Is it possible to conditionally combine data frame rows using pandas in python3?

Question

I have the following data frame.

            Names      Counts  Year
0           Jordan        1043  2000
1            Steve         204  2000
2            Brock           3  2000
3            Steve          33  2000
4             Mike          88  2000
...           ...         ...   ...
20001        Bryce           2  2015
20002        Steve          11  2015
20003        Penny          24  2015
20004        Steve          15  2015
20005        Ryan            5  2015

I want to output the information about the name "Steve" over all years. The output should combine the "Counts" for the name "Steve" if the name appears multiple times within the same year.

Example output might look like:

            Names       Counts  Year
0            Steve         237  2000
1            Steve         400  2001
2            Steve          35  2002
...           ...         ...   ...
15           Steve          26  2015

Asked By: display_name_1

||

Source

Answer 1

do you want something like this ?

#first
cols=['Counts','Year']
df[cols]=df[cols].astype('int32')


df=df[df['Names']=='Steve']
df=df.groupby('Year')['Counts'].agg({'sum'})

Answered By: Clegane

Answer 2

Filter records for Steve then groupby Year, and finally calculate the aggregates i.e. first for Names, and sums for Counts

(df[df['Names'].eq('Steve')]
 .groupby('Year')
 .agg({'Names': 'first', 'Counts': sum})
 .reset_index())


   Year  Names  Counts
0  2000  Steve     237
1  2015  Steve      26

Answered By: ThePyGuy

Is it possible to conditionally combine data frame rows using pandas in python3?

Question:

Answers: