DataProcessing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c08d2557",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "e28341a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Declare filepath of dataset\n",
    "filepath = '/Users/christopheralpert/Documents/Eductation/CompFinance/CFRM523/rep_project/data/US Wheat Futures Historical Data.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "c2045cfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load Data\n",
    "df = load_data(filepath)\n",
    "\n",
    "#First change 'Price' to 'Close'\n",
    "df.rename(columns={'Price': 'Close'}, inplace=True)\n",
    "\n",
    "#Reorder data so oldest is at top, newest is at bottom\n",
    "df = df.iloc[::-1].reset_index(drop=True)\n",
    "\n",
    "#Clean Data\n",
    "df.fillna(method='ffill', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "d299c766",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Vol.</th>\n",
       "      <th>Change %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02/01/1995</td>\n",
       "      <td>370.50</td>\n",
       "      <td>373.50</td>\n",
       "      <td>376.00</td>\n",
       "      <td>370.25</td>\n",
       "      <td>7.51K</td>\n",
       "      <td>-0.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02/02/1995</td>\n",
       "      <td>376.75</td>\n",
       "      <td>369.00</td>\n",
       "      <td>377.00</td>\n",
       "      <td>367.50</td>\n",
       "      <td>11.62K</td>\n",
       "      <td>1.69%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02/03/1995</td>\n",
       "      <td>372.25</td>\n",
       "      <td>376.50</td>\n",
       "      <td>377.25</td>\n",
       "      <td>370.50</td>\n",
       "      <td>9.50K</td>\n",
       "      <td>-1.19%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02/06/1995</td>\n",
       "      <td>369.75</td>\n",
       "      <td>372.50</td>\n",
       "      <td>374.75</td>\n",
       "      <td>369.00</td>\n",
       "      <td>4.57K</td>\n",
       "      <td>-0.67%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>02/07/1995</td>\n",
       "      <td>373.25</td>\n",
       "      <td>370.00</td>\n",
       "      <td>374.00</td>\n",
       "      <td>369.75</td>\n",
       "      <td>5.50K</td>\n",
       "      <td>0.95%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>02/13/2014</td>\n",
       "      <td>594.50</td>\n",
       "      <td>586.38</td>\n",
       "      <td>596.63</td>\n",
       "      <td>585.38</td>\n",
       "      <td>38.27K</td>\n",
       "      <td>1.47%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>02/14/2014</td>\n",
       "      <td>597.50</td>\n",
       "      <td>594.88</td>\n",
       "      <td>602.88</td>\n",
       "      <td>594.50</td>\n",
       "      <td>38.27K</td>\n",
       "      <td>0.50%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>02/18/2014</td>\n",
       "      <td>612.13</td>\n",
       "      <td>599.25</td>\n",
       "      <td>613.13</td>\n",
       "      <td>598.88</td>\n",
       "      <td>38.27K</td>\n",
       "      <td>2.45%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>02/19/2014</td>\n",
       "      <td>620.38</td>\n",
       "      <td>611.88</td>\n",
       "      <td>620.38</td>\n",
       "      <td>609.88</td>\n",
       "      <td>38.27K</td>\n",
       "      <td>1.35%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>02/20/2014</td>\n",
       "      <td>615.88</td>\n",
       "      <td>618.88</td>\n",
       "      <td>620.75</td>\n",
       "      <td>611.63</td>\n",
       "      <td>38.27K</td>\n",
       "      <td>-0.73%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date   Close    Open    High     Low    Vol. Change %\n",
       "0     02/01/1995  370.50  373.50  376.00  370.25   7.51K   -0.80%\n",
       "1     02/02/1995  376.75  369.00  377.00  367.50  11.62K    1.69%\n",
       "2     02/03/1995  372.25  376.50  377.25  370.50   9.50K   -1.19%\n",
       "3     02/06/1995  369.75  372.50  374.75  369.00   4.57K   -0.67%\n",
       "4     02/07/1995  373.25  370.00  374.00  369.75   5.50K    0.95%\n",
       "...          ...     ...     ...     ...     ...     ...      ...\n",
       "4995  02/13/2014  594.50  586.38  596.63  585.38  38.27K    1.47%\n",
       "4996  02/14/2014  597.50  594.88  602.88  594.50  38.27K    0.50%\n",
       "4997  02/18/2014  612.13  599.25  613.13  598.88  38.27K    2.45%\n",
       "4998  02/19/2014  620.38  611.88  620.38  609.88  38.27K    1.35%\n",
