python-for-finances/stock-price-prediction/stock_price_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Reference: https://www.geeksforgeeks.org/stock-price-prediction-using-machine-learning-in-python/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Collecting yellowbrick\n",
      "  Using cached yellowbrick-1.5-py3-none-any.whl (282 kB)\n",
      "Requirement already satisfied: scipy>=1.0.0 in ./venv/lib/python3.10/site-packages (from yellowbrick) (1.11.1)\n",
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      "Installing collected packages: yellowbrick\n",
      "Successfully installed yellowbrick-1.5\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install pandas -q\n",
    "%pip install numpy -q\n",
    "%pip install seaborn  -q\n",
    "%pip install matplotlib -q\n",
    "%pip install yfinance -q\n",
    "%pip install scikit-learn -q\n",
    "%pip install yellowbrick"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import yfinance as yf\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import classification_report, accuracy_score\n",
    "from yellowbrick.classifier import ConfusionMatrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load dataset of bank stock price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ticker = \"ITUB4.SA\"\n",
    "data = yf.download(ticker, start=\"2008-01-01\", progress=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-02</th>\n",
       "      <td>15.100806</td>\n",
       "      <td>15.223335</td>\n",
       "      <td>14.306027</td>\n",
       "      <td>14.411997</td>\n",
       "      <td>8.390958</td>\n",
       "      <td>6442543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-03</th>\n",
       "      <td>14.372258</td>\n",
       "      <td>14.736532</td>\n",
       "      <td>14.117267</td>\n",
       "      <td>14.140448</td>\n",
       "      <td>8.232860</td>\n",
       "      <td>7212266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-04</th>\n",
       "      <td>14.315962</td>\n",
       "      <td>14.431867</td>\n",
       "      <td>13.799355</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7374122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-07</th>\n",
       "      <td>14.292780</td>\n",
       "      <td>14.570953</td>\n",
       "      <td>14.007985</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7597580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-08</th>\n",
       "      <td>14.534526</td>\n",
       "      <td>14.703416</td>\n",
       "      <td>14.256353</td>\n",
       "      <td>14.372258</td>\n",
       "      <td>8.367819</td>\n",
       "      <td>5372057</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close   Volume\n",
       "Date                                                                      \n",
       "2008-01-02  15.100806  15.223335  14.306027  14.411997   8.390958  6442543\n",
       "2008-01-03  14.372258  14.736532  14.117267  14.140448   8.232860  7212266\n",
       "2008-01-04  14.315962  14.431867  13.799355  14.239795   8.290697  7374122\n",
       "2008-01-07  14.292780  14.570953  14.007985  14.239795   8.290697  7597580\n",
       "2008-01-08  14.534526  14.703416  14.256353  14.372258   8.367819  5372057"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize dataset info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3876, 6)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3876.000000</td>\n",
       "      <td>3876.000000</td>\n",
       "      <td>3876.000000</td>\n",
       "      <td>3876.000000</td>\n",
       "      <td>3876.000000</td>\n",
       "      <td>3.876000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>21.517539</td>\n",
       "      <td>21.799286</td>\n",
       "      <td>21.222586</td>\n",
       "      <td>21.512633</td>\n",
       "      <td>16.731696</td>\n",
       "      <td>2.267386e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.123009</td>\n",
       "      <td>7.186481</td>\n",
       "      <td>7.053429</td>\n",
       "      <td>7.115916</td>\n",
       "      <td>7.935137</td>\n",
       "      <td>1.393839e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>7.244082</td>\n",
       "      <td>7.653890</td>\n",
       "      <td>6.999853</td>\n",
       "      <td>7.244082</td>\n",
       "      <td>4.217649</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>15.766475</td>\n",
       "      <td>15.967374</td>\n",
       "      <td>15.577260</td>\n",
       "      <td>15.775082</td>\n",
       "      <td>9.843326</td>\n",
       "      <td>1.333177e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>19.382919</td>\n",
       "      <td>19.682645</td>\n",
       "      <td>19.144298</td>\n",
       "      <td>19.423195</td>\n",
       "      <td>13.558575</td>\n",
       "      <td>1.949876e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>26.915833</td>\n",
