df1:
| A | B |
|---|---|
| 1 | 10 |
| 2 | 20 |
| 3 | 30 |
| 4 | 40 |
| 5 | 50 |
df2:
| A | D |
|---|---|
| 2 | D1 |
| 4 | D2 |
| 100 | D3 |
Here is the code to create:
import pandas as pd
df1 = pd.DataFrame({'A':[1,2,3,4,5],
'B':[10,20,30,40,50]})
df2 = pd.DataFrame({'A':[2,4,100],
'D':['D1','D2','D3']})
What I want to do is, check if df2['A'] has the same data with df1['A']. If it does, then get all the row that data is in. for example. df1['A'] = 2 is also in df2['A']. df2['A'] = 2 has D = D1 and A = 2.(Same applies for A=4)
What I tried:
traindatalist = [df2[df2['A']==dtA].drop('A',axis=1) for dtA in df1['A']]
