I have two data frames
wizards = {player_id': ["3", "4", "0", "9"],
'name':["beal", "avdija", "hachimura", "dinwiddie"],
'total points':}
stat_sheet = {jersey_number': ["9", "9" , "0", "3", "4", "0", "9", "9", , "9" , "0", , "3",
"4", "0", "9"], 'total points':[40, 20, 12, 14, 55, 67, 10, 22, 22, 5, 3, 12, 5, 1]}
wiz_df = pd.DataFrame(wizards)
weeklystats_df = pd.DataFrame(stat_sheet)
I need to make sure that I add up all the points for each player ex:
Beal scored in total 17 points so for his section within the wiz_df it would be 17 points for his row within the wiz_df
So this would need to be done for each player as the unique ID is the player_id and jersey_number
I tried writing a multiple nested for loop which wouldn't work and I tried joining the tables which also did not work either. Kind of stuck on this would appreciate all the help I can get.
You can combine .groupby on weeklystats_df and then .merge with wiz_df:
x = wiz_df.merge(
weeklystats_df.groupby("jersey_number").sum(),
left_on="player_id",
right_index=True,
how="left",
)
print(x)
Prints:
player_id name total points
0 3 beal 17
1 4 avdija 67
2 0 hachimura 89
3 9 dinwiddie 115
wiz_df used:
player_id name
0 3 beal
1 4 avdija
2 0 hachimura
3 9 dinwiddie
weeklystats_df used:
jersey_number total points
0 9 40
1 9 20
2 0 12
3 3 14
4 4 55
5 0 67
6 9 10
7 9 22
8 9 22
9 0 5
10 3 3
11 4 12
12 0 5
13 9 1