       "4999  02/20/2014  615.88  618.88  620.75  611.63  38.27K   -0.73%\n",
       "\n",
       "[5000 rows x 7 columns]"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Inspect\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "a289f6ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Date         object\n",
      "Close       float64\n",
      "Open        float64\n",
      "High        float64\n",
      "Low         float64\n",
      "Vol.        float64\n",
      "Change %    float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "#Before feature engineering, let's convert all types to float or int. Create separate columns for 'Date' and drop 'Date'\n",
    "\n",
    "# Convert 'Close' column to numeric, coercing errors\n",
    "df['Close'] = pd.to_numeric(df['Close'], errors='coerce')\n",
    "\n",
    "# You might have NaNs where there were non-numeric strings, fill them if necessary\n",
    "df['Close'].fillna(method='ffill', inplace=True)  # Forward fill to handle NaNs, or choose another method\n",
    "\n",
    "# Convert 'Date' column to datetime format\n",
    "#df['Date'] = pd.to_datetime(df['Date'], errors='coerce')\n",
    "\n",
    "# Now you can extract datetime components\n",
    "#df['Year'] = df['Date'].dt.year\n",
    "#df['Month'] = df['Date'].dt.month\n",
    "#df['Day'] = df['Date'].dt.day\n",
    "#df['day_of_week'] = df['Date'].dt.dayofweek\n",
    "# Now drop the original 'Date' column\n",
    "#df.drop('Date', axis=1, inplace=True)\n",
    "\n",
    "\n",
    "# Explicitly convert to string, replace commas, and convert to float\n",
    "def clean_numeric(column):\n",
    "    # Convert to string first to ensure .str operations can be performed\n",
    "    column = column.astype(str)\n",
    "    # Replace commas and convert to float\n",
    "    column = column.str.replace(',', '')\n",
    "    return pd.to_numeric(column, errors='coerce')\n",
    "\n",
    "# Apply this function to the columns known to contain numeric strings with commas\n",
    "columns_to_clean = ['Open','High','Low']  # Extend this list based on your actual data\n",
    "for col in columns_to_clean:\n",
    "    df[col] = clean_numeric(df[col])\n",
    "\n",
    "\n",
    "#Convert\n",
    "def convert_volume(vol):\n",
    "    # Ensure vol is a string before checking for 'K' or 'M'\n",
    "    vol = str(vol)\n",
    "    if vol == '-' or vol == 'nan':  # Handle both '-' and unexpected NaN values represented as strings\n",
    "        return np.nan\n",
    "    elif 'K' in vol:\n",
    "        return float(vol.replace('K', '')) * 1e3\n",
    "    elif 'M' in vol:\n",
    "        return float(vol.replace('M', '')) * 1e6\n",
    "    else:\n",
    "        try:\n",
    "            return float(vol)  # Handle numbers as strings or normal numbers\n",
    "        except ValueError:\n",
    "            return np.nan  # In case of any other unexpected string that cannot be converted\n",
    "\n",
    "# Apply this function to the 'Vol.' column\n",
    "df['Vol.'] = df['Vol.'].apply(convert_volume)\n",
    "\n",
    "# Option to fill NaN values, choose one:\n",
    "# df['Vol.'] = df['Vol.'].fillna(0)  # Replace NaN with 0\n",
    "df['Vol.'] = df['Vol.'].fillna(df['Vol.'].mean())  # Replace NaN with mean\n",
    "\n",
    "\n",
    "#Drop the % sign from 'change %' and convert to float\n",
    "\n",
    "# Convert entire 'Change %' column to string, handling potential NaN values\n",
    "df['Change %'] = df['Change %'].astype(str)\n",
    "\n",
    "# Strip the '%' character and convert to float, dividing by 100 to turn into a decimal\n",
    "df['Change %'] = df['Change %'].str.rstrip('%').astype('float') / 100.0\n",
    "\n",
    "# Check for entries that were originally NaN and set them back to NaN if they were converted to strings\n",
    "df['Change %'] = df['Change %'].replace(-0.01, np.nan)  # Assuming '-0.01' results from empty entries turned into '-%'\n",
    "\n",
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "eb48a067",
   "metadata": {},
   "outputs": [],
   "source": [
    "#### FEATURE ENGINEERING ######\n",
    "\n",
    "#Create a returns feature for three different periods\n",
    "\n",
    "#Run a simple for loop which calculates returns\n",
    "#Define 3 periods of interest: daily, monthly and quarterly\n",
    "\n",
    "periods = [1, 21, 63]\n",
    "for period in periods:\n",
    "        df[f'return_{period}d'] = df['Close'].pct_change(periods=period).fillna(0)\n",
