Group rows pandas

Question

Background: I have the following dataframe:

import pandas as pd
d = {'day': ["t", "m", "m", "w", "t", "m","w"], 
     'month': ["01", "01", "01", "01", "02","02","02"], 
     'count': [1, 1, 1, 1,1,1,1]}
df = pd.DataFrame(data=d)

I group by day and month:

df.groupby(by=['day','month']).count()

Output:

day  month count    
m    01     2
     02     1
t    01     1
     02     1
w    01     1
     02     1

From here, I would like to organize the data to obtain the following output:

Desired Output:

day  month count    
m    01     2
t    01     1
w    01     1
m    02     1
t    02     1
w    02     1           

I tried df.sort_values('month') and df.sort_values('day') but it doesn't quite give me what I am looking for

Question: What line(s) of code do I need to add to get my desired output?

Answer 1

Here you go. It only happens to get the day ordering correct, but you might want to convert them to actually 0-6 for days of the week if you have more days later.

df.groupby(by=['day','month'], as_index=False).count().sort_values(by=['month', 'day'])

    day month   count
0   m   01  2
2   t   01  1
4   w   01  1
1   m   02  1
3   t   02  1
5   w   02  1