Jim Crist created ARROW-2444:

             Summary: Better handle reading empty parquet files
                 Key: ARROW-2444
                 URL: https://issues.apache.org/jira/browse/ARROW-2444
             Project: Apache Arrow
          Issue Type: Improvement
            Reporter: Jim Crist

>From [https://github.com/dask/dask/pull/3387#issuecomment-380140003]


Currently pyarrow reads empty parts as float64, even if the underlying columns 
have other dtypes. This can cause problems for pandas downstream, as certain 
operations are only valid on certain dtypes, even if the columns are empty.


Copying the comment Uwe over:

bq. {quote}This is the expected behaviour as an empty string column in Pandas 
is simply an empty column of type object. Sadly object does not tell us much 
about the type of the column at all. We return numpy.float64 in this case as 
it's the most efficient type to store nulls in Pandas.{quote}

{quote}This seems unintuitive at best to me. An empty object column in pandas 
is treated differently in many operations than an empty float64 column (str 
accessor is available, excluded from numeric operations, etc..). Having an 
empty file read in as a different dtype than was written could lead to errors 
in processing code downstream. Would arrow be willing to change this 

We should probably use another method than `field.type.to_pandas_dtype()` in 
this case. The column saved in Parquet should be saved with `NA` as type which 
sadly does not provide enough information. 

We also store the original dtype in the Pandas metadata that is used for the 
actual DataFrame reconstruction later on. If we would also pick up the metadata 
when it was written, we should be able to correctly reconstruct the dtype.

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