I have 2 DataFrames df1 and df2 with the same column names ['a','b','c'] and indexed by dates.
The date index can have similar values.
I would like to create a DataFrame df3 with only the data from columns ['c'] renamed respectively 'df1' and 'df2' and with the correct date index. My problem is that I cannot get how to merge the index properly.
df1 = pd.DataFrame(np.random.randn(5,3), index=pd.date_range('01/02/2014',periods=5,freq='D'), columns=['a','b','c'] )
df2 = pd.DataFrame(np.random.randn(8,3), index=pd.date_range('01/01/2014',periods=8,freq='D'), columns=['a','b','c'] )
df1
a b c
2014-01-02 0.580550 0.480814 1.135899
2014-01-03 -1.961033 0.546013 1.093204
2014-01-04 2.063441 -0.627297 2.035373
2014-01-05 0.319570 0.058588 0.350060
2014-01-06 1.318068 -0.802209 -0.939962
df2
a b c
2014-01-01 0.772482 0.899337 0.808630
2014-01-02 0.518431 -1.582113 0.323425
2014-01-03 0.112109 1.056705 -1.355067
2014-01-04 0.767257 -2.311014 0.340701
2014-01-05 0.794281 -1.954858 0.200922
2014-01-06 0.156088 0.718658 -1.030077
2014-01-07 1.621059 0.106656 -0.472080
2014-01-08 -2.061138 -2.023157 0.257151
The df3 DataFrame should have the following form :
df3
df1 df2
2014-01-01 NaN 0.808630
2014-01-02 1.135899 0.323425
2014-01-03 1.093204 -1.355067
2014-01-04 2.035373 0.340701
2014-01-05 0.350060 0.200922
2014-01-06 -0.939962 -1.030077
2014-01-07 NaN -0.472080
2014-01-08 NaN 0.257151
But with NaN in the df1 column as the date index of df2 is wider. (In this example, I would get NaN for the ollowing dates : 2014-01-01, 2014-01-07 and 2014-01-08
)
Thanks for your help.
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