datasets_mpg.ipynb

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    "# Auto MPG Data Set\n",
    "* **[T81-558: Applications of Deep Learning](https://sites.wustl.edu/jeffheaton/t81-558/)**\n",
    "* Dataset provided by [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Auto+MPG)\n",
    "* [Download Here](https://data.heatonresearch.com/data/t81-558/auto-mpg.csv)\n",
    "\n",
    "This is a common dataset that contains measurements for cars and their MPG. The following fields are present:\n",
    "\n",
    "* **mpg** - The [miles per gallon](https://en.wikipedia.org/wiki/Fuel_economy_in_automobiles) for the car.\n",
    "* **cylinders** - The number of [cylinders](https://en.wikipedia.org/wiki/Cylinder_(engine)) in the car.\n",
    "* **displacement** - The engine [displacement](https://en.wikipedia.org/wiki/Engine_displacement).\n",
    "* **horsepower** - The [horsepower](https://en.wikipedia.org/wiki/Horsepower) produced by the car/engine.\t\n",
    "* **weight** - The weight of the car.\n",
    "* **acceleration** - The acceleration of the car.\n",
    "* **year** - The year the car was produced.\n",
    "* **origin** - Where the car was produced, 1=USA, 2=Europe, 3=Asia.\n",
    "* **name** - The name of the car.\n",
    "\n",
    "\n",
    "\n",
    "The following code shows 10 sample rows."
   ]
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>year</th>\n",
       "      <th>origin</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33.0</td>\n",
       "      <td>4</td>\n",
       "      <td>91.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1795</td>\n",
       "      <td>17.4</td>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>honda civic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28.0</td>\n",
       "      <td>4</td>\n",
       "      <td>120.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>2625</td>\n",
       "      <td>18.6</td>\n",
       "      <td>82</td>\n",
       "      <td>1</td>\n",
       "      <td>ford ranger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.0</td>\n",
       "      <td>6</td>\n",
       "      <td>232.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2634</td>\n",
       "      <td>13.0</td>\n",
       "      <td>71</td>\n",
       "      <td>1</td>\n",
       "      <td>amc gremlin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3940</td>\n",
       "      <td>13.2</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>plymouth volare premier v8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>4237</td>\n",
       "      <td>14.5</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>plymouth fury gran sedan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>27.0</td>\n",
       "      <td>4</td>\n",
       "      <td>97.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>2100</td>\n",
       "      <td>16.5</td>\n",
       "      <td>72</td>\n",
       "      <td>3</td>\n",
       "      <td>toyota corolla 1600 (sw)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>24.0</td>\n",
       "      <td>4</td>\n",
       "      <td>140.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>2865</td>\n",
       "      <td>16.4</td>\n",
       "      <td>82</td>\n",
       "      <td>1</td>\n",
       "      <td>ford fairmont futura</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13.0</td>\n",
       "      <td>8</td>\n",
       "      <td>440.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>4735</td>\n",
       "      <td>11.0</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>chrysler new yorker brougham</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>260.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>4060</td>\n",
       "      <td>19.0</td>\n",
       "      <td>77</td>\n",
       "      <td>1</td>\n",
       "      <td>oldsmobile cutlass supreme</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2875</td>\n",
       "      <td>17.0</td>\n",
       "      <td>74</td>\n",
       "      <td>1</td>\n",
       "      <td>ford maverick</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cylinders  displacement  horsepower  weight  acceleration  year  \\\n",
       "0  33.0          4          91.0        53.0    1795          17.4    76   \n",
       "1  28.0          4         120.0        79.0    2625          18.6    82   \n",
       "2  19.0          6         232.0       100.0    2634          13.0    71   \n",
       "3  13.0          8         318.0       150.0    3940          13.2    76   \n",
       "4  14.0          8         318.0       150.0    4237          14.5    73   \n",
       "5  27.0          4          97.0        88.0    2100          16.5    72   \n",
       "6  24.0          4         140.0        92.0    2865          16.4    82   \n",
       "7  13.0          8         440.0       215.0    4735          11.0    73   \n",
       "8  17.0          8         260.0       110.0    4060          19.0    77   \n",
       "9  21.0          6         200.0         NaN    2875          17.0    74   \n",
       "\n",
       "   origin                          name  \n",
       "0       3                   honda civic  \n",
       "1       1                   ford ranger  \n",
       "2       1                   amc gremlin  \n",
       "3       1    plymouth volare premier v8  \n",
       "4       1      plymouth fury gran sedan  \n",
       "5       3      toyota corolla 1600 (sw)  \n",
       "6       1          ford fairmont futura  \n",
       "7       1  chrysler new yorker brougham  \n",
       "8       1    oldsmobile cutlass supreme  \n",
       "9       1                 ford maverick  "
      ]
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "path = \"./data/\"\n",
    "    \n",
    "filename = os.path.join(path,\"auto-mpg.csv\")\n",
    "df = pd.read_csv(filename,na_values=['NA','?'])\n",
    "\n",
    "# Shuffle\n",
    "np.random.seed(42)\n",
    "df = df.reindex(np.random.permutation(df.index))\n",
    "df.reset_index(inplace=True, drop=True)\n",
    "\n",
    "df[0:10]"
   ]
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