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   "source": [
    "Exercises: Fisher's Iris Data\n",
    "==="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": true
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   "source": [
    "#Load the Iris data set\n",
    "import sklearn.datasets\n",
    "iris = sklearn.datasets.load_iris()\n",
    "X    = iris['data']\n",
    "Y    = iris['target']\n",
    "feature_names = iris['feature_names']\n",
    "target_names = iris['target_names']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#How many data cases are there?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#How many data cases are assigned to each target value?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#What is the average value for each of the features over the whole data set?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#What is the average value of each of the features per type?"
   ]
  }
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