熊猫 - 卷起行来填补缺失的数据

Question

I have an issue that I'm hoping has a relatively simple solution. I have a dataframe with multiple records per unique contact (see "name" below). I'm trying to GroupBy the name and roll up values where they are missing.

   name   id            email
0   bob  5.0              NaN
1   bob  NaN     test@foo.com
2  bill  3.0              NaN
3  bill  NaN  something@a.com

The expected output would be:

   name   id            email
0   bob  5.0     test@foo.com  
1  bill  3.0     something@a.com 

I've tried Pivoting and Re-pivoting a few different ways to no avail. Is there any way I can do this?

Answer 1

You can try groupby.first() :

df.groupby('name')[['id', 'email']].first()

#        id           email
#name       
#bill   3.0 something@a.com
#bob    5.0    test@foo.com

Also check the source code (according to which it takes the first non-null value) here if you are interested.