I have the following dataframe and list:

df = [[[1,2,3],'a'],[[4,5],'b'],[[6,7,8],'c']]
list = [[1,2,3],[4,5]]

And I want to do a inner merge between them, so I can keep the items in common. This will be my result:

df = [[1,2,3],'a'],[[4,5],'b']]

I have been thinking in converting both to strings, but even if I convert my list to string, I haven't been able to merge both of them as the merge function requires the items to be series or dataframes (not strings). This could be a great help!!

Thanks

CodePudding user response：

If I understand you correctly, you want only keep rows from the dataframe where the values (lists) are both in the column and the list:

lst = [[1, 2, 3], [4, 5]]
print(df[df["col1"].isin(lst)])

Prints:

        col1 col2
0  [1, 2, 3]    a
1     [4, 5]    b

DataFrame used:

        col1 col2
0  [1, 2, 3]    a
1     [4, 5]    b
2  [6, 7, 8]    c

CodePudding user response：

Thanks for your answer!

This is what worked for me:

1. Convert my list to a series (my using DB):

match = pd.Series(','.join(map(str,match)))

2. Convert the list of my master DB into a string:

df_temp2['match_s'].loc[m] = ','.join(map(str,df_temp2['match'].loc[m]))

3. Applied an inner merge on both DB:

df_temp3 = df_temp2.merge(match.rename('match'), how='inner', left_on='match_s', right_on='match')

Hope it also works for somebody else :)