    "        \n",
    "\n",
    "#Create a MACD feature\n",
    "\n",
    "span1=12\n",
    "span2=26\n",
    "signal=9\n",
    "\n",
    "exp1 = df['Close'].ewm(span=span1, adjust=False).mean()\n",
    "exp2 = df['Close'].ewm(span=span2, adjust=False).mean()\n",
    "df['macd'] = exp1 - exp2\n",
    "df['macd_signal'] = df['macd'].ewm(span=signal, adjust=False).mean()\n",
    "df['macd_hist'] = df['macd'] - df['macd_signal']\n",
    "\n",
    "#Create a volatility feature\n",
    "window=10\n",
    "df['volatility'] = df['return_1d'].rolling(window=window).std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "fd2e4686",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create a Target column\n",
    "\n",
    "# Shift the 'Price' column by -1 to compare the next day's closing price to the current day\n",
    "df['Target'] = (df['Close'].shift(-1) > df['Close']).astype(int)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "7df77296",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Vol.</th>\n",
       "      <th>Change %</th>\n",
       "      <th>return_1d</th>\n",
       "      <th>return_21d</th>\n",
       "      <th>return_63d</th>\n",
       "      <th>macd</th>\n",
       "      <th>macd_signal</th>\n",
       "      <th>macd_hist</th>\n",
       "      <th>volatility</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02/01/1995</td>\n",
       "      <td>-0.507140</td>\n",
       "      <td>-0.486610</td>\n",
       "      <td>-0.497744</td>\n",
       "      <td>-0.479235</td>\n",
       "      <td>-0.387881</td>\n",
       "      <td>-0.371484</td>\n",
       "      <td>-0.015586</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>-0.026005</td>\n",
       "      <td>-0.027676</td>\n",
       "      <td>-0.000001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02/02/1995</td>\n",
       "      <td>-0.474837</td>\n",
       "      <td>-0.509443</td>\n",
       "      <td>-0.492779</td>\n",
       "      <td>-0.493480</td>\n",
       "      <td>-0.298038</td>\n",
       "      <td>0.734361</td>\n",
       "      <td>0.751372</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.017229</td>\n",
       "      <td>-0.018474</td>\n",
       "      <td>0.112992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02/03/1995</td>\n",
       "      <td>-0.498095</td>\n",
       "      <td>-0.471389</td>\n",
       "      <td>-0.491538</td>\n",
       "      <td>-0.477940</td>\n",
       "      <td>-0.344380</td>\n",
       "      <td>-0.544688</td>\n",
       "      <td>-0.558635</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.019481</td>\n",
       "      <td>-0.010632</td>\n",
       "      <td>0.096278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02/06/1995</td>\n",
       "      <td>-0.511016</td>\n",
       "      <td>-0.491684</td>\n",
       "      <td>-0.503950</td>\n",
       "      <td>-0.485710</td>\n",
       "      <td>-0.452148</td>\n",
       "      <td>-0.313749</td>\n",
       "      <td>-0.320927</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.003433</td>\n",
       "      <td>-0.007775</td>\n",
       "      <td>0.035081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>02/07/1995</td>\n",
       "      <td>-0.492927</td>\n",
       "      <td>-0.504369</td>\n",
       "      <td>-0.507674</td>\n",
       "      <td>-0.481825</td>\n",
       "      <td>-0.431818</td>\n",
       "      <td>0.405716</td>\n",
       "      <td>0.414782</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.014736</td>\n",
       "      <td>-0.003083</td>\n",
       "      <td>0.057604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>02/13/2014</td>\n",
       "      <td>0.650587</td>\n",
       "      <td>0.593536</td>\n",
       "      <td>0.597665</td>\n",
       "      <td>0.635127</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.636656</td>\n",
       "      <td>0.653340</td>\n",
       "      <td>0.234105</td>\n",
       "      <td>-0.650730</td>\n",
       "      <td>-0.113907</td>\n",
       "      <td>-0.588542</td>\n",
       "      <td>1.434463</td>\n",
       "      <td>-0.499596</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>02/14/2014</td>\n",
       "      <td>0.666093</td>\n",
       "      <td>0.636665</td>\n",
       "      <td>0.628696</td>\n",
       "      <td>0.682368</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.205865</td>\n",
       "      <td>0.213843</td>\n",
       "      <td>0.542856</td>\n",
