Details
-
Bug
-
Status: Resolved
-
Major
-
Resolution: Fixed
-
9.0.0
Description
user@ thread: https://lists.apache.org/thread/dhnxq0g4kgdysjowftfv3z5ngj780xpb
repro gist: https://gist.github.com/changhiskhan/4163f8cec675a2418a69ec9168d5fdd9
Arrow => numpy/pandas
For a non-nested array, pa.ExtensionArray.to_numpy automatically "lowers" to the storage type (as expected). However this is not done for nested arrays:
import pyarrow as pa class LabelType(pa.ExtensionType): def __init__(self): super(LabelType, self).__init__(pa.string(), "label") def __arrow_ext_serialize__(self): return b"" @classmethod def __arrow_ext_deserialize__(cls, storage_type, serialized): return LabelType() storage = pa.array(["dog", "cat", "horse"]) ext_arr = pa.ExtensionArray.from_storage(LabelType(), storage) offsets = pa.array([0, 1]) list_arr = pa.ListArray.from_arrays(offsets, ext_arr) list_arr.to_numpy()
---------------------------------------------------------------------------
ArrowNotImplementedError Traceback (most recent call last)
Cell In [15], line 1
----> 1 list_arr.to_numpy()
File /mnt/lance/.venv/lance/lib/python3.10/site-packages/pyarrow/array.pxi:1445, in pyarrow.lib.Array.to_numpy()
File /mnt/lance/.venv/lance/lib/python3.10/site-packages/pyarrow/error.pxi:121, in pyarrow.lib.check_status()
ArrowNotImplementedError: Not implemented type for Arrow list to pandas: extension<label<LabelType>>
As mentioned on the user thread linked from the top, a fairly generic solution would just have the conversion default to the storage array's to_numpy.
pandas/numpy => Arrow
Equivalently, conversion to Arrow is also difficult for nested extension types:
if I have say a pandas DataFrame that has a column of list-of-string and I want to convert that to list-of-label Array. Currently I have to:
1. Convert to list-of-string (storage) numpy array to pa.list_(pa.string())
2. Convert the string values array to ExtensionArray, then reconstitue a list<extension> array using the ExtensionArray combined with the offsets from the result of step 1
import pyarrow as pa import pandas as pd df = pd.DataFrame({'labels': [["dog", "horse", "cat"], ["person", "person", "car", "car"]]}) list_of_storage = pa.array(df.labels) ext_values = pa.ExtensionArray.from_storage(LabelType(), list_of_storage.values) list_of_ext = pa.ListArray.from_arrays(offsets=list_of_storage.offsets, values=ext_values)
For non-nested columns, one can achieve easier conversion by defining a pandas extension dtype, but i don't think that works for a nested column. You would instead have to fallback to something like `pa.ExtensionArray.from_storage` (or `from_pandas`?) to do the trick. Even that doesn't necessarily work for something like a dictionary column because you'd have to pass in the dictionary somehow. Off the cuff, one could provide a custom lambda to `pa.Table.from_pandas` that is used for either specified column names / data types?
Thanks in advance for the consideration!
Attachments
Issue Links
- relates to
-
ARROW-17535 [Python] List<Extension> arrays aren't supported in to_pandas calls
-
- Open
-
-
ARROW-17925 [Python] Use ExtensionScalar.as_py() as fallback in ExtensionArray to_pandas?
-
- Open
-
-
ARROW-17834 [Python] Allow creating ExtensionArray through pa.array(..) constructor
-
- Resolved
-
- links to