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cavedave/correlations

Last active June 26, 2018 10:23
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league results from premiership scraped off wikipedia
Raw
correlations
Pos Pld W D L GF GA Pts
Pos 1.000000 0.355485 -0.891324 0.230178 0.923182 -0.797176 0.842297 -0.904020
Pld 0.355485 1.000000 -0.073403 0.149353 0.257707 -0.040942 0.271909 -0.053488
W -0.891324 -0.073403 1.000000 -0.413831 -0.878324 0.915376 -0.777565 0.989236
D 0.230178 0.149353 -0.413831 1.000000 -0.007839 -0.339314 0.029156 -0.276164
L 0.923182 0.257707 -0.878324 -0.007839 1.000000 -0.816503 0.878841 -0.928555
GF -0.797176 -0.040942 0.915376 -0.339314 -0.816503 1.000000 -0.616188 0.911872
GA 0.842297 0.271909 -0.777565 0.029156 0.878841 -0.616188 1.000000 -0.816231
Pts -0.904020 -0.053488 0.989236 -0.276164 -0.928555 0.911872 -0.816231 1.000000
Raw
multiplePremier.py
df = pd.read_csv('premiership.csv', sep=',', encoding='utf-8', index_col=None)
df.head()
import numpy as np
df.corr()
f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex='col', sharey='row')
f.suptitle('Where to get Premier League Points')
#ax1
ax1.scatter(df['Pts'], df['GF'], alpha=0.7, color='green')
ax1.set_xlabel('Points')
ax1.set_ylabel('Goals Scored')
ax1.text(75, 25, "corr 0.91",size=10)
#ax2
ax2.scatter(df['Pts'], df['GA'], alpha=0.7)
#ax2.title('Premiership Goals Given Away Versus Points')
ax2.set_xlabel('Points')
ax2.set_ylabel('Goals Against')
ax2.text(72, 95, "corr -0.81",size=10)
#ax3
ax3.scatter(df['Pts'], df['W'], alpha=0.5, color='red')
#ax3.title('Premiership Wins Versus Points')
ax3.set_xlabel('Points')
ax3.set_ylabel('Wins')
ax3.text(75, 2, "corr 0.99",size=10)
#ax4
ax4.scatter(df['Pts'], df['D'], alpha=0.6, color='purple')
#ax4.title('Premiership Draws Versus Points')
ax4.set_xlabel('Points')
ax4.set_ylabel('Draws')
ax4.text(75, 28, "corr -.27",size=10)
f.savefig('Premiership.png', bbox_inches='tight')
Raw
pointsgoals.py
df = pd.read_csv('premiership.csv', sep=',', encoding='utf-8', index_col=None)
#,names=['Ans','Details', 'Question','Answer2']
#df.columns = ['Intent', 'Expected','Confidence']
df.head()
plt.scatter(df['Pts'], df['GF'], alpha=0.4)
plt.title('Goals Scored Versus Points')
plt.xlabel('Goals Scored')
plt.ylabel('Points')
plt.text(87, 27, "corr 0.91",size=10)
plt.savefig('GoalsPoints.png', bbox_inches='tight')
import numpy as np
#np.corr(df['GF'], df['GA']) #df['Pts'], df['GF']
df.corr()
Raw
premiership.csv
Pos team Pld W D L GF GA GD Pts year
1 Manchester City (C) 38 28 5 5 93 29 64 89 2012
2 Manchester United 38 28 5 5 89 33 56 89 2012
3 Arsenal 38 21 7 10 74 49 25 70 2012
4 Tottenham Hotspur 38 20 9 9 66 41 25 69 2012
