[ 
https://issues.apache.org/jira/browse/ARROW-11445?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Carlo Mazzaferro updated ARROW-11445:
-------------------------------------
    Description: 
While I have not dug deep enough in the Arrow codebase, it seems to me that 
this is caused by the new numpy release: 
[https://github.com/numpy/numpy/releases] 

The issue below in fact is not observed when using numpy 0.19.*

 

 

 >>> pandas.__version__, pa.__version__, numpy.__version__
('1.2.1', '2.0.0', '1.20.0')
>>> df = pandas.DataFrame(\{'a': numpy.random.randn(10), 'b': 
>>> numpy.random.randn(7).tolist() + [None, pandas.NA, numpy.nan], 'c': 
>>> list(range(9)) + [numpy.nan]})
>>> pa.Table.from_pandas(df)
Traceback (most recent call last):
 File "<input>", line 1, in <module>
 pa.Table.from_pandas(df)
 File "pyarrow/table.pxi", line 1394, in pyarrow.lib.Table.from_pandas
 File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 588, in dataframe_to_arrays
 for c, f in zip(columns_to_convert, convert_fields)]
 File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 588, in <listcomp>
 for c, f in zip(columns_to_convert, convert_fields)]
 File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 574, in convert_column
 raise e
 File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 568, in convert_column
 result = pa.array(col, type=type_, from_pandas=True, safe=safe)
 File "pyarrow/array.pxi", line 292, in pyarrow.lib.array
 File "pyarrow/array.pxi", line 79, in pyarrow.lib._ndarray_to_array
 File "pyarrow/array.pxi", line 67, in pyarrow.lib._ndarray_to_type
 File "pyarrow/error.pxi", line 107, in pyarrow.lib.check_status
pyarrow.lib.ArrowTypeError: ('Did not pass numpy.dtype object', 'Conversion 
failed for column a with type float64')

  was:
While I have not dug deep enough in the Arrow codebase, it seems to me that 
this is caused by the new numpy release: 
[https://github.com/numpy/numpy/releases] 

The issue below in fact is not observed when using numpy 0.19.*

 

 

 
{quote}{{>>> pandas.__version__, pa.__version__, numpy.__version__}}
{{('1.2.1', '2.0.0', '1.20.0')}}
{{>>> df = pandas.DataFrame(\{'a': numpy.random.randn(10), 'b': 
numpy.random.randn(7).tolist() + [None, pandas.NA, numpy.nan], 'c': 
list(range(9)) + [numpy.nan]})}}
{{>>> pa.Table.from_pandas(df)}}
{{Traceback (most recent call last):}}
{{ File "<input>", line 1, in <module>}}
{{ pa.Table.from_pandas(df)}}
{{ File "pyarrow/table.pxi", line 1394, in pyarrow.lib.Table.from_pandas}}
{{ File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 588, in dataframe_to_arrays}}
{{ for c, f in zip(columns_to_convert, convert_fields)]}}
{{ File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 588, in <listcomp>}}
{{ for c, f in zip(columns_to_convert, convert_fields)]}}
{{ File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 574, in convert_column}}
{{ raise e}}
{{ File 
"/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
 line 568, in convert_column}}
{{ result = pa.array(col, type=type_, from_pandas=True, safe=safe)}}
{{ File "pyarrow/array.pxi", line 292, in pyarrow.lib.array}}
{{ File "pyarrow/array.pxi", line 79, in pyarrow.lib._ndarray_to_array}}
{{ File "pyarrow/array.pxi", line 67, in pyarrow.lib._ndarray_to_type}}
{{ File "pyarrow/error.pxi", line 107, in pyarrow.lib.check_status}}
{{pyarrow.lib.ArrowTypeError: ('Did not pass numpy.dtype object', 'Conversion 
failed for column a with type float64')}}
{quote}


> Type conversion failure on numpy 0.1.20
> ---------------------------------------
>
>                 Key: ARROW-11445
>                 URL: https://issues.apache.org/jira/browse/ARROW-11445
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 2.0.0
>         Environment: Python 3.7.4
> Mac OS
>            Reporter: Carlo Mazzaferro
>            Priority: Major
>
> While I have not dug deep enough in the Arrow codebase, it seems to me that 
> this is caused by the new numpy release: 
> [https://github.com/numpy/numpy/releases] 
> The issue below in fact is not observed when using numpy 0.19.*
>  
>  
>  >>> pandas.__version__, pa.__version__, numpy.__version__
> ('1.2.1', '2.0.0', '1.20.0')
> >>> df = pandas.DataFrame(\{'a': numpy.random.randn(10), 'b': 
> >>> numpy.random.randn(7).tolist() + [None, pandas.NA, numpy.nan], 'c': 
> >>> list(range(9)) + [numpy.nan]})
> >>> pa.Table.from_pandas(df)
> Traceback (most recent call last):
>  File "<input>", line 1, in <module>
>  pa.Table.from_pandas(df)
>  File "pyarrow/table.pxi", line 1394, in pyarrow.lib.Table.from_pandas
>  File 
> "/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
>  line 588, in dataframe_to_arrays
>  for c, f in zip(columns_to_convert, convert_fields)]
>  File 
> "/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
>  line 588, in <listcomp>
>  for c, f in zip(columns_to_convert, convert_fields)]
>  File 
> "/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
>  line 574, in convert_column
>  raise e
>  File 
> "/Users/carlomazzafero/.virtualenvs/arr/lib/python3.7/site-packages/pyarrow/pandas_compat.py",
>  line 568, in convert_column
>  result = pa.array(col, type=type_, from_pandas=True, safe=safe)
>  File "pyarrow/array.pxi", line 292, in pyarrow.lib.array
>  File "pyarrow/array.pxi", line 79, in pyarrow.lib._ndarray_to_array
>  File "pyarrow/array.pxi", line 67, in pyarrow.lib._ndarray_to_type
>  File "pyarrow/error.pxi", line 107, in pyarrow.lib.check_status
> pyarrow.lib.ArrowTypeError: ('Did not pass numpy.dtype object', 'Conversion 
> failed for column a with type float64')



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

Reply via email to