I have been trying to make a comparison of two dataframes, creating new dataframes for the ones which have the same entries in two columns. I thought I had cracked it but the code I have now just looks at the two columns of interest and if the string is found anywhere in that column it considers it a match. I need the two strings to be common on the same row across the columns. A sample of the code follows.
#produce table with common items
vto_in_jeff = df_vto[(df_vto['source'].isin(df_jeff['source']) & df_vto['target'].isin(df_jeff['target']))].dropna().reset_index(drop=True)
#vto_in_jeff.index = vto_in_jeff.index + 1
vto_in_jeff['compare'] = 'Common_terms'
print(vto_in_jeff)
vto_in_jeff.to_csv(output_path+'vto_in_'+f+'.csv', index=False)
So this code comes out with a table which has a list of the rows which has both source and target strings, but not the source and target strings necessarily having to appear in the same row. Can anyone help me look specifically row by row?