[
https://issues.apache.org/jira/browse/ARROW-9787?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
quentin lhoest updated ARROW-9787:
----------------------------------
Description:
Hello !
It looks like it is possible to map arrow types to pandas types using the
`types_mapper` argument in `to_pandas`. However it seems to work only for
`pa.Table.to_pandas` and not `pa.array.to_pandas`.
Example to reproduce:
{code:python}
import pyarrow as pa
import pandas as pd
def types_mapper(dtype):
print("Looking at dtype")
if dtype == pa.int64():
print("Changing dtype")
return pd.Int32Dtype()
arr = pa.array([1,2,3], pa.int64())
print(pa.Table.from_arrays([arr],
names=["col"]).to_pandas(types_mapper=types_mapper).col.dtype)
# Prints:
# Looking at dtype
# Changing dtype
# Int32
print(arr.to_pandas(types_mapper=types_mapper).dtype)
# Prints:
# int64
{code}
was:
Hello !
It looks like it is possible to map arrow types to pandas types using the
`types_mapper` argument in `to_pandas`. However it seems to work only for
`pa.Table.to_pandas` and not `pa.array.to_pandas`.
Example to reproduce:
```
import pyarrow as pa
import pandas as pd
def types_mapper(dtype):
print("Looking at dtype")
if dtype == pa.int64():
print("Changing dtype")
return pd.Int32Dtype()
arr = pa.array([1,2,3], pa.int64())
print(pa.Table.from_arrays([arr],
names=["col"]).to_pandas(types_mapper=types_mapper).col.dtype)
# Prints:
# Looking at dtype
# Changing dtype
# Int32
print(arr.to_pandas(types_mapper=types_mapper).dtype)
# Prints:
# int64
```
> pa.array.to_pandas(types_mapper=...) doesn't change the dtype
> -------------------------------------------------------------
>
> Key: ARROW-9787
> URL: https://issues.apache.org/jira/browse/ARROW-9787
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 1.0.0
> Reporter: quentin lhoest
> Priority: Major
>
> Hello !
> It looks like it is possible to map arrow types to pandas types using the
> `types_mapper` argument in `to_pandas`. However it seems to work only for
> `pa.Table.to_pandas` and not `pa.array.to_pandas`.
> Example to reproduce:
> {code:python}
> import pyarrow as pa
> import pandas as pd
> def types_mapper(dtype):
> print("Looking at dtype")
> if dtype == pa.int64():
> print("Changing dtype")
> return pd.Int32Dtype()
> arr = pa.array([1,2,3], pa.int64())
> print(pa.Table.from_arrays([arr],
> names=["col"]).to_pandas(types_mapper=types_mapper).col.dtype)
> # Prints:
> # Looking at dtype
> # Changing dtype
> # Int32
> print(arr.to_pandas(types_mapper=types_mapper).dtype)
> # Prints:
> # int64
> {code}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
