Bryan Cutler created ARROW-1680:
-----------------------------------
Summary: [Python] Timestamp unit change not done in from_pandas()
conversion
Key: ARROW-1680
URL: https://issues.apache.org/jira/browse/ARROW-1680
Project: Apache Arrow
Issue Type: Bug
Components: Python
Reporter: Bryan Cutler
When calling {{Array.from_pandas}} with a pandas.Series of timestamps that have
'ns' unit and specifying a type to coerce to with 'us' causes problems. When
the series has timestamps with a timezone, the unit is ignored. When the
series does not have a timezone, it is applied but causes an OverflowError when
printing.
{noformat}
>>> import pandas as pd
>>> import pyarrow as pa
>>> from datetime import datetime
>>> s = pd.Series([datetime.now()])
>>> s_nyc = s.dt.tz_localize('tzlocal()').dt.tz_convert('America/New_York')
>>> arr = pa.Array.from_pandas(s_nyc, type=pa.timestamp('us',
>>> tz='America/New_York'))
>>> arr.type
TimestampType(timestamp[ns, tz=America/New_York])
>>> arr = pa.Array.from_pandas(s, type=pa.timestamp('us'))
>>> arr.type
TimestampType(timestamp[us])
>>> print(arr)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pyarrow/array.pxi", line 295, in pyarrow.lib.Array.__repr__
(/home/bryan/git/arrow/python/build/temp.linux-x86_64-2.7/lib.cxx:26221)
values = array_format(self, window=10)
File "pyarrow/formatting.py", line 28, in array_format
values.append(value_format(x, 0))
File "pyarrow/formatting.py", line 49, in value_format
return repr(x)
File "pyarrow/scalar.pxi", line 63, in pyarrow.lib.ArrayValue.__repr__
(/home/bryan/git/arrow/python/build/temp.linux-x86_64-2.7/lib.cxx:19535)
return repr(self.as_py())
File "pyarrow/scalar.pxi", line 240, in pyarrow.lib.TimestampValue.as_py
(/home/bryan/git/arrow/python/build/temp.linux-x86_64-2.7/lib.cxx:21600)
return converter(value, tzinfo=tzinfo)
File "pyarrow/scalar.pxi", line 204, in pyarrow.lib.lambda5
(/home/bryan/git/arrow/python/build/temp.linux-x86_64-2.7/lib.cxx:7295)
TimeUnit_MICRO: lambda x, tzinfo: pd.Timestamp(
File "pandas/_libs/tslib.pyx", line 402, in
pandas._libs.tslib.Timestamp.__new__ (pandas/_libs/tslib.c:10051)
File "pandas/_libs/tslib.pyx", line 1467, in
pandas._libs.tslib.convert_to_tsobject (pandas/_libs/tslib.c:27665)
OverflowError: Python int too large to convert to C long
{noformat}
A workaround is to manually change values with astype
{noformat}
>>> arr = pa.Array.from_pandas(s.values.astype('datetime64[us]'))
>>> arr.type
TimestampType(timestamp[us])
>>> print(arr)
<pyarrow.lib.TimestampArray object at 0x7f6a67e0a3c0>
[
Timestamp('2017-10-17 11:04:44.308233')
]
>>>
{noformat}
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