Chang She created ARROW-17813: --------------------------------- Summary: [Python] Nested ExtensionArray conversion to/from pandas/numpy Key: ARROW-17813 URL: https://issues.apache.org/jira/browse/ARROW-17813 Project: Apache Arrow Issue Type: Bug Components: Python Affects Versions: 9.0.0 Reporter: Chang She
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: {code:python} 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() {code} {code:java} --------------------------------------------------------------------------- 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>> {code} 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 {code:python} 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) {code} 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! -- This message was sent by Atlassian Jira (v8.20.10#820010)