Merge two pandas dataframe and create a new binary column based on condition

Question

I have two dataframes - the list of influential medical journals and the list of articles from a broader list journals.

journal_id  journal_title   
1            Journal 1  
2            Journal 2  
3            Journal 3  
    
article_id  journal_title   article_title
1             Journal 1       Title 1
2             Journal 2       Title 2
3             Journal 18      Title 3
4             Journal 55      Title 4

I want to merge two dataframes and create a new column in the second dataframe with article titles, which will mark as a binary output where the article is from influential journal or not (binary output).

Expected output

article_id  journal_title   article_title influential
1             Journal 1         Title 1      1
2             Journal 2         Title 2      1
3             Journal 18        Title 3      0
4             Journal 55        Title 4      0

Appreciate ideas!

You could use the .isin() method. This seems to be the same problem: link — Yehla
– Yehla, Commented Dec 1, 2021 at 12:50

Eha · Accepted Answer · 2021-12-01 12:48:57Z

3

You can first set the value to False, and then set for true for those who fulfill the condition.

df2['influential']=0
df2['influential'][df2['Journal'].isin(df1['Journal'].values)]=1

answered Dec 1, 2021 at 12:48

Eha

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Comments

Ashok Thakur · Accepted Answer · 2021-12-01 16:10:10Z

-1

You can also try this

df2 = df2.merge(df1['journal_title'], how='left', on='journal_title', indicator=True) # merges & creates indicators for matches
df2['influential'] = df2['_merge'].apply(lambda x: 1 if x == 'both' else 0) # if matches (both) then 1 else 0 for (left_only & right_only)
df2.drop(['_merge'], axis=1, inplace=True) #drops the column

edited Dec 1, 2021 at 16:10

answered Dec 1, 2021 at 13:50

Ashok Thakur

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