console.clear()

var data = d3.csvParse(`Starters,Tm,MP,FG,FGA,3P,3PA,FT,FTA,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS,FG%,3P%,FT%
James Harden\hardeja01,HOU,27:04,5,19,2,13,0,0,1,6,7,8,1,1,3,1,12,.263,.154,
DeMar DeRozan\derozde01,TOR,26:46,7,13,1,3,6,7,2,4,6,2,2,0,2,1,21,.538,.333,.857
Stephen Curry\curryst01,GSW,26:35,4,14,3,11,0,0,2,4,6,5,1,0,6,0,11,.286,.273,
Giannis Antetokounmpo\antetgi01,MIL,26:34,6,14,0,2,4,6,4,3,7,2,0,0,2,2,16,.429,.000,.667
Joel Embiid\embiijo01,PHI,20:05,8,13,2,4,1,1,3,5,8,1,1,2,0,3,19,.615,.500,1.000
Kyle Lowry\lowryky01,TOR,21:26,2,11,0,8,0,0,2,5,7,11,3,0,1,1,4,.182,.000,
Klay Thompson\thompkl01,GSW,21:25,5,11,5,10,0,0,1,3,4,0,0,0,1,0,15,.455,.500,
Damian Lillard\lillada01,POR,20:56,9,14,3,8,0,0,2,1,3,2,0,0,1,0,21,.643,.375,
Draymond Green\greendr01,GSW,18:14,0,0,0,0,3,4,3,2,5,2,1,2,0,0,3,,,.750
Karl-Anthony Towns\townska01,MIN,18:11,7,11,1,4,2,2,4,6,10,0,0,0,1,0,17,.636,.250,1.000
Al Horford\horfoal01,BOS,12:46,2,4,0,2,2,2,0,5,5,2,1,0,0,0,6,.500,.000,1.000
LeBron James\jamesle01,LAL,31:17,12,17,4,8,1,1,0,10,10,8,1,0,5,2,29,.706,.500,1.000
Kevin Durant\duranke01,GSW,29:57,7,13,3,8,2,2,1,5,6,5,3,1,2,3,19,.538,.375,1.000
Russell Westbrook\westbru01,OKC,28:28,4,11,1,6,2,3,3,5,8,8,0,0,2,2,11,.364,.167,.667
Kyrie Irving\irvinky01,BOS,27:36,6,16,1,5,0,0,2,5,7,9,1,0,1,2,13,.375,.200,
Anthony Davis\davisan02,NOP,16:40,6,9,0,1,0,0,1,1,2,1,0,0,1,2,12,.667,.000,
Paul George\georgpa01,OKC,26:30,6,15,4,10,0,0,1,4,5,4,1,0,0,2,16,.400,.400,
Andre Drummond\drumman01,DET,17:36,7,7,0,0,0,0,1,2,3,0,0,1,1,2,14,1.000,,
Bradley Beal\bealbr01,WAS,16:51,5,10,4,8,0,0,0,0,0,0,1,0,1,1,14,.500,.500,
Victor Oladipo\oladivi01,IND,15:00,3,8,1,6,0,0,0,2,2,3,3,0,0,0,7,.375,.167,
Kemba Walker\walkeke02,CHO,14:09,5,10,1,5,0,0,1,1,2,1,0,0,0,0,11,.500,.200,
Goran Dragic\dragigo01,MIA,11:28,1,3,0,1,0,0,0,4,4,1,0,0,1,2,2,.333,.000,
LaMarcus Aldridge\aldrila01,SAS,4:28,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,.000,,
Cousins,GSW
Love,CLE
Porzingis,NYK
Wall,WAS
Butler,MIN
`)

var teams = `
TOR* (1)  F C $ 59  23
BOS* (2)  F C $ 55  27
PHI* (3)  F C $ 52  30
CLE* (4)  F C $ 50  32
IND* (5)  F C $ 48  34
MIA* (6)  F C $ 44  38
MIL* (7)  F C $ 44  38
WAS* (8)  F C $ 43  39
DET (9)   F C $ 39  43
CHO (10)  F C $ 36  46
NYK (11)  F C $ 29  53
BRK (12)  F C $ 28  54
CHI (13)  F C $ 27  55
ORL (14)  F C $ 25  57
ATL (15)  F C $ 24  58
HOU* (1)  F C $ 65  17
GSW* (2)  F C $ 58  24
POR* (3)  F C $ 49  33
OKC* (4)  F C $ 48  34
UTA* (5)  F C $ 48  34
NOP* (6)  F C $ 48  34
SAS* (7)  F C $ 47  35
MIN* (8)  F C $ 47  35
DEN (9)   F C $ 46  36
LAC (10)  F C $ 42  40
LAL (11)  F C $ 35  47
SAC (12)  F C $ 27  55
DAL (13)  F C $ 24  58
MEM (14)  F C $ 22  60
PHO (15)  F C $ 21  61
`.split('\n').filter(d => d).map(d => d.substr(0, 3))


byTeam = d3.nestBy(data, d => d.Tm)

teams.forEach(team => {
  var m = _.find(byTeam, {key: team})

  var rv = []
  rv.key = team
  if (!m) byTeam.push(rv)
})

byLength = d3.nestBy(byTeam, d => d.length)


d3.select('body').selectAppend('div.tooltip.tooltip-hidden')

var sel = d3.select('#graph').html('')
var c = d3.conventions({sel, margin: {left: 100}, width: 390, height: 300})

c.x.domain([0, 5])
c.y.domain([0, 15])

c.xAxis.tickFormat(d => d).ticks(5)
d3.drawAxis(c)


c.svg.appendMany('g', byLength)
  .translate(d => c.x(d.key), 0)
  .appendMany('text.team', d => d)
  .translate((d, i) => c.y(i) - 10, 1)
  .text(d => d.key)

c.svg.append('text.title')
  .text("Number of Last Season's All-Stars on Each Team")
  .at({textAnchor: 'middle', x: c.width/2, y: c.height + 80 })