       "      <td>-0.607582</td>\n",
       "      <td>0.008087</td>\n",
       "      <td>-0.469112</td>\n",
       "      <td>1.466400</td>\n",
       "      <td>-0.507162</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>02/18/2014</td>\n",
       "      <td>0.741707</td>\n",
       "      <td>0.658838</td>\n",
       "      <td>0.679586</td>\n",
       "      <td>0.705056</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>1.071888</td>\n",
       "      <td>1.097647</td>\n",
       "      <td>0.735365</td>\n",
       "      <td>-0.437462</td>\n",
       "      <td>0.204482</td>\n",
       "      <td>-0.331765</td>\n",
       "      <td>1.686395</td>\n",
       "      <td>-0.432448</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>02/19/2014</td>\n",
       "      <td>0.784346</td>\n",
       "      <td>0.722922</td>\n",
       "      <td>0.715582</td>\n",
       "      <td>0.762036</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.583362</td>\n",
       "      <td>0.597173</td>\n",
       "      <td>1.104172</td>\n",
       "      <td>-0.427007</td>\n",
       "      <td>0.412795</td>\n",
       "      <td>-0.177547</td>\n",
       "      <td>1.893541</td>\n",
       "      <td>-0.801462</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>02/20/2014</td>\n",
       "      <td>0.761088</td>\n",
       "      <td>0.758440</td>\n",
       "      <td>0.717419</td>\n",
       "      <td>0.771100</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>-0.340396</td>\n",
       "      <td>-0.345374</td>\n",
       "      <td>1.034993</td>\n",
       "      <td>-0.439333</td>\n",
       "      <td>0.539875</td>\n",
       "      <td>-0.027124</td>\n",
       "      <td>1.846952</td>\n",
       "      <td>-0.731737</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date     Close      Open      High       Low      Vol.  Change %  \\\n",
       "0     02/01/1995 -0.507140 -0.486610 -0.497744 -0.479235 -0.387881 -0.371484   \n",
       "1     02/02/1995 -0.474837 -0.509443 -0.492779 -0.493480 -0.298038  0.734361   \n",
       "2     02/03/1995 -0.498095 -0.471389 -0.491538 -0.477940 -0.344380 -0.544688   \n",
       "3     02/06/1995 -0.511016 -0.491684 -0.503950 -0.485710 -0.452148 -0.313749   \n",
       "4     02/07/1995 -0.492927 -0.504369 -0.507674 -0.481825 -0.431818  0.405716   \n",
       "...          ...       ...       ...       ...       ...       ...       ...   \n",
       "4995  02/13/2014  0.650587  0.593536  0.597665  0.635127  0.284517  0.636656   \n",
       "4996  02/14/2014  0.666093  0.636665  0.628696  0.682368  0.284517  0.205865   \n",
       "4997  02/18/2014  0.741707  0.658838  0.679586  0.705056  0.284517  1.071888   \n",
       "4998  02/19/2014  0.784346  0.722922  0.715582  0.762036  0.284517  0.583362   \n",
       "4999  02/20/2014  0.761088  0.758440  0.717419  0.771100  0.284517 -0.340396   \n",
       "\n",
       "      return_1d  return_21d  return_63d      macd  macd_signal  macd_hist  \\\n",
       "0     -0.015586   -0.064437   -0.113838 -0.026005    -0.027676  -0.000001   \n",
       "1      0.751372   -0.064437   -0.113838  0.017229    -0.018474   0.112992   \n",
       "2     -0.558635   -0.064437   -0.113838  0.019481    -0.010632   0.096278   \n",
       "3     -0.320927   -0.064437   -0.113838  0.003433    -0.007775   0.035081   \n",
       "4      0.414782   -0.064437   -0.113838  0.014736    -0.003083   0.057604   \n",
       "...         ...         ...         ...       ...          ...        ...   \n",
       "4995   0.653340    0.234105   -0.650730 -0.113907    -0.588542   1.434463   \n",
       "4996   0.213843    0.542856   -0.607582  0.008087    -0.469112   1.466400   \n",
       "4997   1.097647    0.735365   -0.437462  0.204482    -0.331765   1.686395   \n",
       "4998   0.597173    1.104172   -0.427007  0.412795    -0.177547   1.893541   \n",
       "4999  -0.345374    1.034993   -0.439333  0.539875    -0.027124   1.846952   \n",
       "\n",
       "      volatility  Target  \n",
       "0            NaN       1  \n",
       "1            NaN       0  \n",
       "2            NaN       0  \n",
       "3            NaN       1  \n",
       "4            NaN       0  \n",
       "...          ...     ...  \n",
       "4995   -0.499596       1  \n",
       "4996   -0.507162       1  \n",
       "4997   -0.432448       1  \n",
       "4998   -0.801462       0  \n",
       "4999   -0.731737       0  \n",
       "\n",
