How to group by number of bins a ordered dataframe?

Question

I have a dataframe like that:

year	count_yes	count_no
1900	5	7
1903	5	3
1915	14	6
1919	6	14

I want to have two bins, independently of the value itself.

How can I group those categories and sum its values?

Expected result:

year	count_yes	count_no
1900	10	10
1910	20	20

Logic: Grouped the first two rows (1900 and 1903) and the two last rows (1915 and 1919) and summed the values of each category

I want to create a stacked percentage column graphic, so 1900 would be 50/50% and 1910 would be also 50/50%.

I've already created the function to build this graphic, I just need to adjust the dataframe size into bins to create a better distribution and visualization

Answer 1

This is a way to do what you need, if you are ok using the decades as index:

df['year'] = (df.year//10)*10
df_group   = df.groupby('year').sum()

Output>>>

df_group

       count_yes    count_no
year        
1900          10          10
1910          20          20