$ curl cheat.sh/

#  use the `add` method with `fill_value=0` parameter.

 df1 = pd.DataFrame({'val':{'a': 1, 'b':2, 'c':3}})
 df2 = pd.DataFrame({'val':{'a': 1, 'b':2, 'd':3}})

 df1.add(df2, fill_value=0)

    val
 a  2.0
 b  4.0
 c  3.0
 d  3.0

#  ---
#  
#  ## MultiIndex example

 idx1 = pd.MultiIndex.from_tuples([('a', 'A'), ('a', 'B'), ('b', 'A'), ('b', 'D')])
 idx2 = pd.MultiIndex.from_tuples([('a', 'A'), ('a', 'C'), ('b', 'A'), ('b', 'C')])

 np.random.seed([3,1415])
 df1 = pd.DataFrame(np.random.randn(4, 1), idx1, ['val'])
 df2 = pd.DataFrame(np.random.randn(4, 1), idx2, ['val'])

 df1

           val
 a A -2.129724
   B -1.268466
 b A -1.970500
   D -2.259055

 df2

           val
 a A -0.349286
   C -0.026955
 b A  0.316236
   C  0.348782

 df1.add(df2, fill_value=0)

           val
 a A -2.479011
   B -1.268466
   C -0.026955
 b A -1.654264
   C  0.348782
   D -2.259055

#  ____
#  
#  ## More than 2 dataframes

 from functools import reduce

 df1 = pd.DataFrame({'val':{'a': 1, 'b':2, 'c':3}})
 df2 = pd.DataFrame({'val':{'a': 1, 'b':2, 'd':3}})
 df3 = pd.DataFrame({'val':{'e': 1, 'c':2, 'd':3}})
 df4 = pd.DataFrame({'val':{'f': 1, 'a':2, 'd':3}})
 df5 = pd.DataFrame({'val':{'g': 1, 'f':2, 'd':3}})

 reduce(lambda a, b: a.add(b, fill_value=0), [df1, df2, df3, df4, df5])

     val
 a   4.0
 b   4.0
 c   5.0
 d  12.0
 e   1.0
 f   3.0
 g   1.0

#  [piRSquared] [so/q/38472276] [cc by-sa 3.0]

$

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