Count how many times a value occurs in a pandas data frame based on a condition

Question

I'm trying to calculate how many times a value occurs in a specific location inside a data frame.

As an example I use this data frame:

   import pandas as pd
   
   d = {'Fruit': ['Apple', 'Apple', 'Apple', 'Onion', 'Onion', 'Onion', 'Onion', 'Pear', 'Pear', 'Pear', 
   'Pear', 'Pear'],
        'Country': ['USA', 'SUI', 'USA', 'SUI', 'USA', 'SUI', 'SUI', 'USA', 'USA', 'USA', 'SUI', 'SUI']}

   df = pd.DataFrame(data=d)

I do not understand how I can calculate for example how many Apples there are in USA and SUI and add this to a 'Count' column.

The output should look something like this:

import pandas as pd

d = {'Fruit': ['Apple', 'Apple', 'Apple', 'Onion', 'Onion', 'Onion', 'Onion', 'Pear', 'Pear', 'Pear', 'Pear', 'Pear'],
     'Country': ['USA', 'SUI', 'USA', 'SUI', 'USA', 'SUI', 'SUI', 'USA', 'USA', 'USA', 'SUI', 'SUI'],
     'Count': [2, 1, 2, 3, 1, 3, 3, 3, 3, 3, 2, 2]}

df = pd.DataFrame(data=d)

I would know how to count the values themselves (how many apples occur in the Fruit column) but not how to add this condition to the calculation.

Thanks for your help in advance.

Answer 1

Try Groupby transform :

df['counts'] = df.groupby(['Fruit', 'Country'])['Country'].transform('size')

df :

    Fruit Country  counts
0   Apple     USA       2
1   Apple     SUI       1
2   Apple     USA       2
3   Onion     SUI       3
4   Onion     USA       1
5   Onion     SUI       3
6   Onion     SUI       3
7    Pear     USA       3
8    Pear     USA       3
9    Pear     USA       3
10   Pear     SUI       2
11   Pear     SUI       2

Answer 2

You can use groupby followed by a join , like this:

fruit_counts = df.groupby(["Fruit", "Country"]).size().rename("Count")
df.join(fruit_counts, on=["Fruit", "Country"])

Output:

    Fruit Country  Count
0   Apple     USA      2
1   Apple     SUI      1
2   Apple     USA      2
3   Onion     SUI      3
4   Onion     USA      1
5   Onion     SUI      3
6   Onion     SUI      3
7    Pear     USA      3
8    Pear     USA      3
9    Pear     USA      3
10   Pear     SUI      2
11   Pear     SUI      2