Python Pandas - 基于列条目的两个数据框的交集
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/26921943/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas - intersection of two data frames based on column entries
提问by Bib
Suppose I have two DataFrames like so:
假设我有两个像这样的 DataFrame：
>>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:
我想创建一个新的 DataFrame，它由在两个矩阵中具有匹配“S”和“T”条目的行以及来自 dfA 的 prob 列和来自 dfB 的 knstats 列组成。结果应该类似于以下内容，并且顺序相同很重要：
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
采纳答案by user308827
You can merge them so:
您可以合并它们，以便：
s1 = pd.merge(dfA, dfB, how='inner', on=['S', 'T'])
To drop NA rows:
要删除 NA 行：
s1.dropna(inplace=True)
