NBA_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "import numpy as np\n",
    "import pandas as pd \n",
    "from matplotlib.patches import Arc, Circle\n",
    "import networkx as nx\n",
    "import community\n",
    "from matplotlib.patches import Circle, Rectangle, Arc\n",
    "%matplotlib inline\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib.gridspec as gridspec\n",
    "plt.style.use('seaborn-white')\n",
    "from matplotlib.font_manager import FontProperties\n",
    "from matplotlib import rcParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gsw_pass_matrix = [[0,4.0,19.5,7.8,9.5], [4.6,0,6.2,2.2,2.8], [36.0,3.7,0,10.8,12.8], [3.6,2.6,7.8,0,6.6],\n",
    "                  [13.0,2.2,12.8,6.3,0]]\n",
    "gsw_pass = np.asarray(gsw_pass_matrix)\n",
    "toronto_pass_matrix = [[0, 15.3, 14.5, 17.2, 5.7], [17.7, 0, 6.7, 8.8, 3.5], [18.7, 8.2, 0, 10.2, 2.2],[12.2, 8.8, 8, 0, 3.8], [8.2, 3.3, 2.7, 3.3, 0]]\n",
    "toronto_pass = np.asarray(toronto_pass_matrix)\n",
    "gsw_names = ['Curry', 'Looney', 'Green', 'Thompson', 'Iguodala']\n",
    "toronto_names = ['Lowry', 'Siakam', 'Gasol', 'Leonard', 'Green']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "mat1 = []\n",
    "mat2 = []\n",
    "for i in range(len(toronto_names)):\n",
    "    for j in range(5):\n",
    "        if toronto_pass[i][j] == 0:\n",
    "            mat1.append([toronto_names[i], toronto_names[j], toronto_pass[i][j]])\n",
    "        else:\n",
    "            mat1.append([toronto_names[i], toronto_names[j], 1/toronto_pass[i][j]])\n",
    "\n",
    "#For pagerank\n",
    "for i in range(len(toronto_names)):\n",
    "    for j in range(5):\n",
    "        if toronto_pass[i][j] == 0:\n",
    "            mat2.append([toronto_names[i], toronto_names[j], toronto_pass[i][j]])\n",
    "        else:\n",
    "            mat2.append([toronto_names[i], toronto_names[j], toronto_pass[i][j]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "H = nx.DiGraph()\n",
    "H.add_nodes_from(toronto_names)\n",
    "H.add_weighted_edges_from(mat1)\n",
    "\n",
    "#For pagerank\n",
    "I = nx.DiGraph()\n",
    "I.add_nodes_from(toronto_names)\n",
    "I.add_weighted_edges_from(mat2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Lowry': 1.0,\n",
       " 'Siakam': 0.3333333333333333,\n",
       " 'Gasol': 0.3333333333333333,\n",
       " 'Leonard': 0.3333333333333333,\n",
       " 'Green': 0.3333333333333333}"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Betweeness Centrality \n",
    "b_g = nx.betweenness_centrality(H, normalized=True, weight = 'weight')\n",
    "b_g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Eigenvector Centrality\n",
    "e_g = nx.eigenvector_centrality(H, max_iter=100, tol=1e-06, nstart=None, weight='weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PageRank Centrality\n",
    "p_g = nx.pagerank(I, weight = 'weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Closeness Centrality\n",
    "c_g = nx.closeness_centrality(H, distance='weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "mat = []\n",
    "mat0 = []\n",
    "for i in range(len(gsw_names)):\n",
    "    for j in range(5):\n",
    "        if gsw_pass[i][j] == 0:\n",
    "            mat.append([gsw_names[i], gsw_names[j], gsw_pass[i][j]])\n",
    "        else:\n",
    "            mat.append([gsw_names[i], gsw_names[j], 1/gsw_pass[i][j]])\n",
    "for i in range(len(gsw_names)):\n",
    "    for j in range(5):\n",
    "        if gsw_pass[i][j] == 0:\n",
    "            mat0.append([gsw_names[i], gsw_names[j], gsw_pass[i][j]])\n",
    "        else:\n",
    "            mat0.append([gsw_names[i], gsw_names[j], gsw_pass[i][j]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = nx.DiGraph()\n",
    "G.add_nodes_from(gsw_names)\n",
    "G.add_weighted_edges_from(mat)\n",
    "\n",
    "F = nx.DiGraph()\n",
    "F.add_nodes_from(gsw_names)\n",
    "F.add_weighted_edges_from(mat0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "b_t = nx.betweenness_centrality(G, normalized=True, weight = 'weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "#e_t = nx.eigenvector_centrality(G, max_iter=100, tol=1e-06, nstart=None, weight='weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "p_t = nx.pagerank(F, weight = 'weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "c_t = nx.closeness_centrality(G, distance='weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 1)"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#fig, ax = plt.subplots(2, 2, sharey = True)\n",
