Same calculation for all combinations in DataFrame

Question

I got dataframe like below,

import pandas as pd
df = pd.DataFrame({'CITY': ['A','B','C','A','C','B'], 
                   'MAKE_NAME': ['SO','OK','CO','LU','CO','OK'],
                   'USER' : ['JK','JK','MK','JK','JK','JK'],
                   'RESULT_CODE' : ['Y','Y','N','N','Y','Y'],
                   'VALID' : [1,1,1,1,1,0],
                   'COUNT' : [1,1,1,1,1,1] })

I want to calculate the valid/count of all combinations in double and triple and quadruple. Also i want to get result as dataframe.

For example result for double like below,

Also result for triple like below,

Thanks for all,

No pictures of data please. See [this guide](https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples). — Quang Hoang, Dec 14 '20 at 16:40

score 0 · Accepted Answer · answered Dec 17 '20 at 11:41

You can find the solution below.

import pandas as pd
df = pd.DataFrame({'CITY': ['A','B','C','A','C','B'], 
                   'MAKE_NAME': ['SO','OK','CO','LU','CO','OK'],
                   'USER' : ['JK','JK','MK','JK','JK','JK'],
                   'RESULT_CODE' : ['Y','Y','N','N','Y','Y'],
                   'VALID' : [1,1,1,1,1,0],
                   'COUNT' : [1,1,1,1,1,1] })
for i in df.columns:
    for j in df.columns:
        for k in df.columns:
            for l in df.columns:


                try:
                    a1 = df.groupby([i,j,k,l], as_index=False, sort=True, group_keys=True)[['VALID','COUNT']].count()
                    a1['RATE'] = a1.VALID / a1.COUNT
                    print(a1)          
                except Exception:
                    pass

Same calculation for all combinations in DataFrame

1 Answers1