How To Combine Data Frames With Different (but Sometimes Overlapping) Indexes Over A Period Of Time In Pandas?

This is a continuation of my other StackOverflow post. Suppose I have a few data frames that are coming in with any random order (below, I'll mock those data frames). # assume tha

Solution 1:

concat + groupby on axis=1

l=[df1,df2,df3,df4]
m=pd.concat(l,axis=1,sort=False)
m.groupby(m.columns,axis=1).first().fillna('') #ideally don't use the fillna

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    2016-01 2016-02 2016-03 2016-04 2017-01 2017-02 2017-03 2017-04
N1       A1      B1      C1      D1      A1      B1      C1      D1
N2       A2      B2      C2      D2      A2      B2      C2      D2
N3       A3      B3      C3      D3      A3      B3      C3      D3
N4       A4      B4      C4      D4                                
N5                                       A5      B5      C5      D5
N6       A6      B6      C6      D6      A6      B6      C6      D6
N7       A7      B7      C7      D7      A7      B7      C7      D7
N8       A8      B8      C8      D8                                
N9       A9      B9      C9      D9      A9      B9      C9      D9
N10                                     A10     B10     C10     D10