Subtract a column from one pandas dataframe from another

Question

I'm sorry for a dumb question, but I cannot find any way to do this easily.

I have two pandas data frames in Python 2.7, which are indexed by tenor:

In [136]: rates
Out[136]:
          A      A-    BBB+     BBB    BBB-      BB
3M   0.3150  0.3530  0.4960  0.6460  0.7910  1.9070
6M   0.3070  0.3560  0.5330  0.6740  0.8740  1.9170
1Y   0.3810  0.4470  0.6380  0.8970  1.1220  1.9900
2Y   0.7040  0.8690  1.0080  1.3510  1.6150  2.3230
3Y   1.0650  1.2870  1.4350  1.7950  2.0960  2.7590
4Y   1.5980  1.7920  1.9540  2.2660  2.6600  3.5890
5Y   2.0890  2.2660  2.4390  2.7890  3.2200  4.3280
7Y   2.9760  3.2010  3.2500  3.7600  4.3790  5.1970
8Y   3.3410  3.5410  3.5920  4.1270  4.7610  5.5170
9Y   3.5870  3.7400  3.9180  4.4630  4.9830  5.7710
10Y  3.7970  3.9410  4.1980  4.6440  5.1170  5.9630
15Y  4.6750  4.7290  5.3450  5.3440  5.3760  7.0900
20Y  5.3580  5.3760  5.5020  5.5850  5.5610  8.1920
25Y  5.2545  5.4055  5.4345  5.5435  5.5375  7.9935
30Y  5.1510  5.4350  5.3670  5.5020  5.5140  7.7950

and

In [137]: treas
Out[137]:
     2013-09-20 12:01:00
1M                 0.008
3M                 0.013
6M                 0.043
1Y                 0.104
2Y                 0.332
3Y                 0.688
5Y                 1.478
7Y                 2.109
10Y                2.735
30Y                3.762

I would like to subtract the treas from each column in rates in the common indices where the data is present, and throw away the rest of the rows. How would I do that? Both rates - treas as well as rates.sub(treas) and rates.rsub(treas) produces NaN data frames?

Thank you.

Answer 1

rates.sub(treas.iloc[:,0],axis=0).dropna()

or

rates.sub(treas.squeeze(),axis=0).dropna()