[FIXED] I am trying to groupby values in a specific column that holds multiple values?

Issue

I have this huge netflix dataset which I am trying to see which actors appeared in the most movies/tv shows specifically in America. First, I created a list of unique actors from the dataset. Then created a nested for loop to loop through each name in list3(containing unique actors which checked each row in df3(filtered dataset with 2000+rows) if the column cast contained the current actors name from list3. I believe using iterrows takes too long

myDict1 = {}


for name in list3:
    if name not in myDict1:
        myDict1[name] = 0
    for index, row in df3.iterrows():
        if name in row["cast"]:
            myDict1[name] += 1
            
myDict1

Title	cast
Movie1	Robert De Niro, Al Pacino, Tarantino
Movie2	Tom Hanks, Robert De Niro, Tom Cruise
Movie3	Tom Cruise, Zendaya, Seth Rogen

I want my output to be like this:

Name	Count
Robert De Niro	2
Tom Cruise	2

Solution

Use

out = df['cast'].str.split(', ').explode().value_counts()
out = pd.DataFrame({'Name': out.index, 'Count': out.values})


>>> out
             Name  Count
0      Tom Cruise      2
1  Robert De Niro      2
2         Zendaya      1
3      Seth Rogen      1
4       Tarantino      1
5       Al Pacino      1
6       Tom Hanks      1

Answered By - Amit Vikram Singh