       "[5000 rows x 15 columns]"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Inspect and verify target is accurate\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "ce15e381",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Normalize the features\n",
    "scaler = StandardScaler()\n",
    "#if 'Date' in df.columns:\n",
    "    #df['Date'] = pd.to_datetime(df['Date'])\n",
    "    #df['Month'] = df['Date'].dt.month\n",
    "    #df['Day'] = df['Date'].dt.day\n",
    "    #df['Weekday'] = df['Date'].dt.weekday\n",
    "    #df.drop('Date', axis=1, inplace=True)  # Optional: remove if not needed for modeling\n",
    "\n",
    "#Select only numerical columns and exclude the target column for scaling\n",
    "features = df.columns[(df.dtypes == 'float64') | (df.dtypes == 'int64')]\n",
    "features = (features[features != 'Target'])# & (features[features != 'Date'])   # Exclude the target column from scaling\n",
    "\n",
    "df[features] = scaler.fit_transform(df[features])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "bc3be765",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Vol.</th>\n",
       "      <th>Change %</th>\n",
       "      <th>return_1d</th>\n",
       "      <th>return_21d</th>\n",
       "      <th>return_63d</th>\n",
       "      <th>macd</th>\n",
       "      <th>macd_signal</th>\n",
       "      <th>macd_hist</th>\n",
       "      <th>volatility</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02/01/1995</td>\n",
       "      <td>-0.507140</td>\n",
       "      <td>-0.486610</td>\n",
       "      <td>-0.497744</td>\n",
       "      <td>-0.479235</td>\n",
       "      <td>-0.387881</td>\n",
       "      <td>-0.371484</td>\n",
       "      <td>-0.015586</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>-0.026005</td>\n",
       "      <td>-0.027676</td>\n",
       "      <td>-0.000001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02/02/1995</td>\n",
       "      <td>-0.474837</td>\n",
       "      <td>-0.509443</td>\n",
       "      <td>-0.492779</td>\n",
       "      <td>-0.493480</td>\n",
       "      <td>-0.298038</td>\n",
       "      <td>0.734361</td>\n",
       "      <td>0.751372</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.017229</td>\n",
       "      <td>-0.018474</td>\n",
       "      <td>0.112992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02/03/1995</td>\n",
       "      <td>-0.498095</td>\n",
       "      <td>-0.471389</td>\n",
       "      <td>-0.491538</td>\n",
       "      <td>-0.477940</td>\n",
       "      <td>-0.344380</td>\n",
       "      <td>-0.544688</td>\n",
       "      <td>-0.558635</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.019481</td>\n",
       "      <td>-0.010632</td>\n",
       "      <td>0.096278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02/06/1995</td>\n",
       "      <td>-0.511016</td>\n",
       "      <td>-0.491684</td>\n",
       "      <td>-0.503950</td>\n",
       "      <td>-0.485710</td>\n",
       "      <td>-0.452148</td>\n",
       "      <td>-0.313749</td>\n",
       "      <td>-0.320927</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.003433</td>\n",
       "      <td>-0.007775</td>\n",
       "      <td>0.035081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>02/07/1995</td>\n",
       "      <td>-0.492927</td>\n",
       "      <td>-0.504369</td>\n",
       "      <td>-0.507674</td>\n",
       "      <td>-0.481825</td>\n",
       "      <td>-0.431818</td>\n",
       "      <td>0.405716</td>\n",
       "      <td>0.414782</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.014736</td>\n",
       "      <td>-0.003083</td>\n",
       "      <td>0.057604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>02/13/2014</td>\n",
       "      <td>0.650587</td>\n",
       "      <td>0.593536</td>\n",
       "      <td>0.597665</td>\n",
       "      <td>0.635127</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.636656</td>\n",
       "      <td>0.653340</td>\n",
       "      <td>0.234105</td>\n",
       "      <td>-0.650730</td>\n",
       "      <td>-0.113907</td>\n",
       "      <td>-0.588542</td>\n",
       "      <td>1.434463</td>\n",
       "      <td>-0.499596</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>02/14/2014</td>\n",
       "      <td>0.666093</td>\n",
       "      <td>0.636665</td>\n",
       "      <td>0.628696</td>\n",
       "      <td>0.682368</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.205865</td>\n",
