book5_linking.ipynb

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   "source": [
    "# Bokeh Libraries\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.models import ColumnDataSource, CategoricalColorMapper, Div, NumeralTickFormatter\n",
    "from bokeh.layouts import gridplot, column\n",
    "\n",
    "# Import data\n",
    "from read_nba_data import team_stats\n",
    "\n",
    "# Out to file\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare data\n",
    "gm_stats = (team_stats[team_stats['teamAbbr'] == 'CHI']\n",
    "                .loc[:, ['gmDate',\n",
    "                         'teamPTS',\n",
    "                         'teamTRB',\n",
    "                         'teamAST',\n",
    "                         'teamTO',\n",
    "                         'team2P%',\n",
    "                         'team3P%',\n",
    "                         'opptPTS']]\n",
    "                .sort_values('gmDate'))\n",
    "\n",
    "# Add game number\n",
    "gm_stats['game_num'] = range(1, len(gm_stats)+1)\n",
    "\n",
    "# Make a win_loss column\n",
    "win_loss = []\n",
    "for _, row in gm_stats.iterrows():\n",
    "\n",
    "    if row['teamPTS'] > row['opptPTS']:\n",
    "        win_loss.append('W')\n",
    "    else:\n",
    "        win_loss.append('L')\n",
    "\n",
    "# Add the win_loss data to the DataFrame\n",
    "gm_stats['winLoss'] = win_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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      "application/vnd.bokehjs_exec.v0+json": ""
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     "metadata": {
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   "source": [
    "# Store the data in a ColumnDataSource\n",
    "gm_stats_cds = ColumnDataSource(gm_stats)\n",
    "\n",
    "# Create a CategoricalColorMapper that assigns a color to wins and losses\n",
    "win_loss_mapper = CategoricalColorMapper(factors = ['W', 'L'],\n",
    "                                         palette=['green', 'red'])\n",
    "\n",
    "\n",
    "# Map stat names to columns in the data\n",
    "stat_names = {'Points': 'teamPTS',\n",
    "              'Assists': 'teamAST',\n",
    "              'Rebounds': 'teamTRB',\n",
    "              'Turnovers': 'teamTO'}\n",
    "\n",
    "# The figure for each stat will be held in this dict\n",
    "stat_figs = {}\n",
    "\n",
    "# For each stat in the dict\n",
    "for stat_label, stat_col in stat_names.items():\n",
    "\n",
    "    # Create a figure\n",
    "    fig = figure(y_axis_label=stat_label,\n",
    "                 height=200, width=400,\n",
    "                 x_range=(1, 10), tools=['xpan', 'reset', 'save'])\n",
    "\n",
    "    # Configure vbar\n",
    "    fig.vbar(x='game_num', top=stat_col, source=gm_stats_cds, width=0.9,\n",
    "             color=dict(field='winLoss', transform=win_loss_mapper))\n",
    "\n",
    "    # Add the figure to stats_figs dict\n",
    "    stat_figs[stat_label] = fig\n",
    "\n",
    "# Create layout\n",
    "grid = gridplot([[stat_figs['Points'], stat_figs['Assists']],\n",
    "                [stat_figs['Rebounds'], stat_figs['Turnovers']]])\n",
    "\n",
    "# Link together the x-axes\n",
    "stat_figs['Points'].x_range = \\\n",
    "    stat_figs['Assists'].x_range = \\\n",
    "    stat_figs['Rebounds'].x_range = \\\n",
    "    stat_figs['Turnovers'].x_range\n",
    "\n",
    "# Add a title for the entire visualization using Div\n",
    "html = \"\"\"<h3>Chicago Game Log</h3>\n",
    "<b><i>2017-18 </i></b>\n",
    "<br>\n",
    "<i>Wins (green) vs Losses (red)</i>\n",
    "\"\"\"\n",
    "sup_title = Div(text=html)\n",
    "\n",
    "# Visualize\n",
    "show(column(sup_title, grid))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
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   ],
   "source": [
    "# Specify the tools\n",
    "toolList = ['lasso_select', 'tap', 'reset', 'save']\n",
    "\n",
    "# Create a figure relating the percentages\n",
    "pctFig = figure(title='2PT FG % vs 3PT FG %, 2017-18 Regular Season',\n",
    "                height=400, width=400, tools=toolList,\n",
    "                x_axis_label='2PT FG%', y_axis_label='3PT FG%')\n",
    "\n",
    "# Draw with circle markers\n",
    "pctFig.circle(x='team2P%', y='team3P%', source=gm_stats_cds,\n",
    "              size=12, color='black')\n",
    "\n",
    "# Format the y-axis and x-axis tick labels as percentages\n",
    "pctFig.xaxis[0].formatter = NumeralTickFormatter(format='00.0%')\n",
    "pctFig.yaxis[0].formatter = NumeralTickFormatter(format='00.0%')\n",
    "\n",
    "# Create a figure relating the totals\n",
    "totFig = figure(title='Team Points vs Opponent Points, 2017-18 Regular Season',\n",
    "                height=400, width=400, tools=toolList,\n",
    "                x_axis_label='Team Points', y_axis_label='Opponent Points')\n",
    "\n",
    "# Draw with square markers\n",
    "totFig.square(x='teamPTS', y='opptPTS', source=gm_stats_cds, size=10,\n",
    "              color=dict(field='winLoss', transform=win_loss_mapper))\n",
    "\n",
    "# Create layout\n",
    "grid = gridplot([[pctFig, totFig]])\n",
    "\n",
    "# Visualize\n",
    "show(grid)"
   ]
  }
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