How to sort and count each unique value in a column in Pandas

Question

I currently have a data frame that is a reading a csv file called: "wimbledons_champions_claned.csv" I need to gather the data for the number of each unique nationality in the column "Champion Nationality". For example, nationality that shows up in the data is "AUS" and I need to count how many there are and I need to do this with 14 others. Is there any efficient way to do this without having to hard code. I currently am doing something like this:

 import pandas as pd
 df = pd.read_csv("wimbledons_champions_claned.csv")

 ausChampions = len(df[df['Champion Nationality'] == 'AUS']
 fraChampions = len(df[df['Champion Nationality'] == 'FRA']
 etc...

If there is any better way to do this I would greatly appreciate it. Thank you.

Answer 1

Something like this:

df['Champion Nationality'].value_counts()

Answer 2

You could just use df['Champion Nationality'].value_counts() . You could also use the Counter function from the collections library. This will return a dictionary of each Champion Nationality in the pandas and how many times is repeated.

import pandas as pd
from collections import Counter

df = pd.read_csv("wimbledons_champions_claned.csv")

result = Counter(df['Champion Nationality'].tolist())

so if you do result['AUS'] it will return how many times it has shown up on the DataFrame