{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "flex_title = \"NBA Scoring (2008)\"\n",
    "flex_orientation = \"rows\"\n",
    "flex_source_code = \"https://github.com/danielfrg/jupyter-flex/blob/master/examples/nba-scoring.ipynb\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"http://datasets.flowingdata.com/ppg2008.csv\"\n",
    "df = pd.read_csv(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.rename(columns={\"Name  \": \"Name\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.set_index(\"Name\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "size=650"
    ]
   },
   "source": [
    "### Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "source = (df-df.mean())/df.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
   "outputs": [],
   "source": [
    "heatmap = go.Heatmap(x=source.columns, y=source.index, z=source, hoverongaps=False, colorscale='Viridis', showscale=False)\n",
    "\n",
    "fig = go.FigureWidget(data=heatmap)\n",
    "\n",
    "margin = go.layout.Margin(l=20, r=20, b=20, t=30)\n",
    "fig.update_layout(margin=margin)\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "footer"
    ]
   },
   "source": [
    "Normalized stats by players"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "size=350"
    ]
   },
   "source": [
    "### Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
   "outputs": [],
   "source": [
    "df.index.name = \"\"\n",
    "df[[\"G\", \"MIN\", \"PTS\"]].iloc[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}