How to remove shared rows in two data frames in Pandas?

Question

I have two data frames - df1and df2.

df1 has row1,row2,row3,row4,row5
df2 has row2,row5

I want to have a new data frame such as df1-df2. That is, there should be lines like - in the resulting data frame row1,row3,row4.

Answer 1

You can use to combine two data roles, and then to delete all duplicate rows in them. pandas.concat drop_duplicates

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

Answer 2

You can use the function index.difference()

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

Answer 3

, .