       "      <td>0.213843</td>\n",
       "      <td>0.542856</td>\n",
       "      <td>-0.607582</td>\n",
       "      <td>0.008087</td>\n",
       "      <td>-0.469112</td>\n",
       "      <td>1.466400</td>\n",
       "      <td>-0.507162</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>02/18/2014</td>\n",
       "      <td>0.741707</td>\n",
       "      <td>0.658838</td>\n",
       "      <td>0.679586</td>\n",
       "      <td>0.705056</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>1.071888</td>\n",
       "      <td>1.097647</td>\n",
       "      <td>0.735365</td>\n",
       "      <td>-0.437462</td>\n",
       "      <td>0.204482</td>\n",
       "      <td>-0.331765</td>\n",
       "      <td>1.686395</td>\n",
       "      <td>-0.432448</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>02/19/2014</td>\n",
       "      <td>0.784346</td>\n",
       "      <td>0.722922</td>\n",
       "      <td>0.715582</td>\n",
       "      <td>0.762036</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.583362</td>\n",
       "      <td>0.597173</td>\n",
       "      <td>1.104172</td>\n",
       "      <td>-0.427007</td>\n",
       "      <td>0.412795</td>\n",
       "      <td>-0.177547</td>\n",
       "      <td>1.893541</td>\n",
       "      <td>-0.801462</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>02/20/2014</td>\n",
       "      <td>0.761088</td>\n",
       "      <td>0.758440</td>\n",
       "      <td>0.717419</td>\n",
       "      <td>0.771100</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>-0.340396</td>\n",
       "      <td>-0.345374</td>\n",
       "      <td>1.034993</td>\n",
       "      <td>-0.439333</td>\n",
       "      <td>0.539875</td>\n",
       "      <td>-0.027124</td>\n",
       "      <td>1.846952</td>\n",
       "      <td>-0.731737</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date     Close      Open      High       Low      Vol.  Change %  \\\n",
       "0     02/01/1995 -0.507140 -0.486610 -0.497744 -0.479235 -0.387881 -0.371484   \n",
       "1     02/02/1995 -0.474837 -0.509443 -0.492779 -0.493480 -0.298038  0.734361   \n",
       "2     02/03/1995 -0.498095 -0.471389 -0.491538 -0.477940 -0.344380 -0.544688   \n",
       "3     02/06/1995 -0.511016 -0.491684 -0.503950 -0.485710 -0.452148 -0.313749   \n",
       "4     02/07/1995 -0.492927 -0.504369 -0.507674 -0.481825 -0.431818  0.405716   \n",
       "...          ...       ...       ...       ...       ...       ...       ...   \n",
       "4995  02/13/2014  0.650587  0.593536  0.597665  0.635127  0.284517  0.636656   \n",
       "4996  02/14/2014  0.666093  0.636665  0.628696  0.682368  0.284517  0.205865   \n",
       "4997  02/18/2014  0.741707  0.658838  0.679586  0.705056  0.284517  1.071888   \n",
       "4998  02/19/2014  0.784346  0.722922  0.715582  0.762036  0.284517  0.583362   \n",
       "4999  02/20/2014  0.761088  0.758440  0.717419  0.771100  0.284517 -0.340396   \n",
       "\n",
       "      return_1d  return_21d  return_63d      macd  macd_signal  macd_hist  \\\n",
       "0     -0.015586   -0.064437   -0.113838 -0.026005    -0.027676  -0.000001   \n",
       "1      0.751372   -0.064437   -0.113838  0.017229    -0.018474   0.112992   \n",
       "2     -0.558635   -0.064437   -0.113838  0.019481    -0.010632   0.096278   \n",
       "3     -0.320927   -0.064437   -0.113838  0.003433    -0.007775   0.035081   \n",
       "4      0.414782   -0.064437   -0.113838  0.014736    -0.003083   0.057604   \n",
       "...         ...         ...         ...       ...          ...        ...   \n",
       "4995   0.653340    0.234105   -0.650730 -0.113907    -0.588542   1.434463   \n",
       "4996   0.213843    0.542856   -0.607582  0.008087    -0.469112   1.466400   \n",
       "4997   1.097647    0.735365   -0.437462  0.204482    -0.331765   1.686395   \n",
       "4998   0.597173    1.104172   -0.427007  0.412795    -0.177547   1.893541   \n",
       "4999  -0.345374    1.034993   -0.439333  0.539875    -0.027124   1.846952   \n",
       "\n",
       "      volatility  Target  \n",
       "0            NaN       1  \n",
       "1            NaN       0  \n",
       "2            NaN       0  \n",
       "3            NaN       1  \n",
       "4            NaN       0  \n",
       "...          ...     ...  \n",
       "4995   -0.499596       1  \n",
       "4996   -0.507162       1  \n",
       "4997   -0.432448       1  \n",
       "4998   -0.801462       0  \n",