       "      <td>27.295000</td>\n",
       "      <td>26.580000</td>\n",
       "      <td>26.912500</td>\n",
       "      <td>24.145989</td>\n",
       "      <td>2.864823e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>38.669998</td>\n",
       "      <td>39.790001</td>\n",
       "      <td>38.400002</td>\n",
       "      <td>39.689999</td>\n",
       "      <td>33.508636</td>\n",
       "      <td>1.606699e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open         High          Low        Close    Adj Close  \\\n",
       "count  3876.000000  3876.000000  3876.000000  3876.000000  3876.000000   \n",
       "mean     21.517539    21.799286    21.222586    21.512633    16.731696   \n",
       "std       7.123009     7.186481     7.053429     7.115916     7.935137   \n",
       "min       7.244082     7.653890     6.999853     7.244082     4.217649   \n",
       "25%      15.766475    15.967374    15.577260    15.775082     9.843326   \n",
       "50%      19.382919    19.682645    19.144298    19.423195    13.558575   \n",
       "75%      26.915833    27.295000    26.580000    26.912500    24.145989   \n",
       "max      38.669998    39.790001    38.400002    39.689999    33.508636   \n",
       "\n",
       "             Volume  \n",
       "count  3.876000e+03  \n",
       "mean   2.267386e+07  \n",
       "std    1.393839e+07  \n",
       "min    0.000000e+00  \n",
       "25%    1.333177e+07  \n",
       "50%    1.949876e+07  \n",
       "75%    2.864823e+07  \n",
       "max    1.606699e+08  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 3876 entries, 2008-01-02 to 2023-08-11\n",
      "Data columns (total 6 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   Open       3876 non-null   float64\n",
      " 1   High       3876 non-null   float64\n",
      " 2   Low        3876 non-null   float64\n",
      " 3   Close      3876 non-null   float64\n",
      " 4   Adj Close  3876 non-null   float64\n",
      " 5   Volume     3876 non-null   int64  \n",
      "dtypes: float64(5), int64(1)\n",
      "memory usage: 212.0 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's look at how quarterly results can affect stock prices over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 5))\n",
    "plt.plot(data[\"Adj Close\"])\n",
    "plt.title(\"ITUB4 close price\", fontsize=24)\n",
    "plt.ylabel(\"Price (in R$)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let\"s check if the \"Close\" and \"Adj Close\" have the same values, so that we can remove possibly redundant data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-02</th>\n",
       "      <td>15.100806</td>\n",
       "      <td>15.223335</td>\n",
       "      <td>14.306027</td>\n",
       "      <td>14.411997</td>\n",
       "      <td>8.390958</td>\n",
       "      <td>6442543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-03</th>\n",
       "      <td>14.372258</td>\n",
       "      <td>14.736532</td>\n",
       "      <td>14.117267</td>\n",
       "      <td>14.140448</td>\n",
       "      <td>8.232860</td>\n",
       "      <td>7212266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-04</th>\n",
       "      <td>14.315962</td>\n",
       "      <td>14.431867</td>\n",
       "      <td>13.799355</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7374122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-07</th>\n",
       "      <td>14.292780</td>\n",
       "      <td>14.570953</td>\n",
       "      <td>14.007985</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7597580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-08</th>\n",
       "      <td>14.534526</td>\n",
       "      <td>14.703416</td>\n",
       "      <td>14.256353</td>\n",
       "      <td>14.372258</td>\n",
       "      <td>8.367819</td>\n",
       "      <td>5372057</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-07</th>\n",
       "      <td>27.930000</td>\n",
       "      <td>28.280001</td>\n",
       "      <td>27.620001</td>\n",
       "      <td>27.660000</td>\n",
       "      <td>27.660000</td>\n",
       "      <td>33001900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-08</th>\n",
       "      <td>27.360001</td>\n",
       "      <td>28.010000</td>\n",
       "      <td>27.110001</td>\n",
       "      <td>27.600000</td>\n",
       "      <td>27.600000</td>\n",
       "      <td>44517500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-09</th>\n",
       "      <td>27.500000</td>\n",
       "      <td>27.600000</td>\n",
       "      <td>26.920000</td>\n",
       "      <td>27.500000</td>\n",
       "      <td>27.500000</td>\n",
       "      <td>35060900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-10</th>\n",
       "      <td>27.650000</td>\n",
