for idx, pair in enumerate(sorted_exp_wins):
# edge case for ties; check that current expected wins not same (when rounded) as previous
curr_ew = (idx + 1, pair[1])
curr_aw = owners_wins[pair[0]]
if round(curr_ew[1], 4) == round(prev_ew[1], 4):
print('{0: >4} | {1: >19} | {2: >13.3f} | {3: >11} | {4: >+6.3f}'.format(prev_ew[0], pair[0], prev_ew[1], curr_aw, curr_aw - prev_ew[1]))
else:
print('{0: >4} | {1: >19} | {2: >13.3f} | {3: >11} | {4: >+6.3f}'.format(idx + 1, pair[0], pair[1], curr_aw, curr_aw - pair[1]))
prev_ew = curr_ew
print('\nESPN Power Rankings:')
for row in league_obj.power_rankings(week_num):
print('{0: >19} | {1: >5}'.format(row[1].owner, row[0]))
# update expected wins dictionary
for pair in sorted_scores:
expected_wins[pair[0]] = '{0:.6f}'.format(pair[1]) # round to 6 decimal places
# values are now updated, need to save to a new file for this week
# determine proper filename
if new_wk_num < 10:
new_file = latest_rankings[0:-6] + '0' + str(new_wk_num) + '.csv'
else:
new_file = latest_rankings[0:-6] + str(new_wk_num) + '.csv'
# -*- coding: utf-8 -*-
from espnff import League
import datetime
import numpy as np
from flask import Flask, render_template
app = Flask(__name__)
# Logic for web app. Look into breaking this into modules later.
league_id = 646859
year = 2017
league = League(league_id,year)
team1 = league.teams[0]
powerRankings= league.power_rankings(week=2)
topTeamRank = str(powerRankings[0:][1])
topTeamRank = topTeamRank[5:-1]
points= []
teams = []
pRanks = np.asarray(powerRankings, str)
# Custom date time filter
@app.template_filter()
def datetimefilter(value, format='%Y/%m/%d %H:%M'):
"""convert a datetime to a different format"""
return value.strftime(format)
app.jinja_env.filters['datetimefilter'] = datetimefilter
@app.route("/")
def template_test():
def power_graphs(league_id=None,
year=None,
espn_s2=None,
swid=None,
latestWeek=17):
if league_id == None:
raise Exception('Must enter league ID...Exiting')
elif year == None:
raise Exception('Must enter league year...Exiting')
league = League(league_id, year, espn_s2, swid)
wks = []
twks = []
trks = []
def find_index(df, column, find_term):
df = df[column][df.index[df[column] == find_term]]
return (df.index[0])
for i in range(0, latestWeek):
w = i + 1
wk = league.power_rankings(week=w)
wk = pd.DataFrame(wk, columns=['Score', 'Team'])
wks.append(wk)
wk = wks
wks = []
for i in range(len(wk)):
t = []
s = []
for x in range(len(wk[i])):
tb = str(wk[i]['Team'][x])
tb = str(tb)[5:(len(tb) - 1)]
t.append(tb)
s.append(float(wk[i]['Score'][x]))
ts = pd.DataFrame({'Team': t, 'Score': s})
wks.append(ts)
for i in range(len(wks)):
wks[i].sort_values('Team', inplace=True)
wks[i].reset_index(drop=True, inplace=True)
wksTeam = []
for i in range(len(wks)):
place = [i + 1]
place.extend(list(wks[i]['Score']))
wksTeam.append(place)
c = ['Week']
c.extend(sorted(t))
##Change this to fit your league's team names
color_dict = {
'Team1': '#00e9ff',
'Team2': '#0083ff',
"Team3": '#2e00ff',
'Team4': '#981E32',
'Team5': '#521f6d',
'Team6': '#d8ff00',
"Team7": '#002C5F',
'Team8': '#ffa100',
'Team9': '#6d571f',
'Team10': '#ff0000',
'Team11': '#46b230',
'Team12': '#00ff11'
}
for i in range(len(sorted(t))):
color_dict[t[i]] = color_dict['Team' + str(i + 1)]
tpd = pd.DataFrame(data=wksTeam, columns=c)
tpd.to_csv('wk' + str(len(wksTeam)) + ' power scores.csv', index=False)
tpd = pd.read_csv('wk' + str(len(wksTeam)) + ' power scores.csv',
index_col='Week')
for i in range(len(wks)):
test = wks[i].sort_values('Score', ascending=False)
twks.append(test.reset_index(drop=True))
for x in range(len(twks)):
place = [x + 1]
for i in range(len(sorted(t))):
place.append(find_index(twks[x], 'Team', sorted(t)[i]) + 1)
trks.append(place)
ranks = pd.DataFrame(data=trks, columns=c)
ranks.to_csv('wk' + str(len(wksTeam)) + ' power rankings.csv', index=False)
ranks = pd.read_csv('wk' + str(len(wksTeam)) + ' power rankings.csv',
index_col='Week')
lines = tpd.plot.line(
title='Power Rankings',
table=True,
use_index=False,
color=[color_dict.get(x, '#333333') for x in ranks.columns])
plt.axes().get_xaxis().set_visible(False)
plt.legend(bbox_to_anchor=(1.25, 1), loc='upper right', borderaxespad=0.)
plt.plot(marker='o')
plt.subplots_adjust(0.13, 0.36, 0.81, 0.96, 0.2, 0.2)
lines = ranks.plot.line(
title='Power Score',
table=True,
use_index=False,
color=[color_dict.get(x, '#333333')
for x in ranks.columns]).invert_yaxis()
plt.axes().get_xaxis().set_visible(False)
plt.legend(bbox_to_anchor=(1.25, 1), loc='upper right', borderaxespad=0.)
plt.plot(marker='o')
plt.subplots_adjust(0.13, 0.36, 0.81, 0.96, 0.2, 0.2)
plt.show()