I have two Dataframes that I am trying to merge by match to values in a column. The column to match are header1 in Df1 and header2 in Df2 (the value is list). I am looking for an adapted approach.
Df1: Df2: |--------------|---------------| |--------------|------------------------| | id_1 | header1 | | id_2 | header2 | |--------------|---------------| |--------------|------------------------| | 112 | item1 | | 32 |['item1','item2',...] | |--------------|---------------| |--------------|------------------------| | 56 | mass | |--------------|---------------|
Wanted results:
Df_merged: |--------------|---------------|--------------|------------------------| | id_1 | header1 | id_2 | header2 | |--------------|---------------|--------------|------------------------| | 112 | item1 | 32 |['item1','item2',...] | |--------------|---------------|--------------|------------------------|
Does anyone know how to merge these two dataframe ?. I have absolutely no idea how to handle this. Thanks a lot in advance.
Use DataFrame.explode with reassign header2 to header1 for avoid lost original column header2 and then use DataFrame.merge:
df = df1.merge(df2.assign(header1 = df2['header2']).explode('header1'), on='header1')