       "4999   -0.731737       0  \n",
       "\n",
       "[5000 rows x 15 columns]"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Inspect\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "d966247c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop the last row where future price is unknown due to shift\n",
    "clean_df = clean_df.iloc[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "73821746",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>return_21d</th>\n",
       "      <th>return_63d</th>\n",
       "      <th>macd</th>\n",
       "      <th>macd_signal</th>\n",
       "      <th>macd_hist</th>\n",
       "      <th>volatility</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>02/14/1995</td>\n",
       "      <td>-0.503264</td>\n",
       "      <td>-0.495490</td>\n",
       "      <td>-0.507674</td>\n",
       "      <td>-0.483120</td>\n",
       "      <td>-0.449743</td>\n",
       "      <td>-0.073927</td>\n",
       "      <td>-0.076736</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>0.007077</td>\n",
       "      <td>0.001755</td>\n",
       "      <td>0.017732</td>\n",
       "      <td>-0.730385</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>02/15/1995</td>\n",
       "      <td>-0.529106</td>\n",
       "      <td>-0.500564</td>\n",
       "      <td>-0.522569</td>\n",
       "      <td>-0.506429</td>\n",
       "      <td>-0.324925</td>\n",
       "      <td>-0.615747</td>\n",
       "      <td>-0.627913</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>-0.032836</td>\n",
       "      <td>-0.005585</td>\n",
       "      <td>-0.090127</td>\n",
       "      <td>-0.657557</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>02/16/1995</td>\n",
       "      <td>-0.526522</td>\n",
       "      <td>-0.522128</td>\n",
       "      <td>-0.538705</td>\n",
       "      <td>-0.514199</td>\n",
       "      <td>-0.406680</td>\n",
       "      <td>0.045984</td>\n",
       "      <td>0.046483</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>-0.060570</td>\n",
       "      <td>-0.017360</td>\n",
       "      <td>-0.144584</td>\n",
       "      <td>-0.808153</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>02/17/1995</td>\n",
       "      <td>-0.526522</td>\n",
       "      <td>-0.519591</td>\n",
       "      <td>-0.537464</td>\n",
       "      <td>-0.506429</td>\n",
       "      <td>-0.447994</td>\n",
       "      <td>-0.016192</td>\n",
       "      <td>-0.015586</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>-0.081905</td>\n",
       "      <td>-0.031322</td>\n",
       "      <td>-0.171426</td>\n",
       "      <td>-0.853840</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>02/21/1995</td>\n",
       "      <td>-0.558824</td>\n",
       "      <td>-0.524665</td>\n",
       "      <td>-0.547393</td>\n",
       "      <td>-0.532329</td>\n",
       "      <td>-0.374328</td>\n",
       "      <td>-0.771186</td>\n",
       "      <td>-0.790386</td>\n",
       "      <td>-0.064437</td>\n",
       "      <td>-0.113838</td>\n",
       "      <td>-0.141218</td>\n",
       "      <td>-0.055116</td>\n",
       "      <td>-0.292156</td>\n",
       "      <td>-0.756758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4994</th>\n",
       "      <td>02/12/2014</td>\n",
       "      <td>0.606036</td>\n",
       "      <td>0.608099</td>\n",
       "      <td>0.604467</td>\n",
       "      <td>0.637717</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>-0.260455</td>\n",
       "      <td>-0.266400</td>\n",
       "      <td>0.195159</td>\n",
       "      <td>-0.746172</td>\n",
       "      <td>-0.241849</td>\n",
       "      <td>-0.705371</td>\n",
       "      <td>1.375110</td>\n",
       "      <td>-0.522140</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>02/13/2014</td>\n",
       "      <td>0.650587</td>\n",
       "      <td>0.593536</td>\n",
       "      <td>0.597665</td>\n",
       "      <td>0.635127</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.636656</td>\n",
       "      <td>0.653340</td>\n",
       "      <td>0.234105</td>\n",
       "      <td>-0.650730</td>\n",
       "      <td>-0.113907</td>\n",
       "      <td>-0.588542</td>\n",
       "      <td>1.434463</td>\n",
       "      <td>-0.499596</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>02/14/2014</td>\n",
       "      <td>0.666093</td>\n",
       "      <td>0.636665</td>\n",
       "      <td>0.628696</td>\n",