5 Newcastle United 38 19 8 11 56 51 5 65 2012
6 Chelsea 38 18 10 10 65 46 19 64 2012
7 Everton 38 15 11 12 50 40 10 56 2012
8 Liverpool 38 14 10 14 47 40 7 52 2012
9 Fulham 38 14 10 14 48 51 −3 52 2012
10 West Bromwich Albion 38 13 8 17 45 52 −7 47 2012
11 Swansea City 38 12 11 15 44 51 −7 47 2012
12 Norwich City 38 12 11 15 52 66 −14 47 2012
13 Sunderland 38 11 12 15 45 46 −1 45 2012
14 Stoke City 38 11 12 15 36 53 −17 45 2012
15 Wigan Athletic 38 11 10 17 42 62 −20 43 2012
16 Aston Villa 38 7 17 14 37 53 −16 38 2012
17 Queens Park Rangers 38 10 7 21 43 66 −23 37 2012
18 Bolton Wanderers (R) 38 10 6 22 46 77 −31 36 2012
19 Blackburn Rovers (R) 38 8 7 23 48 78 −30 31 2012
20 Wolverhampton Wanderers (R) 38 5 10 23 40 82 −42 25 2012
21 Notts County (R) 46 12 14 20 45 63 −18 50 2012
22 Crawley Town (R) 46 13 11 22 53 79 −26 50 2012
23 Leyton Orient (R) 46 12 13 21 59 69 −10 49 2012
24 Yeovil Town (R) 46 10 10 26 36 75 −39 40 2012
1 Manchester United (C) 38 28 5 5 86 43 43 89 2013
2 Manchester City 38 23 9 6 66 34 32 78 2013
3 Chelsea 38 22 9 7 75 39 36 75 2013
4 Arsenal 38 21 10 7 72 37 35 73 2013
5 Tottenham Hotspur 38 21 9 8 66 46 20 72 2013
6 Everton 38 16 15 7 55 40 15 63 2013
7 Liverpool 38 16 13 9 71 43 28 61 2013
8 West Bromwich Albion 38 14 7 17 53 57 −4 49 2013
9 Swansea City 38 11 13 14 47 51 −4 46 2013
10 West Ham United 38 12 10 16 45 53 −8 46 2013
11 Norwich City 38 10 14 14 41 58 −17 44 2013
12 Fulham 38 11 10 17 50 60 −10 43 2013
13 Stoke City 38 9 15 14 34 45 −11 42 2013
14 Southampton 38 9 14 15 49 60 −11 41 2013
15 Aston Villa 38 10 11 17 47 69 −22 41 2013
16 Newcastle United 38 11 8 19 45 68 −23 41 2013
17 Sunderland 38 9 12 17 41 54 −13 39 2013
18 Wigan Athletic (R) 38 9 9 20 47 73 −26 36 2013
19 Reading (R) 38 6 10 22 43 73 −30 28 2013
1 Chelsea (C) 38 26 9 3 73 32 41 87 2014
2 Manchester City 38 24 7 7 83 38 45 79 2014
3 Arsenal 38 22 9 7 71 36 35 75 2014
4 Manchester United 38 20 10 8 62 37 25 70 2014
5 Tottenham Hotspur 38 19 7 12 58 53 5 64 2014
6 Liverpool 38 18 8 12 52 48 4 62 2014
7 Southampton 38 18 6 14 54 33 21 60 2014
8 Swansea City 38 16 8 14 46 49 −3 56 2014
9 Stoke City 38 15 9 14 48 45 3 54 2014
10 Crystal Palace 38 13 9 16 47 51 −4 48 2014
11 Everton 38 12 11 15 48 50 −2 47 2014
12 West Ham United 38 12 11 15 44 47 −3 47 2014
13 West Bromwich Albion 38 11 11 16 38 51 −13 44 2014
14 Leicester City 38 11 8 19 46 55 −9 41 2014
15 Newcastle United 38 10 9 19 40 63 −23 39 2014
16 Sunderland 38 7 17 14 31 53 −22 38 2014
17 Aston Villa 38 10 8 20 31 57 −26 38 2014
18 Hull City (R) 38 8 11 19 33 51 −18 35 2014
19 Burnley (R) 38 7 12 19 28 53 −25 33 2014
20 Queens Park Rangers (R) 38 8 6 24 42 73 −31 30 2014
1 Leicester City (C) 38 23 12 3 68 36 32 81 2015