       "      <td>27.940001</td>\n",
       "      <td>27.520000</td>\n",
       "      <td>27.590000</td>\n",
       "      <td>27.590000</td>\n",
       "      <td>30620600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-11</th>\n",
       "      <td>27.629999</td>\n",
       "      <td>27.799999</td>\n",
       "      <td>27.459999</td>\n",
       "      <td>27.639999</td>\n",
       "      <td>27.639999</td>\n",
       "      <td>19424700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3876 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close    Volume\n",
       "Date                                                                       \n",
       "2008-01-02  15.100806  15.223335  14.306027  14.411997   8.390958   6442543\n",
       "2008-01-03  14.372258  14.736532  14.117267  14.140448   8.232860   7212266\n",
       "2008-01-04  14.315962  14.431867  13.799355  14.239795   8.290697   7374122\n",
       "2008-01-07  14.292780  14.570953  14.007985  14.239795   8.290697   7597580\n",
       "2008-01-08  14.534526  14.703416  14.256353  14.372258   8.367819   5372057\n",
       "...               ...        ...        ...        ...        ...       ...\n",
       "2023-08-07  27.930000  28.280001  27.620001  27.660000  27.660000  33001900\n",
       "2023-08-08  27.360001  28.010000  27.110001  27.600000  27.600000  44517500\n",
       "2023-08-09  27.500000  27.600000  26.920000  27.500000  27.500000  35060900\n",
       "2023-08-10  27.650000  27.940001  27.520000  27.590000  27.590000  30620600\n",
       "2023-08-11  27.629999  27.799999  27.459999  27.639999  27.639999  19424700\n",
       "\n",
       "[3876 rows x 6 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 6)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data[\"Close\"] == data[\"Adj Close\"]].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can notice, only 8 rows the \"Close\" and \"Adj Close\" have the same value, so we can't remove it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before moving on, let's check the dataset for null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Open         0\n",
       "High         0\n",
       "Low          0\n",
       "Close        0\n",
       "Adj Close    0\n",
       "Volume       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_22901/980192968.py:6: MatplotlibDeprecationWarning: Auto-removal of overlapping axes is deprecated since 3.6 and will be removed two minor releases later; explicitly call ax.remove() as needed.\n",
      "  plt.subplot(2, 3, i+1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "features = [\"Open\", \"High\", \"Low\", \"Close\", \"Adj Close\", \"Volume\"]\n",
    "\n",
    "plt.subplots(figsize=(20, 10))\n",
    "\n",
    "for i, column in enumerate(features):\n",
    "    plt.subplot(2, 3, i+1)\n",
    "\n",
    "    # https://stackoverflow.com/questions/67638590/emulating-deprecated-seaborn-distplots\n",
    "    _, FD_bins = np.histogram(data[column], bins=\"fd\")\n",
    "    bin_nr = min(len(FD_bins)-1, 50)\n",
    "    sns.histplot(data=data, x=column, bins=bin_nr,\n",
    "                 stat=\"density\", alpha=0.4, kde=True, kde_kws={\"cut\": 3})\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After that, let's create the box plot to identify outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_22901/2157267840.py:4: MatplotlibDeprecationWarning: Auto-removal of overlapping axes is deprecated since 3.6 and will be removed two minor releases later; explicitly call ax.remove() as needed.\n",
      "  plt.subplot(2,3,i+1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(20,10))\n",
    "\n",
    "for i, column in enumerate(features):\n",
    "  plt.subplot(2,3,i+1)\n",
    "  sns.boxplot(data[column]).set_title(column)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can conclude that only in the volume column have outliers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's add 3 new columns \"day\", \"month\" and \"year\" from column \"Date\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>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>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-02</th>\n",
       "      <td>15.100806</td>\n",
       "      <td>15.223335</td>\n",
       "      <td>14.306027</td>\n",
       "      <td>14.411997</td>\n",
       "      <td>8.390958</td>\n",
       "      <td>6442543</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-03</th>\n",
       "      <td>14.372258</td>\n",
       "      <td>14.736532</td>\n",
       "      <td>14.117267</td>\n",
       "      <td>14.140448</td>\n",
       "      <td>8.232860</td>\n",
       "      <td>7212266</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-04</th>\n",
       "      <td>14.315962</td>\n",
       "      <td>14.431867</td>\n",
