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Francois Saint-Jacques edited comment on ARROW-3586 at 12/3/18 7:49 PM: ------------------------------------------------------------------------ Is this possible this was solved in the master branch? I can't seem to reproduce locally. {code:java} for t in [pa.int32(), pa.int64(), pa.float32(), pa.float64()]: print(pa.Table.from_arrays(arrays=[pa.array([], type=t)], names=['col']).to_pandas(categories=['col'])) Empty DataFrame Columns: [col] Index: [] Empty DataFrame Columns: [col] Index: [] Empty DataFrame Columns: [col] Index: [] Empty DataFrame Columns: [col] Index: [] for t in [pa.int32(), pa.int64(), pa.float32(), pa.float64()]: print(pa.Table.from_arrays(arrays=[pa.array([1,2,3], type=t)], names=['col']).to_pandas(categories=['col'])) col 0 1 1 2 2 3 col 0 1 1 2 2 3 col 0 1.0 1 2.0 2 3.0 col 0 1.0 1 2.0 2 3.0 {code} was (Author: fsaintjacques): Is this possible this was solved in the master branch? I can't seem to reproduce locally. ``` for t in [pa.int32(), pa.int64(), pa.float32(), pa.float64()]: print(pa.Table.from_arrays(arrays=[pa.array([], type=t)], names=['col']).to_pandas(categories=['col'])) Empty DataFrame Columns: [col] Index: [] Empty DataFrame Columns: [col] Index: [] Empty DataFrame Columns: [col] Index: [] Empty DataFrame Columns: [col] Index: [] for t in [pa.int32(), pa.int64(), pa.float32(), pa.float64()]: print(pa.Table.from_arrays(arrays=[pa.array([1,2,3], type=t)], names=['col']).to_pandas(categories=['col'])) col 0 1 1 2 2 3 col 0 1 1 2 2 3 col 0 1.0 1 2.0 2 3.0 col 0 1.0 1 2.0 2 3.0 ``` > [Python] Segmentation fault when converting empty table to pandas with > categoricals > ----------------------------------------------------------------------------------- > > Key: ARROW-3586 > URL: https://issues.apache.org/jira/browse/ARROW-3586 > Project: Apache Arrow > Issue Type: Bug > Affects Versions: 0.10.0, 0.11.0 > Environment: - Ubuntu 16.04, Python 2.7.12, pyarrow 0.11.0, pandas > 0.23.4 > - Debian9, Python 2.7.13, pyarrow 0.10.0, pandas 0.23.4 > Reporter: Andreas > Priority: Major > Fix For: 0.12.0 > > > {code:java} > import pyarrow as pa > table = pa.Table.from_arrays(arrays=[pa.array([], type=pa.int32())], > names=['col']) > table.to_pandas(categories=['col']){code} > This produces a segmentation fault for certain types (e.g, int\{32,64}) while > it works for others (e.g. string, binary). -- This message was sent by Atlassian JIRA (v7.6.3#76005)