I have two dataFrame, both of them have name column, I want to make new dataframe of dataframeA have and dataframeB don't have
dataframeA
id name
1 aaa
2 bbbb
3 cccc
4 gggg
dataframeB
id name
1 ddd
2 aaa
3 gggg
new dataframe
id name
1 bbbb
2 cccc
If I understand correctly, ou can merge the two dataframes
import pandas as pd
merged_df = pd.merge(dataframe_a, dataframe_b, on='name')
You can use reduce from functools, or you can use isin, to create a new_df that only contains values in dfA that are also present in dfB.
Approach 1 using reduce:
from functools import reduce #import package
li = [dfA, dfB] #create list of dataframes
new_df = reduce(lambda left,right: pd.merge(left,right,on='name'), li) #reduce list
Approach 2 using isin:
new_df = dfA[dfA['name'].isin(dfB['name])]
One way you could do this is to utilise python's set functionality.
This will convert the specified columns to sets and then create a new dataframe using the output.
dataframe = pd.DataFrame(data = {
'name': list(set(dataframeA['name'].tolist()) - set(dataframeB['name'].tolist()))
})
