How many different days customer visits app

Question

I have a dataframe that looks like. Each object_id represents different customer.

date    objectId
15/07/18    "__gb5c9e15dfc004930b8ac9d5d1df1880e"
16/07/18    "__g0b2abb9da5d646eb930c1ce9bb6df5ef"
16/07/18    "__c5ff64e5448c44fabe26e88bc0e41497"
17/07/18    "__c7b0a5824a914d7198a328cdf35c95bf"
18/07/18    "__8929216e8d534569ae6fd6701c92fc4c"
19/07/18    "__gec079853a06748a79b4d101713c1e21d"
19/07/18    "__d7f24fa5909b43f4a5282877ed4eed3e"
19/07/18    "__ga523090706304454ba581d79f366816a"
19/07/18    "__d409d75e4207409b8ea030f69b70bf83"
19/07/18    "-g940dc0277b7f46c8b7d8de195a8fd975"
20/07/18    "__d7f24fa5909b43f4a5282877ed4eed3e"
20/07/18    "__ga523090706304454ba581d79f366816a"
21/07/18    "__d409d75e4207409b8ea030f69b70bf83"
21/07/18    "-g940dc0277b7f46c8b7d8de195a8fd975" 

I want to count how many different days does each customer comes. I tried something like

df.groupby(['objectId'])['date'].count(). 

It gives me total number of times customer came to the app not different days that customer came to app.

Answer 1

You can use GroupBy with nunique:

res = df.groupby('objectId')['date'].nunique()

print(res)

objectId
-g940dc0277b7f46c8b7d8de195a8fd975     2
__8929216e8d534569ae6fd6701c92fc4c     1
__c5ff64e5448c44fabe26e88bc0e41497     1
__c7b0a5824a914d7198a328cdf35c95bf     1
__d409d75e4207409b8ea030f69b70bf83     2
__d7f24fa5909b43f4a5282877ed4eed3e     2
__g0b2abb9da5d646eb930c1ce9bb6df5ef    1
__ga523090706304454ba581d79f366816a    2
__gb5c9e15dfc004930b8ac9d5d1df1880e    1
__gec079853a06748a79b4d101713c1e21d    1
Name: date, dtype: int64