在Python中将VLOOKUP与合并一起使用

Question

I have this pandas DataFrame with almost 540000 rows:

df1.head()

    username  hour    totalCount
0   lowi      00:00   12
1   klark     00:00   0
2   sturi     00:00   2
3   nukr      00:00   10
4   irore     00:00   2

I also have this other pandas DataFrame with almost 52000 rows and with some duplicated rows:

df2.head()

   username   community
0    klark       0
1    irore       2
2    sturi       2
3    sturi       2
4    sturi       2

I want to merge the column of 'community' of df2 into the df1, but in the corresponding row according to the username. I have used this code:

df_merge = df_hu.merge(df_comm, on='username')
df_merge

But I get the following DataFrame with almost 1205880 rows and duplicated ones:

    username    hour    totalCount  community
0   lowi        00:00   12          2
1   lowi        00:00   12          2
2   lowi        00:00   12          2
3   lowi        01:00   9           2
4   lowi        01:00   9           2

The expected output would be this:

df_merge.head()

    username  hour    totalCount community
0   lowi      00:00   12         2
1   klark     00:00   0          0
2   sturi     00:00   2          2
3   nukr      00:00   10         1 (not showed in the example)
4   irore     00:00   2          1 (not showed in the example)

Answer 1

Using pandas.Series.map :

df2 = df2.drop_duplicates().set_index('username')
df1['community'] = df1['username'].map(df2['community'])
print(df1)

Output:

  username   hour  totalCount  community
0     lowi  00:00          12        NaN
1    klark  00:00           0        0.0
2    sturi  00:00           2        2.0
3     nukr  00:00          10        NaN
4    irore  00:00           2        2.0

Note that lowi and nukr weren't in the example df2 so NaN .