       "      <td>0.682368</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.205865</td>\n",
       "      <td>0.213843</td>\n",
       "      <td>0.542856</td>\n",
       "      <td>-0.607582</td>\n",
       "      <td>0.008087</td>\n",
       "      <td>-0.469112</td>\n",
       "      <td>1.466400</td>\n",
       "      <td>-0.507162</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>02/18/2014</td>\n",
       "      <td>0.741707</td>\n",
       "      <td>0.658838</td>\n",
       "      <td>0.679586</td>\n",
       "      <td>0.705056</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>1.071888</td>\n",
       "      <td>1.097647</td>\n",
       "      <td>0.735365</td>\n",
       "      <td>-0.437462</td>\n",
       "      <td>0.204482</td>\n",
       "      <td>-0.331765</td>\n",
       "      <td>1.686395</td>\n",
       "      <td>-0.432448</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>02/19/2014</td>\n",
       "      <td>0.784346</td>\n",
       "      <td>0.722922</td>\n",
       "      <td>0.715582</td>\n",
       "      <td>0.762036</td>\n",
       "      <td>0.284517</td>\n",
       "      <td>0.583362</td>\n",
       "      <td>0.597173</td>\n",
       "      <td>1.104172</td>\n",
       "      <td>-0.427007</td>\n",
       "      <td>0.412795</td>\n",
       "      <td>-0.177547</td>\n",
       "      <td>1.893541</td>\n",
       "      <td>-0.801462</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4984 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date     Close      Open      High       Low      Vol.  Change %  \\\n",
       "9     02/14/1995 -0.503264 -0.495490 -0.507674 -0.483120 -0.449743 -0.073927   \n",
       "10    02/15/1995 -0.529106 -0.500564 -0.522569 -0.506429 -0.324925 -0.615747   \n",
       "11    02/16/1995 -0.526522 -0.522128 -0.538705 -0.514199 -0.406680  0.045984   \n",
       "12    02/17/1995 -0.526522 -0.519591 -0.537464 -0.506429 -0.447994 -0.016192   \n",
       "13    02/21/1995 -0.558824 -0.524665 -0.547393 -0.532329 -0.374328 -0.771186   \n",
       "...          ...       ...       ...       ...       ...       ...       ...   \n",
       "4994  02/12/2014  0.606036  0.608099  0.604467  0.637717  0.284517 -0.260455   \n",
       "4995  02/13/2014  0.650587  0.593536  0.597665  0.635127  0.284517  0.636656   \n",
       "4996  02/14/2014  0.666093  0.636665  0.628696  0.682368  0.284517  0.205865   \n",
       "4997  02/18/2014  0.741707  0.658838  0.679586  0.705056  0.284517  1.071888   \n",
       "4998  02/19/2014  0.784346  0.722922  0.715582  0.762036  0.284517  0.583362   \n",
       "\n",
       "      return_1d  return_21d  return_63d      macd  macd_signal  macd_hist  \\\n",
       "9     -0.076736   -0.064437   -0.113838  0.007077     0.001755   0.017732   \n",
       "10    -0.627913   -0.064437   -0.113838 -0.032836    -0.005585  -0.090127   \n",
       "11     0.046483   -0.064437   -0.113838 -0.060570    -0.017360  -0.144584   \n",
       "12    -0.015586   -0.064437   -0.113838 -0.081905    -0.031322  -0.171426   \n",
       "13    -0.790386   -0.064437   -0.113838 -0.141218    -0.055116  -0.292156   \n",
       "...         ...         ...         ...       ...          ...        ...   \n",
       "4994  -0.266400    0.195159   -0.746172 -0.241849    -0.705371   1.375110   \n",
       "4995   0.653340    0.234105   -0.650730 -0.113907    -0.588542   1.434463   \n",
       "4996   0.213843    0.542856   -0.607582  0.008087    -0.469112   1.466400   \n",
       "4997   1.097647    0.735365   -0.437462  0.204482    -0.331765   1.686395   \n",
       "4998   0.597173    1.104172   -0.427007  0.412795    -0.177547   1.893541   \n",
       "\n",
       "      volatility  Target  \n",
       "9      -0.730385       0  \n",
       "10     -0.657557       1  \n",
       "11     -0.808153       0  \n",
       "12     -0.853840       0  \n",
       "13     -0.756758       1  \n",
       "...          ...     ...  \n",
       "4994   -0.522140       1  \n",
       "4995   -0.499596       1  \n",
       "4996   -0.507162       1  \n",
       "4997   -0.432448       1  \n",
       "4998   -0.801462       0  \n",
       "\n",
       "[4984 rows x 15 columns]"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "bded75a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Export the df....if running Train Test Split in your model script\n",
    "clean_df.to_csv('TrainingSets/TrainingData.csv', index=False)"
   ]
  }
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