    "fig.suptitle('Golden State Warriors')\n",
    "fig.subplots_adjust(wspace=0.4)\n",
    "ax[0,0].barh(toronto_names, b_t.values(), color = '#1D428A', align = 'center')\n",
    "ax[0,0].set(title = \"Betweenness Centrality\")\n",
    "ax[0,1].barh(toronto_names, e_t.values(), color = '#FFC72C', align = 'center')\n",
    "ax[1,0].barh(toronto_names, p_t.values(), color = '#26282A', align = 'center')\n",
    "ax[1,0].set_xlim(0, 1)\n",
    "ax[0,0].set_xlim(0, 1)\n",
    "ax[0,1].set_xlim(0, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 14)"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1 = plt.figure()\n",
    "gs = gridspec.GridSpec(2, 4)\n",
    "fig1.suptitle('Toronto Raptors', size = 15)\n",
    "gs.update(wspace=1, hspace=0.4)\n",
    "ax1 = plt.subplot(gs[0, :2], )\n",
    "ax1.barh(toronto_names, b_g.values(), color = '#CE1141', align = 'center')\n",
    "ax1.set(title = \"Betweenness Centrality\")\n",
    "ax1.set_xlim(0,1)\n",
    "\n",
    "ax2 = plt.subplot(gs[0, 2:])\n",
    "ax2.barh(toronto_names, p_g.values(), color = '#000000', align = 'center')\n",
    "ax2.set(title = \"PageRank Centrality\")\n",
    "ax2.set_xlim(0,1)\n",
    "\n",
    "ax3 = plt.subplot(gs[1, :])\n",
    "ax3.set(title = \"Closeness Centrality\")\n",
    "ax3.barh(toronto_names, c_g.values(), color = '#B4975A', align = 'center')\n",
    "ax3.set_xlim(0,14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 14)"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1 = plt.figure()\n",
    "gs = gridspec.GridSpec(2, 4)\n",
    "gs.update(wspace=1.5, hspace=0.4)\n",
    "fig1.suptitle('Golden State Warriors', size = 15)\n",
    "ax1 = plt.subplot(gs[0, :2], )\n",
    "ax1.barh(gsw_names, b_t.values(), color = '#1D428A', align = 'center')\n",
    "ax1.set(title = \"Betweenness Centrality\")\n",
    "ax1.set_xlim(0,1)\n",
    "\n",
    "ax2 = plt.subplot(gs[0, 2:])\n",
    "ax2.barh(gsw_names, p_t.values(), color = '#FFC72C', align = 'center')\n",
    "ax2.set(title = \"PageRank Centrality\")\n",
    "ax2.set_xlim(0,1)\n",
    "\n",
    "ax3 = plt.subplot(gs[1, :])\n",
    "ax3.set(title = \"Closeness Centrality\")\n",
    "ax3.barh(gsw_names, c_t.values(), color = '#26282A', align = 'center')\n",
    "ax3.set_xlim(0,14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 1)"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Betweenness \n",
    "ax = plt.subplot(111)\n",
    "ax.barh(toronto_names, b_g.values(), color = '#CE1141', align = 'center')\n",
    "ax.set(title = \"Betweenness Centrality: Toronto Raptors\")\n",
    "ax.set_xlim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 1)"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax1 = plt.subplot(111)\n",
    "ax1.barh(gsw_names, b_t.values(), color = '#1D428A', align = 'center')\n",
    "ax1.set(title = \"Betweenness Centrality: Golden State Warriors\")\n",
    "ax1.set_xlim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 1)"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Closeness \n",
    "ax = plt.subplot(111)\n",
    "ax.barh(toronto_names, p_g.values(), color = '#000000', align = 'center')\n",
    "ax.set(title = \"PageRank Centrality: Toronto Raptors\")\n",
    "ax.set_xlim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 1)"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax1 = plt.subplot(111)\n",
    "ax1.barh(gsw_names, p_t.values(), color = '#FFC72C', align = 'center')\n",
    "ax1.set(title = \"PageRank Centrality: Golden State Warriors\")\n",
    "ax1.set_xlim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 14)"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax3 = plt.subplot(111)\n",
    "ax3.set(title = \"Closeness Centrality\")\n",
    "ax3.barh(gsw_names, c_t.values(), color = '#26282A', align = 'center')\n",
    "ax3.set_xlim(0,14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 14)"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax3 = plt.subplot(111)\n",
    "ax3.set(title = \"Closeness Centrality\")\n",
    "ax3.barh(toronto_names, c_g.values(), color = '#B4975A', align = 'center')\n",
    "ax3.set_xlim(0,14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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