Creating a pandas DataFrame from columns of other DataFrames with similar indexes

You can use concat:

In [11]: pd.concat([df1['c'], df2['c']], axis=1, keys=['df1', 'df2'])
Out[11]: 
                 df1       df2
2014-01-01       NaN -0.978535
2014-01-02 -0.106510 -0.519239
2014-01-03 -0.846100 -0.313153
2014-01-04 -0.014253 -1.040702
2014-01-05  0.315156 -0.329967
2014-01-06 -0.510577 -0.940901
2014-01-07       NaN -0.024608
2014-01-08       NaN -1.791899

[8 rows x 2 columns]

The axis argument determines the way the DataFrames are stacked:

df1 = pd.DataFrame([1, 2, 3])
df2 = pd.DataFrame(['a', 'b', 'c'])

pd.concat([df1, df2], axis=0)
   0
0  1
1  2
2  3
0  a
1  b
2  c

pd.concat([df1, df2], axis=1)

   0  0
0  1  a
1  2  b
2  3  c