Verified, issue: https://issues.apache.org/jira/browse/ARROW-4258
On Mon, Jan 14, 2019 at 12:31 AM Wes McKinney <wesmck...@gmail.com> wrote: > This seems like a bug to me; I would not expect this to fail. It's too > bad it didn't get fixed in time for 0.12 > > On Thu, Jan 10, 2019 at 4:20 PM Bryan Cutler <cutl...@gmail.com> wrote: > > > > Hi All, > > > > I have a question about using pyarrow.Array.from_pandas with the safe > flag > > set to True. When the Pandas data contains integers and NULL values, it > > will get changed to a floating point dtype and then if the type is casted > > back to an integer in Arrow, it will raise an error "ArrowInvalid: > Floating > > point value truncated". Is this the expected behavior? I'm guessing it > > doesn't look at the actual values, just what type is being converted. Is > > there a way around this specific error besides setting safe to False? > Here > > is a concise example: > > > > >>> pa.Array.from_pandas(pd.Series([1, None]), type=pa.int32(), > safe=True) > > Traceback (most recent call last): > > File "<stdin>", line 1, in <module> > > File "pyarrow/array.pxi", line 474, in pyarrow.lib.Array.from_pandas > > File "pyarrow/array.pxi", line 169, in pyarrow.lib.array > > File "pyarrow/array.pxi", line 69, in pyarrow.lib._ndarray_to_array > > File "pyarrow/error.pxi", line 81, in pyarrow.lib.check_status > > pyarrow.lib.ArrowInvalid: Floating point value truncated > > > > I came across this issue in https://github.com/apache/spark/pull/22807, > > specifically withi this discussion > > https://github.com/apache/spark/pull/22807#discussion_r246859417. > > > > Thanks! > > Bryan >
