Suppose I have two DataFrames like so:
>>dfA
S T prob
0 ! ! ! ! ! ! 8.1623999e-05
1 ! ! ! ! ! ! " 0.00354090007
2 ! ! ! ! ! ! . 0.00210241997
3 ! ! ! ! ! ! ? 6.55684998e-05
4 ! ! ! ! ! ! 0.203119993
5 ! ! ! ! ! ! ” 6.62070015e-05
6 ! ! ! ! ! 0.00481862016
7 ! ! ! ! 0.0274260994
8 ! ! ! " ! ! ! 7.99940026e-05
9 ! ! ! " ! 1.51188997e-05
10 ! ! ! " 8.50678989e-05
>>dfB
S T knstats
0 ! ! ! ! ! ! ! knstats=2,391,104,64,25
1 ! ! ! ! ! ! " knstats=4,391,6,64,2
2 ! ! ! ! ! ! . knstats=4,391,5,64,2
3 ! ! ! ! ! ! ? knstats=1,391,4,64,4
4 ! ! ! ! ! ! knstats=220,391,303,64,55
5 ! ! ! ! ! knstats=16,391,957,64,115
6 ! ! ! ! knstats=28,391,5659,64,932
7 ! ! ! " ! ! ! knstats=2,391,2,64,1
8 ! ! ! " ! knstats=1,391,37,64,13
9 ! ! ! " knstats=2,391,1.11721e+06,64,180642
10 ! ! . " knstats=2,391,120527,64,20368
I want to create a new DataFrame which is composed of the rows which have matching "S" and "T" entries in both matrices, along with the prob column from dfA and the knstats column from dfB. The result should look something like the following, and it is important that the order is the same:
S T prob knstats
0 ! ! ! ! ! ! ! 8.1623999e-05 knstats=2,391,104,64,25
1 ! ! ! ! ! ! " 0.00354090007 knstats=4,391,6,64,2
2 ! ! ! ! ! ! . 0.00210241997 knstats=4,391,5,64,2
3 ! ! ! ! ! ! ? 6.55684998e-05 knstats=1,391,4,64,4
4 ! ! ! ! ! ! 0.203119993 knstats=220,391,303,64,55
5 ! ! ! ! ! 0.00481862016 knstats=16,391,957,64,115
6 ! ! ! ! 0.0274260994 knstats=28,391,5659,64,932
7 ! ! ! " ! ! ! 7.99940026e-05 knstats=2,391,2,64,1
8 ! ! ! " ! 1.51188997e-05 knstats=1,391,37,64,13
9 ! ! ! " 8.50678989e-05 knstats=2,391,1.11721e+06,64,180642
You can merge them so:
s1 = pd.merge(dfA, dfB, how='inner', on=['S', 'T'])
To drop NA rows:
s1.dropna(inplace=True)