: 3, dtype: boolean
Attributes
None
Methods
None