pandas -基于列条目的两个数据框的交集 [英] Pandas - intersection of two data frames based on column entries

问题描述

假设我有两个这样的DataFrame:

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

我想创建一个新的DataFrame，它由在两个矩阵中具有匹配的"S"和"T"条目的行以及dfA的prob列和dfB的knstats列组成.结果应类似于以下内容，并且顺序必须相同:

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

推荐答案

您可以将它们合并:

s1 = pd.merge(dfA, dfB, how='inner', on=['S', 'T'])

要删除NA行:

s1.dropna(inplace=True)

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