visualization/1-viz-intro.ipynb

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   "source": [
    "# Visualizing Data\n",
    "\n",
    "Here we will use two libraries\n",
    "- matplotlib : a very capable python graph library\n",
    "- Seaborn : a high level library built on top of matplotlib.  Seaborn aims to give 'pretty' graphs right out of the box \n"
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   "source": [
    "# imports\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns #seaborn produces pretty nice graphs!"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "## Boxplot"
   ]
  },
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   "source": [
    "salaries = np.array([22, 25, 30, 35, 40, 42, 45, 50, 55, 60, 65, 70])\n",
    "\n",
    "## TODO : do a boxplot of salaries\n",
    "## Hint : plot.boxplot(data)\n",
    "plt.???(salaries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "outputs": [],
   "source": [
    "## seaborn plot\n",
    "sns.boxplot(data=???)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Histograms"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "salaries = np.array([22, 25, 30, 35, 40, 42, 45, 50, 55, 60, 65, 70])\n",
    "\n",
    "## TODO : histogram\n",
    "## HINT : plt.hist\n",
    "plt.???(salaries, rwidth=0.7, bins=5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "\n",
    "## seaborn\n",
    "sns.distplot(salaries, bins=5, kde=False, rug=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   },
   "outputs": [],
   "source": [
    "bills = np.array([50,30,60,40,65,20,10,15,25,35])\n",
    "tips= np.array([12,7,13,8,15,5,2,2,3,4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   },
   "outputs": [],
   "source": [
    "## TODO : plot bill vs. tips\n",
    "## Hint : plot.scatter (x axis data,   y axis data)\n",
    "\n",
    "plt.???(bills, tips)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   "outputs": [],
   "source": [
    "## TODO : add labels\n",
    "##   X-axis :  bill\n",
    "##   Y-axis : tip\n",
    "\n",
    "plt.xlabel(\"bill amount\")\n",
    "plt.ylabel(\"tip\")\n",
    "plt.???(bills, tips)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
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   },
   "outputs": [],
   "source": [
    "## Seaborn \n",
    "sns.stripplot(x=bills, y=tips)"
   ]
  }
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