Monte Carlo后处理无法运行，NBA DFS阵容输出空白求助

我写了一套用于NBA每日梦幻体育（DFS）阵容优化的蒙特卡洛模拟后处理代码，运行时没有报错，但最终输出的CSV阵容是空的。这套代码本应完成模拟数据清理、特征计算并生成最优阵容，而且进度提示也完全没触发。我可以提供完整代码协助排查问题，代码如下：

# simR may need to be deleted
#need to convert this into a function

simR = pd.DataFrame()

# l is a dataFrame that will hold the total points scored by each lineup
l = pd.DataFrame()


## a - m stores diffrent features of the simulation results

a = []
b = []
c = []
d = []
e = []
f = []
g = []
h = []
k = []
m = []

token = True  #GPP or cash
for i in range(len(sim)):
    if token == True:
        p = sim.iloc[i,:][sim.iloc[i,:]<= round(num_l*0.01)] #top 1% 12
        q = sim.iloc[i,:][sim.iloc[i,:]<=round(num_l*0.1)] #top 10% 117
        r = sim.iloc[i,:][sim.iloc[i,:]>round(num_l*0.1)] #remaining 117
        l = val.iloc[i,:]
        
        a.append(i+1)
        b.append(p.count())
        e.append((p.count()/num_sim)*100)
        c.append(q.count())
        f.append((q.count()/num_sim)*100)
        d.append(r.count())
        h.append((r.count()/num_sim)*100)
        g.append((p.count()*4)+(q.count()*.1)-(r.count()*5))
        k.append(l.mean())
        m.append(l.std())
        
    else:
        p = [sim.iloc[i,:][sim.iloc[i,:]<=600]] #top 50%
        r = [sim.iloc[i,:][sim.iloc[i,:]>600]] #bottom 50%
        l = val.iloc[i,:]

        
        a.append(i+1)
        b.append(p.count())
        e.append((p.count()/num_sim)*100)
        d.append(r.count())
        h.append((r.count()/num_sim)*100)
        g.append((p.count()*5)-(r.count()*5))
        k.append(l.mean())
        m.append(l.std())
        
        
    if i == 1:
        
        print('Cleaning Data')
        
    elif i==round(num_l*.1):
        print('Data is 10% clean')
        
    elif i==round(num_l*.25):
        print('Data is 25% clean')
    elif i== round(num_l*.5):
        print('Data is 50% clean')
    elif i== round(num_l*.75):
        print('Data is 75% clean')
    elif i== (num_l-1):
        print('Data is 100% clean')

内容的提问来源于stack exchange，提问作者Eddie Chinea