Merging with empty DataFrame

Question

I'm trying to merge a dataframe (df1) with another dataframe (df2) for which df2 can potentially be empty. The merge condition is df1.index=df2.z (df1 is never empty), but I'm getting the following error.

Is there any way to get this working?

In [31]:
import pandas as pd
In [32]:
df1 = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [1, 2, 3]})
df2 = pd.DataFrame({'x':[], 'y':[], 'z':[]})
dfm = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-34-4e9943198dae> in <module>()
----> 1 dfmb = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')

/usr/local/lib/python2.7/dist-packages/pandas/tools/merge.pyc in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy)
     37                          right_index=right_index, sort=sort, suffixes=suffixes,
     38                          copy=copy)
---> 39     return op.get_result()
     40 if __debug__:
     41     merge.__doc__ = _merge_doc % '\nleft : DataFrame'

/usr/local/lib/python2.7/dist-packages/pandas/tools/merge.pyc in get_result(self)
    185 
    186     def get_result(self):
--> 187         join_index, left_indexer, right_indexer = self._get_join_info()
    188 
    189         ldata, rdata = self.left._data, self.right._data

/usr/local/lib/python2.7/dist-packages/pandas/tools/merge.pyc in _get_join_info(self)
    277                 join_index = self.left.index.take(left_indexer)
    278             elif self.left_index:
--> 279                 join_index = self.right.index.take(right_indexer)
    280             else:
    281                 join_index = Index(np.arange(len(left_indexer)))

/usr/local/lib/python2.7/dist-packages/pandas/core/index.pyc in take(self, indexer, axis)
    981 
    982         indexer = com._ensure_platform_int(indexer)
--> 983         taken = np.array(self).take(indexer)
    984 
    985         # by definition cannot propogate freq

IndexError: cannot do a non-empty take from an empty axes.

Answer 1

Another alternative, similar to Joran's:

try:
    dfm = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
except IndexError:
    dfm = df1.reindex_axis(df1.columns.union(df2.columns), axis=1)

I'm not sure which is clearer but both the following work:

In [11]: df1.reindex_axis(df1.columns.union(df2.columns), axis=1)
Out[11]:
   a  b  c   x   y   z
0  1  4  1 NaN NaN NaN
1  2  5  2 NaN NaN NaN
2  3  6  3 NaN NaN NaN

In [12]: df1.loc[:, df1.columns.union(df2.columns)]
Out[12]:
   a  b  c   x   y   z
0  1  4  1 NaN NaN NaN
1  2  5  2 NaN NaN NaN
2  3  6  3 NaN NaN NaN

(I prefer the former.)

Answer 2

try:
    dfm = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
except IndexError:
    dfm = df1 if not df1.empty else df2

might be sufficient for your needs