Categorical_Continuous.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Categorical and Continuous Data"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "Categorical data: data contain a finite number of categories or distinct groups. Categorical data might not have a logical order. For example, categorical predictors include gender, material type, and payment method. On the other hand, categorical have strings or labels. \n",
        "\nContinuous data: are numeric variables that have an infinite number of values between any two values. A continuous variable can be numeric or date/time. For example, the length of a part or the date and time a payment is received. "
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# fix_yahoo_finance is used to fetch data \n",
        "import fix_yahoo_finance as yf\n",
        "yf.pdr_override()"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# input\n",
        "symbol = 'AMD'\n",
        "start = '2014-01-01'\n",
        "end = '2019-01-01'\n",
        "\n",
        "# Read data \n",
        "dataset = yf.download(symbol,start,end)\n",
        "\n",
        "# View Columns\n",
        "dataset.head()"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  1 of 1 downloaded\n"
          ]
        },
        {
          "output_type": "execute_result",
          "execution_count": 2,
          "data": {
            "text/plain": [
              "            Open  High   Low  Close  Adj Close    Volume\n",
              "Date                                                    \n",
              "2014-01-02  3.85  3.98  3.84   3.95       3.95  20548400\n",
              "2014-01-03  3.98  4.00  3.88   4.00       4.00  22887200\n",
              "2014-01-06  4.01  4.18  3.99   4.13       4.13  42398300\n",
              "2014-01-07  4.19  4.25  4.11   4.18       4.18  42932100\n",
              "2014-01-08  4.23  4.26  4.14   4.18       4.18  30678700"
            ],
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              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
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              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2014-01-02</th>\n",
              "      <td>3.85</td>\n",
              "      <td>3.98</td>\n",
              "      <td>3.84</td>\n",
              "      <td>3.95</td>\n",
              "      <td>3.95</td>\n",
              "      <td>20548400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-03</th>\n",
              "      <td>3.98</td>\n",
              "      <td>4.00</td>\n",
              "      <td>3.88</td>\n",
              "      <td>4.00</td>\n",
              "      <td>4.00</td>\n",
              "      <td>22887200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-06</th>\n",
              "      <td>4.01</td>\n",
              "      <td>4.18</td>\n",
              "      <td>3.99</td>\n",
              "      <td>4.13</td>\n",
              "      <td>4.13</td>\n",
              "      <td>42398300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-07</th>\n",
              "      <td>4.19</td>\n",
              "      <td>4.25</td>\n",
              "      <td>4.11</td>\n",
              "      <td>4.18</td>\n",
              "      <td>4.18</td>\n",
              "      <td>42932100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-08</th>\n",
              "      <td>4.23</td>\n",
              "      <td>4.26</td>\n",
              "      <td>4.14</td>\n",
              "      <td>4.18</td>\n",
              "      <td>4.18</td>\n",
              "      <td>30678700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
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      "execution_count": 2,
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    {
      "cell_type": "code",
      "source": [
        "# Create Data\n",
        "dataset['Open_Close'] = (dataset['Open'] - dataset['Adj Close'])/dataset['Open']\n",
        "dataset['High_Low'] = (dataset['High'] - dataset['Low'])/dataset['Low']\n",
        "dataset['Increase_Decrease'] = np.where(dataset['Volume'].shift(-1) > dataset['Volume'],1,0)\n",
        "dataset['Buy_Sell_on_Open'] = np.where(dataset['Open'].shift(-1) > dataset['Open'],1,0)\n",
        "dataset['Buy_Sell'] = np.where(dataset['Adj Close'].shift(-1) > dataset['Adj Close'],1,0)\n",
        "dataset['Returns'] = dataset['Adj Close'].pct_change()\n",
        "dataset = dataset.dropna()\n",
        "dataset.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": [
              "            Open  High   Low  Close  Adj Close    Volume  Open_Close  \\\n",
              "Date                                                                   \n",
              "2014-01-03  3.98  4.00  3.88   4.00       4.00  22887200   -0.005025   \n",
              "2014-01-06  4.01  4.18  3.99   4.13       4.13  42398300   -0.029925   \n",
              "2014-01-07  4.19  4.25  4.11   4.18       4.18  42932100    0.002387   \n",
              "2014-01-08  4.23  4.26  4.14   4.18       4.18  30678700    0.011820   \n",
              "2014-01-09  4.20  4.23  4.05   4.09       4.09  30667600    0.026190   \n",
              "\n",
              "            High_Low  Increase_Decrease  Buy_Sell_on_Open  Buy_Sell   Returns  \n",
              "Date                                                                           \n",
              "2014-01-03  0.030928                  1                 1         1  0.012658  \n",
              "2014-01-06  0.047619                  1                 1         1  0.032500  \n",
              "2014-01-07  0.034063                  0                 1         0  0.012107  \n",
              "2014-01-08  0.028986                  0                 0         0  0.000000  \n",
              "2014-01-09  0.044444                  0                 0         1 -0.021531  "
            ],
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              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Open_Close</th>\n",
              "      <th>High_Low</th>\n",
              "      <th>Increase_Decrease</th>\n",
              "      <th>Buy_Sell_on_Open</th>\n",
              "      <th>Buy_Sell</th>\n",