       "      <td>13.799355</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7374122</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-07</th>\n",
       "      <td>14.292780</td>\n",
       "      <td>14.570953</td>\n",
       "      <td>14.007985</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7597580</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-08</th>\n",
       "      <td>14.534526</td>\n",
       "      <td>14.703416</td>\n",
       "      <td>14.256353</td>\n",
       "      <td>14.372258</td>\n",
       "      <td>8.367819</td>\n",
       "      <td>5372057</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close   Volume  \\\n",
       "Date                                                                         \n",
       "2008-01-02  15.100806  15.223335  14.306027  14.411997   8.390958  6442543   \n",
       "2008-01-03  14.372258  14.736532  14.117267  14.140448   8.232860  7212266   \n",
       "2008-01-04  14.315962  14.431867  13.799355  14.239795   8.290697  7374122   \n",
       "2008-01-07  14.292780  14.570953  14.007985  14.239795   8.290697  7597580   \n",
       "2008-01-08  14.534526  14.703416  14.256353  14.372258   8.367819  5372057   \n",
       "\n",
       "            day  month  year  \n",
       "Date                          \n",
       "2008-01-02    2      1  2008  \n",
       "2008-01-03    3      1  2008  \n",
       "2008-01-04    4      1  2008  \n",
       "2008-01-07    7      1  2008  \n",
       "2008-01-08    8      1  2008  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['day'] = data.index.day.astype('int')\n",
    "data['month'] = data.index.month.astype('int')\n",
    "data['year'] = data.index.year.astype('int')\n",
    " \n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we create an `is_quarter` column to use later in the algorithm because every quarter the companies publish the quarterly results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>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>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>is_quarter_end</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-02</th>\n",
       "      <td>15.100806</td>\n",
       "      <td>15.223335</td>\n",
       "      <td>14.306027</td>\n",
       "      <td>14.411997</td>\n",
       "      <td>8.390958</td>\n",
       "      <td>6442543</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-03</th>\n",
       "      <td>14.372258</td>\n",
       "      <td>14.736532</td>\n",
       "      <td>14.117267</td>\n",
       "      <td>14.140448</td>\n",
       "      <td>8.232860</td>\n",
       "      <td>7212266</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-04</th>\n",
       "      <td>14.315962</td>\n",
       "      <td>14.431867</td>\n",
       "      <td>13.799355</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7374122</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-07</th>\n",
       "      <td>14.292780</td>\n",
       "      <td>14.570953</td>\n",
       "      <td>14.007985</td>\n",
       "      <td>14.239795</td>\n",
       "      <td>8.290697</td>\n",
       "      <td>7597580</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-08</th>\n",
       "      <td>14.534526</td>\n",
       "      <td>14.703416</td>\n",
       "      <td>14.256353</td>\n",
       "      <td>14.372258</td>\n",
       "      <td>8.367819</td>\n",
       "      <td>5372057</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close   Volume  \\\n",
       "Date                                                                         \n",
       "2008-01-02  15.100806  15.223335  14.306027  14.411997   8.390958  6442543   \n",
       "2008-01-03  14.372258  14.736532  14.117267  14.140448   8.232860  7212266   \n",
       "2008-01-04  14.315962  14.431867  13.799355  14.239795   8.290697  7374122   \n",
       "2008-01-07  14.292780  14.570953  14.007985  14.239795   8.290697  7597580   \n",
       "2008-01-08  14.534526  14.703416  14.256353  14.372258   8.367819  5372057   \n",
       "\n",
       "            day  month  year  is_quarter_end  \n",
       "Date                                          \n",
       "2008-01-02    2      1  2008               0  \n",
       "2008-01-03    3      1  2008               0  \n",
       "2008-01-04    4      1  2008               0  \n",
       "2008-01-07    7      1  2008               0  \n",
       "2008-01-08    8      1  2008               0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['is_quarter_end'] = np.where(data['month'] % 3 == 0, 1, 0)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_22901/1494818884.py:5: MatplotlibDeprecationWarning: Auto-removal of overlapping axes is deprecated since 3.6 and will be removed two minor releases later; explicitly call ax.remove() as needed.\n",
