'My pulp function has been working, and then randomly. It just stops working

My code has randomly stopped working and I can't figure out the problem. It's supposed to print out the best possible lineup with the requirements of being under $50,000. Only 1 CPT and 5 UTIL. You can't have the name used more than once. It was working a couple of days ago, now it randomly has stopped working. Any fixes?

import pulp
import pandas as pd
    
data_file = '[email protected]'

df = pd.read_csv(data_file, index_col=['Name', 'Roster Position'], skipinitialspace=True)

totalMoney = 0
totalPoints = 0

legal_assignments = df.index   
name_set = df.index.unique(0)  

costs = df['Salary'].to_dict()
values = df['MyOwnProjFPTs'].to_dict()
ids = df['ID'].to_dict()

# set up LP
draft = pulp.LpVariable.dicts('selected', legal_assignments, cat='Binary')

prob = pulp.LpProblem('Draft_Kings_Showdown', pulp.LpMaximize)

# obj
prob += pulp.lpSum([draft[n, p]*values[n,p] for (n, p) in legal_assignments])

# salary cap
prob += pulp.lpSum([draft[n, p]*costs[n,p] for (n, p) in legal_assignments]) <= 50000

# pick 5 UTIL
prob += pulp.lpSum([draft[n, p] for (n, p) in legal_assignments if p == 'UTIL']) == 5

# pick 1 CPT
prob += pulp.lpSum([draft[n, p] for (n, p) in legal_assignments if p == 'CPT']) == 1

# use each player only once
for name in name_set:
    prob += pulp.lpSum([draft[n, p] for (n, p) in legal_assignments if n == name]) <=1

#have under this set amount of points
prob += pulp.lpSum([draft[n, p]*values[n,p] for (n, p) in legal_assignments]) <= 500

print("Name"," " *13,"Salary", " "*4, "Util/Cpt", " "*5, "PPG\n")

for idx in draft:
    if draft[idx].varValue:

        totalMoney += costs[idx]
       
        totalPoints += values[idx]
        print(idx[0], " "*6, costs[idx]," "*6, idx[1], " "*6,values[idx])
        
print("Total used amount of salary cap:", totalMoney, "Amount remaining: ", 50000 - totalMoney)
print("Projected points for the game: ", round(totalPoints, 2))

My CSV file is pictured here -> A picture of my CSV file, with all the column names.



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