How to get items from a df meeting another df's criteria

Question

I have a df of users and the teams they belong. Another df with teams and their scores on different match. I want to select only the scores that match a user’s team:

import pandas as pd

users = [['tom', 'team1'], ['tom', 'team2'], ['john', 'team2'], ['john', 'team3']]
match = [['team1', 100], ['team2', 120], ['team2', 80], ['team3', 70]]

users_df = pd.DataFrame(users, columns=['name', 'team'])
match_df = pd.DataFrame(match, columns=['team','score'])

user_teams = users_df['team'][users_df['name']== 'tom'].to_list()

scores = []
for x in user_teams:
    a = match_df['score'][match_df['team'] == x].to_list()
    scores.append(a)

print(scores)

So, the output should be team1 and team2 scores inside a list:

[100, 120, 80]

The problem is that with this code I get each item inside a list that appends to ‘scores’ list:

[[100], [120, 80]]

But if I run the code without to_list() command on the line a = match_df['score'][match_df['team'] == x].to_list(), I have the following as result:

[0    100
Name: score, dtype: object, 2    120
Name: score, dtype: object]

What am I doing wrong?

Asked By: vini.m.oliveira

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Source

Answer 1

there are 2 ways to achieve this:

use extend to the list (not append) (as suggested by @Psidom)
OR
flatten the scores such that: [i for sg in scores for i in sg]

example:

scores  = [[100], [120, 80]]
[i for sg in scores for i in sg] #sg for sub_group

desired result

 [100, 120, 80]

Answered By: adhg

Answer 2

At the end of your group you can write:

out = [s for group in scores for s in group]
print(out)

This should remove the extra list within the list. Cheers

Answered By: Saad Bin Munir

How to get items from a df meeting another df's criteria

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