              "      <th>Returns</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2014-01-03</th>\n",
              "      <td>3.98</td>\n",
              "      <td>4.00</td>\n",
              "      <td>3.88</td>\n",
              "      <td>4.00</td>\n",
              "      <td>4.00</td>\n",
              "      <td>22887200</td>\n",
              "      <td>-0.005025</td>\n",
              "      <td>0.030928</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.012658</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-06</th>\n",
              "      <td>4.01</td>\n",
              "      <td>4.18</td>\n",
              "      <td>3.99</td>\n",
              "      <td>4.13</td>\n",
              "      <td>4.13</td>\n",
              "      <td>42398300</td>\n",
              "      <td>-0.029925</td>\n",
              "      <td>0.047619</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.032500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-07</th>\n",
              "      <td>4.19</td>\n",
              "      <td>4.25</td>\n",
              "      <td>4.11</td>\n",
              "      <td>4.18</td>\n",
              "      <td>4.18</td>\n",
              "      <td>42932100</td>\n",
              "      <td>0.002387</td>\n",
              "      <td>0.034063</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.012107</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-08</th>\n",
              "      <td>4.23</td>\n",
              "      <td>4.26</td>\n",
              "      <td>4.14</td>\n",
              "      <td>4.18</td>\n",
              "      <td>4.18</td>\n",
              "      <td>30678700</td>\n",
              "      <td>0.011820</td>\n",
              "      <td>0.028986</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-09</th>\n",
              "      <td>4.20</td>\n",
              "      <td>4.23</td>\n",
              "      <td>4.05</td>\n",
              "      <td>4.09</td>\n",
              "      <td>4.09</td>\n",
              "      <td>30667600</td>\n",
              "      <td>0.026190</td>\n",
              "      <td>0.044444</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.021531</td>\n",
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          },
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      ],
      "execution_count": 3,
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    },
    {
      "cell_type": "code",
      "source": [
        "# Create Labels string\n",
        "dataset['Increase_Decrease_L'] = np.where(dataset['Volume'].shift(-1) > dataset['Volume'],'Increase','Decrease')\n",
        "dataset['Buy_Sell_on_Open_L'] = np.where(dataset['Open'].shift(-1) > dataset['Open'],'Buy','Sell')\n",
        "dataset['Buy_Sell_L'] = np.where(dataset['Adj Close'].shift(-1) > dataset['Adj Close'],'Buy','Sell')\n",
        "dataset.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/plain": [
              "            Open  High   Low  Close  Adj Close    Volume  Open_Close  \\\n",
              "Date                                                                   \n",
              "2014-01-03  3.98  4.00  3.88   4.00       4.00  22887200   -0.005025   \n",
              "2014-01-06  4.01  4.18  3.99   4.13       4.13  42398300   -0.029925   \n",
              "2014-01-07  4.19  4.25  4.11   4.18       4.18  42932100    0.002387   \n",
              "2014-01-08  4.23  4.26  4.14   4.18       4.18  30678700    0.011820   \n",
              "2014-01-09  4.20  4.23  4.05   4.09       4.09  30667600    0.026190   \n",
              "\n",
              "            High_Low  Increase_Decrease  Buy_Sell_on_Open  Buy_Sell   Returns  \\\n",
              "Date                                                                            \n",
              "2014-01-03  0.030928                  1                 1         1  0.012658   \n",
              "2014-01-06  0.047619                  1                 1         1  0.032500   \n",
              "2014-01-07  0.034063                  0                 1         0  0.012107   \n",
              "2014-01-08  0.028986                  0                 0         0  0.000000   \n",
              "2014-01-09  0.044444                  0                 0         1 -0.021531   \n",
              "\n",
              "           Increase_Decrease_L Buy_Sell_on_Open_L Buy_Sell_L  \n",
              "Date                                                          \n",
              "2014-01-03            Increase                Buy        Buy  \n",
              "2014-01-06            Increase                Buy        Buy  \n",
              "2014-01-07            Decrease                Buy       Sell  \n",
              "2014-01-08            Decrease               Sell       Sell  \n",
              "2014-01-09            Decrease               Sell        Buy  "
            ],
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              "      <th>Open</th>\n",
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              "      <th>Low</th>\n",
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              "      <th>Buy_Sell_L</th>\n",
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              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th>2014-01-03</th>\n",
              "      <td>3.98</td>\n",
              "      <td>4.00</td>\n",
              "      <td>3.88</td>\n",
              "      <td>4.00</td>\n",
              "      <td>4.00</td>\n",
              "      <td>22887200</td>\n",
              "      <td>-0.005025</td>\n",
              "      <td>0.030928</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.012658</td>\n",
              "      <td>Increase</td>\n",
              "      <td>Buy</td>\n",
              "      <td>Buy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-06</th>\n",
              "      <td>4.01</td>\n",
              "      <td>4.18</td>\n",
              "      <td>3.99</td>\n",
              "      <td>4.13</td>\n",
              "      <td>4.13</td>\n",
              "      <td>42398300</td>\n",
              "      <td>-0.029925</td>\n",
