如何删除 Pandas 中两个数据框中的公共行？
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How to remove common rows in two dataframes in Pandas?
提问by user3243499
I have two dataframes - df1and df2.
我有两个数据框 -df1和df2.
df1 has row1,row2,row3,row4,row5
df2 has row2,row5
I want to have a new dataframe such that df1-df2. That is, the resultant dataframe should have rows as - row1,row3,row4.
我想要一个新的数据框，这样df1-df2. 也就是说，结果数据帧的行应该是 - row1,row3,row4。
采纳答案by Nickil Maveli
You can use pandas.concatto concatenate the two dataframes rowwise, followed by drop_duplicatesto remove all the duplicated rows in them.
您可以使用pandas.concat逐行连接两个数据框，然后drop_duplicates删除其中的所有重复行。
In [1]: import pandas as pd
df_1 = pd.DataFrame({"A":["foo", "foo", "foo", "bar"], "B":[0,1,1,1], "C":["A","A","B","A"]})
df_2 = pd.DataFrame({"A":["foo", "bar", "foo", "bar"], "B":[1,0,1,0], "C":["A","B","A","B"]})
In [2]: df = pd.concat([df_1, df_2])
In [3]: df
Out[3]:
A B C
0 foo 0 A
1 foo 1 A
2 foo 1 B
3 bar 1 A
0 foo 1 A
1 bar 0 B
2 foo 1 A
3 bar 0 B
In [4]: df.drop_duplicates(keep=False)
Out[4]:
A B C
0 foo 0 A
2 foo 1 B
3 bar 1 A
回答by Olivier Ma
You can use the index.difference()function
您可以使用该index.difference()功能
import numpy as np
import pandas as pd
df1 = pd.DataFrame(np.random.randn(5, 2), index= ['row' + str(i) for i in range(1, 6)])
df1
0 1
row1 0.249451 -0.107651
row2 1.295390 -1.773707
row3 -0.893647 -0.683306
row4 -1.090551 0.016833
row5 0.864612 0.369138
df2 = pd.DataFrame(np.random.randn(2, 2), index= ['row' + str(i) for i in [2, 5]])
df2
0 1
row2 0.549396 -0.675574
row5 1.348785 0.942216
df1.loc[df1.index.difference(df2.index), ]
0 1
row1 0.249451 -0.107651
row3 -0.893647 -0.683306
row4 -1.090551 0.016833
回答by Manideep Karthik
For these kind of questions, see left join in pandas.
对于此类问题，请参阅 left join in pandas。
