Pandas Python: Add column that counts IDs per Product

Question

I am trying to add a column to my dataframe that tells me the number of a product per group. My dataframe looks like this:

ID    Product  Time
6578  X        ...
6574  Y
6439  X
6543  Y
6756  X
6756  X

What I want as an output is this:

ID    Product   Number_of_ID_per_Product  Time
6578  X         1                         ...
6574  Y         1
6439  X         2
6543  Y         2
6756  X         3
6756  X         4

I tried

df['ID_Number_per_Part']=vormessen.groupby(['Product'])['ID'].count()

which gives me only NaN values.

Use `vormessen.groupby('Product')['ID'].cumcount().add(1)` – Chris Adams Sep 07 '20 at 12:59 — Chris Adams, Sep 07 '20 at 12:59

score 0 · Answer 1 · answered Sep 07 '20 at 13:20

this can be done using group by statement (a concept very widely used in SQL)

df[0].groupyby(1: name of the field to group by with)(2: aggregated fields).([3: type of aggregation].()

In your case it will be:

Vormasseen
Product
ID
Count

Similarly, you can do the same for avg, max, min, etc.

Pandas Python: Add column that counts IDs per Product

1 Answers1