Code

import cvxpy
import pandas as pd
import numpy as np
from wordcloud import WordCloud
import matplotlib.pyplot as plt

###load data
PL = pd.read_csv(dath_path)

###visualization
point_dict = dict(zip(PL.Name,PL.Points))
text = " ".join ([(k + " ")* v for k,v in point_dict.items()])
wordcloud = WordCloud(max_font_size = 50, ,max_words = 100 , background_color = 'white',collocations = False).generate(text)
plt.imshow(wordcloud)
plt.axis("off")

###auxiliary variables
end_GK = PL.index[PL['Role']=='GK']
end_GK = end_GK[len(end_GK)-1]

end_D = PL.index[PL['Role']=='D']
end_D = end_D[len(end_D)-1]

end_M = PL.index[PL['Role']=='M']
end_M = end_M[len(end_M)-1]

###fixed input
Budget = 100
prices = np.array(PL['Price']) 
points = np.array(PL['Points'])
GoalKeepers = 2
Defenders = 5
Midfielders = 5
Forwards = 3 

###Desicion variabels - choose/not choose player
selection = cvxpy.Bool(len(prices))

###constraints
#Budget 
C1 = selection.T * prices <= Budget
#Choose 2 Goal keepers
C2 = selection[:(end_GK+1)].T * np.ones(end_GK+1) == GoalKeepers
#Choose 5 Defenders
C3 = selection[(end_GK+1):(end_D+1)].T * np.ones(end_D-end_GK) == Defenders
#Choose 5 Midfielders
C4 = selection[(end_D+1):(end_M+1)].T * np.ones(end_M-end_D) == Midfielders
#Choose 3 Forwards
C5 = selection[(end_M+1):].T * np.ones(len(prices)-end_M-1) == Forwards
#select at most 3 players from each team
teams = PL.Team.unique()
lsC = []
for t in teams:
    lsC.append(selection[PL['Team']==t].T * np.ones(sum(PL['Team']==t))<=3)
lsC.append(C1)
lsC.append(C2)
lsC.append(C3)
lsC.append(C4)
lsC.append(C5)

###target function
TF = selection.T*points

###problem define and solve
PL_problem = cvxpy.Problem(cvxpy.Maximize(TF), lsC)
PL_problem.solve(solver=cvxpy.GLPK_MI)

###chosen variables
CV = selection.value
all_players = PL['Name'].tolist()

opt_team = []
for ind,name in enumerate(all_players):
    if CV[ind]==1:
        opt_team.append(name)