def exclude_players(df):
import pandas as pd
import numpy as np
import FF_scoring
import easygui as eg
players = pd.unique(df.Name.ravel()) #getting a list of teams for the week
question = "Select players to exclude"
title = "Select players"
listOfOptions = players
choice = eg.multchoicebox(question , title, listOfOptions)
print choice
cont = raw_input("Exclude these players (if none are showing, there are none selected)? (y/n)")
cont = str(cont)
if cont == 'y':
df = df[~df.Name.isin(choice)] #removing the teams
else:
df = FF_scoring.exclude_players(df)
return df
if fd =='1':
#kick_sal = 5000
kick_sal = raw_input("Enter kicker salary: ")
kick_sal = int(kick_sal)
salary = 60000-kick_sal
data_set = "weeks/week-" +week + "/aggregate-week" +week +'fd.csv'
excel_out = "weeks/week-" +week + "/lineups-week" + week + spec +'fd.xlsx'
else:
data_set = "weeks/week-" +week + "/aggregate-week" +week +'dk.csv'
excel_out = "weeks/week-" +week + "/lineups-week" + week + spec + 'dk.xlsx'
#getting the data
df = pd.read_csv(data_set)
df = FF_scoring.exclude_teams(df)
df = FF_scoring.exclude_players(df)
#need a list here
#score_list = ['average']
score_list = FF_scoring.which_scores(df)
#print score_list
#---------
#cont = raw_input("Continue (y/n)?") # for ESPN, this is for the csv_output (auto-refreshes projections)
#cont = str(cont)
#if cont == 'n':
# sys.exit(0)
#---------