              "      <td>0.047619</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.032500</td>\n",
              "      <td>Increase</td>\n",
              "      <td>Buy</td>\n",
              "      <td>Buy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-07</th>\n",
              "      <td>4.19</td>\n",
              "      <td>4.25</td>\n",
              "      <td>4.11</td>\n",
              "      <td>4.18</td>\n",
              "      <td>4.18</td>\n",
              "      <td>42932100</td>\n",
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              "      <td>0.034063</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.012107</td>\n",
              "      <td>Decrease</td>\n",
              "      <td>Buy</td>\n",
              "      <td>Sell</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-08</th>\n",
              "      <td>4.23</td>\n",
              "      <td>4.26</td>\n",
              "      <td>4.14</td>\n",
              "      <td>4.18</td>\n",
              "      <td>4.18</td>\n",
              "      <td>30678700</td>\n",
              "      <td>0.011820</td>\n",
              "      <td>0.028986</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>Decrease</td>\n",
              "      <td>Sell</td>\n",
              "      <td>Sell</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014-01-09</th>\n",
              "      <td>4.20</td>\n",
              "      <td>4.23</td>\n",
              "      <td>4.05</td>\n",
              "      <td>4.09</td>\n",
              "      <td>4.09</td>\n",
              "      <td>30667600</td>\n",
              "      <td>0.026190</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.021531</td>\n",
              "      <td>Decrease</td>\n",
              "      <td>Sell</td>\n",
              "      <td>Buy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ]
          },
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      ],
      "execution_count": 4,
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    },
    {
      "cell_type": "code",
      "source": [
        "dataset.info()"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 1257 entries, 2014-01-03 to 2018-12-31\n",
            "Data columns (total 15 columns):\n",
            "Open                   1257 non-null float64\n",
            "High                   1257 non-null float64\n",
            "Low                    1257 non-null float64\n",
            "Close                  1257 non-null float64\n",
            "Adj Close              1257 non-null float64\n",
            "Volume                 1257 non-null int32\n",
            "Open_Close             1257 non-null float64\n",
            "High_Low               1257 non-null float64\n",
            "Increase_Decrease      1257 non-null int32\n",
            "Buy_Sell_on_Open       1257 non-null int32\n",
            "Buy_Sell               1257 non-null int32\n",
            "Returns                1257 non-null float64\n",
            "Increase_Decrease_L    1257 non-null object\n",
            "Buy_Sell_on_Open_L     1257 non-null object\n",
            "Buy_Sell_L             1257 non-null object\n",
            "dtypes: float64(8), int32(4), object(3)\n",
            "memory usage: 137.5+ KB\n"
          ]
        }
      ],
      "execution_count": 5,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# separating the features and labels\n",
        "\n",
        "data_feat = dataset.drop(columns=[\"Buy_Sell\"],axis=1)\n",
        "data_label = dataset[\"Buy_Sell\"]"
      ],
      "outputs": [],
      "execution_count": 8,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# first just take a look at all the columns\n",
        "list(data_feat.columns)"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 9,
          "data": {
            "text/plain": [
              "['Open',\n",
              " 'High',\n",
              " 'Low',\n",
              " 'Close',\n",
              " 'Adj Close',\n",
              " 'Volume',\n",
              " 'Open_Close',\n",
              " 'High_Low',\n",
              " 'Increase_Decrease',\n",
              " 'Buy_Sell_on_Open',\n",
              " 'Returns',\n",
              " 'Increase_Decrease_L',\n",
              " 'Buy_Sell_on_Open_L',\n",
              " 'Buy_Sell_L']"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 9,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "categorical_columns = [col for col in data_feat.columns if len(data_feat[col].unique())==2 or data_feat[col].dtype=='O']"
      ],
      "outputs": [],
      "execution_count": 10,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "continuous_columns = [col for col in data_feat.columns if len(data_feat[col].unique())>2 and (data_feat[col].dtype=='int64' or data_feat[col].dtype=='float64')]"
      ],
      "outputs": [],
      "execution_count": 11,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Categorical Variables:\")\n",
        "print(\"categorical columns : \", categorical_columns)\n",
        "print('-'*50)\n",
        "print(\"Continuous Variables:\")\n",
        "print(\"continuous columns : \", continuous_columns)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Categorical Variables:\n",
            "categorical columns :  ['Increase_Decrease', 'Buy_Sell_on_Open', 'Increase_Decrease_L', 'Buy_Sell_on_Open_L', 'Buy_Sell_L']\n",
            "--------------------------------------------------\n",
            "Continuous Variables:\n",
            "continuous columns :  ['Open', 'High', 'Low', 'Close', 'Adj Close', 'Open_Close', 'High_Low', 'Returns']\n"
          ]
        }
      ],
      "execution_count": 13,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    }
  ],
  "metadata": {
    "kernel_info": {
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "pygments_lexer": "ipython3",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "version": "3.5.5",
      "mimetype": "text/x-python",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    },
    "kernelspec": {
      "name": "python3",
      "language": "python",
      "display_name": "Python 3"
    },
    "nteract": {
      "version": "0.12.2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}