      "  plt.subplot(2,2,i+1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_grouped = data.groupby('year').mean()\n",
    "plt.subplots(figsize=(20,15))\n",
    " \n",
    "for i, column in enumerate(['Open', 'High', 'Low', 'Close']):\n",
    "  plt.subplot(2,2,i+1)\n",
    "  data_grouped[col].plot.bar().set_title(column)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>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>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is_quarter_end</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21.562839</td>\n",
       "      <td>21.844573</td>\n",
       "      <td>21.272231</td>\n",
       "      <td>21.561341</td>\n",
       "      <td>16.760581</td>\n",
       "      <td>2.262913e+07</td>\n",
       "      <td>15.810131</td>\n",
       "      <td>5.978732</td>\n",
       "      <td>2015.344934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21.426729</td>\n",
       "      <td>21.708502</td>\n",
       "      <td>21.123064</td>\n",
       "      <td>21.414992</td>\n",
       "      <td>16.673791</td>\n",
       "      <td>2.276353e+07</td>\n",
       "      <td>15.598450</td>\n",
       "      <td>7.327907</td>\n",
       "      <td>2015.277519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Open       High        Low      Close  Adj Close  \\\n",
       "is_quarter_end                                                          \n",
       "0               21.562839  21.844573  21.272231  21.561341  16.760581   \n",
       "1               21.426729  21.708502  21.123064  21.414992  16.673791   \n",
       "\n",
       "                      Volume        day     month         year  \n",
       "is_quarter_end                                                  \n",
       "0               2.262913e+07  15.810131  5.978732  2015.344934  \n",
       "1               2.276353e+07  15.598450  7.327907  2015.277519  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('is_quarter_end').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the above DataFrame we can make some importante observations:\n",
    "\n",
    "- The price (\"Adj Close\") is slightly lower when it is at the end of a quarter\n",
    "\n",
    "- The volume has a small increase at the end of a quarter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['open-close']  = data['Open'] - data['Adj Close']\n",
    "data['low-high']  = data['Low'] - data['High']\n",
    "data['target'] = np.where(data['Adj Close'].shift(-1) > data['Adj Close'], 1, 0) # \"1\" if the \"Adj Close\" of the previous day is higher than the current \"Adj Close\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The \"target\" is the most importante feature, because it will be used to help model to buy or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(\n",
    "  data['target'].value_counts().values,\n",
    "  labels=[0, 1], \n",
    "  autopct='%1.1f%%'\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 10))\n",
    " \n",
    "# As our concern is with the highly\n",
    "# correlated features only so, we will visualize\n",
    "# our heatmap as per that criteria only.\n",
    "sns.heatmap(data.corr() > 0.9, annot=True, cbar=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Splitting and Normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((3488, 3), (388, 3))"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = data[['open-close', 'low-high', 'is_quarter_end']]\n",
    "target = data['target']\n",
    " \n",
    "scaler = StandardScaler()\n",
    "features = scaler.fit_transform(features)\n",
    " \n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    features, target, test_size=0.1, random_state=2022\n",
    ")\n",
    "\n",
    "X_train.shape, X_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Development and Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = SVC(kernel='sigmoid', C=1, probability=True)\n",
    " \n",
    "model.fit(X_train, y_train)\n",
    " \n",
    "predicts = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5180412371134021"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x550 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm = ConfusionMatrix(model)\n",
    "cm.fit(X_train, y_train)\n",
    "cm.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.48      0.52      0.50       181\n",
      "           1       0.55      0.51      0.53       207\n",
      "\n",
      "    accuracy                           0.52       388\n",
      "   macro avg       0.52      0.52      0.52       388\n",
      "weighted avg       0.52      0.52      0.52       388\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, predicts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5180412371134021"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(Y_valid, predicts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}