2 Arsenal 38 20 11 7 65 36 29 71 2015
3 Tottenham Hotspur 38 19 13 6 69 35 34 70 2015
4 Manchester City 38 19 9 10 71 41 30 66 2015
5 Manchester United 38 19 9 10 49 35 14 66 2015
6 Southampton 38 18 9 11 59 41 18 63 2015
7 West Ham United 38 16 14 8 65 51 14 62 2015
8 Liverpool 38 16 12 10 63 50 13 60 2015
9 Stoke City 38 14 9 15 41 55 −14 51 2015
10 Chelsea 38 12 14 12 59 53 6 50 2015
11 Everton 38 11 14 13 59 55 4 47 2015
12 Swansea City 38 12 11 15 42 52 −10 47 2015
13 Watford 38 12 9 17 40 50 −10 45 2015
14 West Bromwich Albion 38 10 13 15 34 48 −14 43 2015
15 Crystal Palace 38 11 9 18 39 51 −12 42 2015
16 Bournemouth 38 11 9 18 45 67 −22 42 2015
17 Sunderland 38 9 12 17 48 62 −14 39 2015
18 Newcastle United (R) 38 9 10 19 44 65 −21 37 2015
19 Norwich City (R) 38 9 7 22 39 67 −28 34 2015
20 Aston Villa (R) 38 3 8 27 27 76 −49 17 2015
1 Chelsea (C) 38 30 3 5 85 33 52 93 2016
2 Tottenham Hotspur 38 26 8 4 86 26 60 86 2016
3 Manchester City 38 23 9 6 80 39 41 78 2016
4 Liverpool 38 22 10 6 78 42 36 76 2016
5 Arsenal 38 23 6 9 77 44 33 75 2016
6 Manchester United 38 18 15 5 54 29 25 69 2016
7 Everton 38 17 10 11 62 44 18 61 2016
8 Southampton 38 12 10 16 41 48 −7 46 2016
9 Bournemouth 38 12 10 16 55 67 −12 46 2016
10 West Bromwich Albion 38 12 9 17 43 51 −8 45 2016
11 West Ham United 38 12 9 17 47 64 −17 45 2016
12 Leicester City 38 12 8 18 48 63 −15 44 2016
13 Stoke City 38 11 11 16 41 56 −15 44 2016
14 Crystal Palace 38 12 5 21 50 63 −13 41 2016
15 Swansea City 38 12 5 21 45 70 −25 41 2016
16 Burnley 38 11 7 20 39 55 −16 40 2016
17 Watford 38 11 7 20 40 68 −28 40 2016
18 Hull City (R) 38 9 7 22 37 80 −43 34 2016
19 Middlesbrough (R) 38 5 13 20 27 53 −26 28 2016
20 Sunderland (R) 38 6 6 26 29 69 −40 24 2016
1 Manchester City (C) 38 32 4 2 106 27 79 100 2017
2 Manchester United 38 25 6 7 68 28 40 81 2017
3 Tottenham Hotspur 38 23 8 7 74 36 38 77 2017
4 Liverpool 38 21 12 5 84 38 46 75 2017
5 Chelsea 38 21 7 10 62 38 24 70 2017
6 Arsenal 38 19 6 13 74 51 23 63 2017
7 Burnley 38 14 12 12 36 39 −3 54 2017
8 Everton 38 13 10 15 44 58 −14 49 2017
9 Leicester City 38 12 11 15 56 60 −4 47 2017
10 Newcastle United 38 12 8 18 39 47 −8 44 2017
11 Crystal Palace 38 11 11 16 45 55 −10 44 2017
12 Bournemouth 38 11 11 16 45 61 −16 44 2017
13 West Ham United 38 10 12 16 48 68 −20 42 2017
14 Watford 38 11 8 19 44 64 −20 41 2017
15 Brighton & Hove Albion 38 9 13 16 34 54 −20 40 2017
16 Huddersfield Town 38 9 10 19 28 58 −30 37 2017
17 Southampton 38 7 15 16 37 56 −19 36 2017
18 Swansea City (R) 38 8 9 21 28 56 −28 33 2017
19 Stoke City (R) 38 7 12 19 35 68 −33 33 2017
20 West Bromwich Albion (R) 38 6 13 19 31 56 −25 31 2017
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