I have a dataframe:
id value_type
1 b
1 a
1 a
2 a
3 a
3 b
I want to calculate percent of each value_type with each id group.so desired result is:
id value_type perc
1 b 0.33
1 a 0.66
2 a 1
3 a 0.5
3 b 0.5
How could I do that? I tried groupby().size() but it counts, but i need percentages
Check below code:
import pandas as pd
df = pd.DataFrame({'col1':[1,1,1,2,3,3],'col2':['b','a','a','a','a','b']})
df['perc'] = df.groupby(['col1','col2'])['col2'].transform('count')/df.groupby('col1')['col2'].transform('count')
df.round(2).drop_duplicates()
Output:
you also can do something like this:
res = df.groupby('id').value_counts(normalize=True).reset_index(name='perc')
print(res)
'''
id value_type perc
0 1 a 0.666667
1 1 b 0.333333
2 2 a 1.000000
3 3 a 0.500000
4 3 b 0.500000