How to calculate a percentage in a dataframe grouping by two columns

Question

I'm grouping by a dataframe on two columns "zone_id and eventName. I need to compute the percentage for the eventName grouped by zone_id.

In other words I need to compute (clicked/printed)*100 by zone_id.

import pandas as pd

#read the csv file
df = pd.read_csv('data.csv', sep=';')

result=df.groupby(['zone_id','eventName']).event.count()

print(result)

#I use count() method to extract the number of clicked and printed by zone_id. Then on this basis I think to be able to find a way to compute a     percentage by zone_id.

output : 
zone_id  eventName
28       printed         88
9283     clicked         197
         printed         7732
9284     clicked         2
         printed         452
9287     clicked         129
         printed         3802
9614     clicked         4
         printed         342
17437    clicked         55
         printed         4026

#By using mean() function, the mean calculation is well done grouped by zone_id
result=df.groupby(['zone_id','eventName']).event.count().groupby('zone_id').mean()

print(result)

output :
zone_id
28         88.0
9283     3964.5
9284      227.0
9287     1965.5
9614      173.0
17437    2040.5

#Expected result : I need to compute the percentage of eventName (clicked/printed)*100 by zone_id
 Expected output:
zone_id
28        0%    -> (0/88)*100
9283      2.54% -> (197/7732)*100
9284      0.44% -> (2/452)*100
9287      3.39% -> (129/3802)*100
9614      1.16% -> (4/342)*100
17437     1.36% -> (55/4026)*100

Answer 1

Without sample data it's hard to see, but try something like this?

events = df.groupby(['zone_id','eventName']).size()
events.loc[pd.IndexSlice[:, 'printed']] / events.loc[pd.IndexSlice[:, 'clicked']]

Or using unstack to get the clicked and printed as columns:

events = df.groupby(['zone_id','eventName']).size().unstack(level=1)
events['printed'] / events['clicked']