Potential Solution for AssertionError: invalid dtype determination in get_concat_dtype when concatenating operation on list of Dataframes?

[kbtyo]

I have a list of Pandas Dataframes that I am attempting to combine using the concatenation function.

dataframe_lists = [df1, df2, df3]

result = pd.concat(dataframe_lists, keys = ['one', 'two','three'], ignore_index=True)

The full traceback that I receive when I execute this function is:

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-198-a30c57d465d0> in <module>()
----> 1 result = pd.concat(dataframe_lists, keys = ['one', 'two','three'], ignore_index=True)
      2 check(dataframe_lists)

C:\WinPython-64bit-3.4.3.5\python-3.4.3.amd64\lib\site-packages\pandas\tools\merge.py in concat(objs, axis, join, join_axes, ignore_index, keys, levels, names, verify_integrity, copy)
    753                        verify_integrity=verify_integrity,
    754                        copy=copy)
--> 755     return op.get_result()
    756 
    757 

C:\WinPython-64bit-3.4.3.5\python-3.4.3.amd64\lib\site-packages\pandas\tools\merge.py in get_result(self)
    924 
    925             new_data = concatenate_block_managers(
--> 926                 mgrs_indexers, self.new_axes, concat_axis=self.axis, copy=self.copy)
    927             if not self.copy:
    928                 new_data._consolidate_inplace()

C:\WinPython-64bit-3.4.3.5\python-3.4.3.amd64\lib\site-packages\pandas\core\internals.py in concatenate_block_managers(mgrs_indexers, axes, concat_axis, copy)
   4061                                                 copy=copy),
   4062                          placement=placement)
-> 4063               for placement, join_units in concat_plan]
   4064 
   4065     return BlockManager(blocks, axes)

C:\WinPython-64bit-3.4.3.5\python-3.4.3.amd64\lib\site-packages\pandas\core\internals.py in <listcomp>(.0)
   4061                                                 copy=copy),
   4062                          placement=placement)
-> 4063               for placement, join_units in concat_plan]
   4064 
   4065     return BlockManager(blocks, axes)

C:\WinPython-64bit-3.4.3.5\python-3.4.3.amd64\lib\site-packages\pandas\core\internals.py in concatenate_join_units(join_units, concat_axis, copy)
   4150         raise AssertionError("Concatenating join units along axis0")
   4151 
-> 4152     empty_dtype, upcasted_na = get_empty_dtype_and_na(join_units)
   4153 
   4154     to_concat = [ju.get_reindexed_values(empty_dtype=empty_dtype,

C:\WinPython-64bit-3.4.3.5\python-3.4.3.amd64\lib\site-packages\pandas\core\internals.py in get_empty_dtype_and_na(join_units)
   4139         return np.dtype('m8[ns]'), tslib.iNaT
   4140     else:  # pragma
-> 4141         raise AssertionError("invalid dtype determination in get_concat_dtype")
   4142 
   4143 

AssertionError: invalid dtype determination in get_concat_dtype


I believe that the error lies in the fact that one of the data frames is empty. As a temporary workaround this rather perplexing error. I used the simple function check to verify and return just the headers of the empty dataframe: 

def check(list_of_df):

    headers = []
    for df in dataframe_lists:
        if df.empty is not True:
            continue
        else:  
            headers.append(df.columns)

    return headers

I am wondering if it is possible to use this function to, if in the case of an empty dataframe, return just that empty dataframe's headers and append it to the concatenated dataframe. The output would be a single row for the headers (and, in the case of a repeating column name, just a single instance of the header (as in the case of the concatenation function). I have two sample data sources, one and two non-empty data sets. 

df1: https://gist.github.com/ahlusar1989/42708e6a3ca0aed9b79b
df2 :https://gist.github.com/ahlusar1989/26eb4ce1578e0844eb82

Here is an empty dataframe.


df3 (empty dataframe): https://gist.github.com/ahlusar1989/0721bd8b71416b54eccd

I would like to have the resulting concatenate have the column headers (with their values) that reflects df1 and df2...

'AT','AccountNum', 'AcctType', 'Amount', 'City', 'Comment', 'Country','DuplicateAddressFlag', 'FromAccount', 'FromAccountNum', 'FromAccountT','PN', 'PriorCity', 'PriorCountry', 'PriorState', 'PriorStreetAddress','PriorStreetAddress2', 'PriorZip', 'RTID', 'State', 'Street1','Street2', 'Timestamp', 'ToAccount', 'ToAccountNum', 'ToAccountT', 'TransferAmount', 'TransferMade', 'TransferTimestamp', 'Ttype', 'WA','WC', 'Zip'

as follows: 

'A', 'AT','AccountNum', 'AcctType', 'Amount', 'B', 'C', 'City', 'Comment', 'Country', 'D', 'DuplicateAddressFlag', 'E', 'F' 'FromAccount', 'FromAccountNum', 'FromAccountT', 'G', 'PN', 'PriorCity', 'PriorCountry', 'PriorState', 'PriorStreetAddress','PriorStreetAddress2', 'PriorZip', 'RTID', 'State', 'Street1','Street2', 'Timestamp', 'ToAccount', 'ToAccountNum', 'ToAccountT', 'TransferAmount', 'TransferMade', 'TransferTimestamp', 'Ttype', 'WA','WC', 'Zip'

I welcome any feedback on how to best do this. Thank you.