{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MisWyhViGzpm"
   },
   "source": [
    "## Importing basic packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "YH-BInNOxEjx"
   },
   "outputs": [],
   "source": [
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VhF7NzG8G6XX"
   },
   "source": [
    "## Loading Dataset\n",
    "\n",
    "We can use boston housing dataset for PCA. Boston dataset has 13 features which we can reduce by using PCA.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "shTVAi2oCesd"
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('Cereals.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "9L-aQNXvCese",
    "outputId": "996c7eea-703d-4751-ea54-121da58747e6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(77, 14)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "Bii7X82ICesf",
    "outputId": "8f1311d4-7d50-4229-f169-ef2a532177df",
    "scrolled": true
   },
   "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>name</th>\n",
       "      <th>calories</th>\n",
       "      <th>protein</th>\n",
       "      <th>fat</th>\n",
       "      <th>sodium</th>\n",
       "      <th>fiber</th>\n",
       "      <th>carbo</th>\n",
       "      <th>sugars</th>\n",
       "      <th>potass</th>\n",
       "      <th>vitamins</th>\n",
       "      <th>shelf</th>\n",
       "      <th>weight</th>\n",
       "      <th>cups</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100%_Bran</td>\n",
       "      <td>70</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.33</td>\n",
       "      <td>68.402973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100%_Natural_Bran</td>\n",
       "      <td>120</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>33.983679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>All-Bran</td>\n",
       "      <td>70</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>260</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.33</td>\n",
       "      <td>59.425505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>All-Bran_with_Extra_Fiber</td>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>140</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>93.704912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Almond_Delight</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>200</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>34.384843</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  calories  protein  fat  sodium  fiber  carbo  \\\n",
       "0                  100%_Bran        70        4    1     130   10.0    5.0   \n",
       "1          100%_Natural_Bran       120        3    5      15    2.0    8.0   \n",
       "2                   All-Bran        70        4    1     260    9.0    7.0   \n",
       "3  All-Bran_with_Extra_Fiber        50        4    0     140   14.0    8.0   \n",
       "4             Almond_Delight       110        2    2     200    1.0   14.0   \n",
       "\n",
       "   sugars  potass  vitamins  shelf  weight  cups     rating  \n",
       "0     6.0   280.0        25      3     1.0  0.33  68.402973  \n",
       "1     8.0   135.0         0      3     1.0  1.00  33.983679  \n",
       "2     5.0   320.0        25      3     1.0  0.33  59.425505  \n",
       "3     0.0   330.0        25      3     1.0  0.50  93.704912  \n",
       "4     8.0     NaN        25      3     1.0  0.75  34.384843  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "fjKwaYu8Cesh"
   },
   "outputs": [],
   "source": [
    "df.set_index(\"name\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "ZOu-ekHOCesi",
    "outputId": "d060d6bf-3c37-40a8-8d3d-0deeda0a1540"
   },
   "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>calories</th>\n",
       "      <th>protein</th>\n",
       "      <th>fat</th>\n",
       "      <th>sodium</th>\n",
       "      <th>fiber</th>\n",
       "      <th>carbo</th>\n",
       "      <th>sugars</th>\n",
       "      <th>potass</th>\n",
       "      <th>vitamins</th>\n",
       "      <th>shelf</th>\n",
       "      <th>weight</th>\n",
       "      <th>cups</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100%_Bran</th>\n",
       "      <td>70</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.33</td>\n",
       "      <td>68.402973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100%_Natural_Bran</th>\n",
       "      <td>120</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>33.983679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All-Bran</th>\n",
       "      <td>70</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>260</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.33</td>\n",
       "      <td>59.425505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All-Bran_with_Extra_Fiber</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>140</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>93.704912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Almond_Delight</th>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>200</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>34.384843</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           calories  protein  fat  sodium  fiber  carbo  \\\n",
       "name                                                                      \n",
       "100%_Bran                        70        4    1     130   10.0    5.0   \n",
       "100%_Natural_Bran               120        3    5      15    2.0    8.0   \n",
       "All-Bran                         70        4    1     260    9.0    7.0   \n",
       "All-Bran_with_Extra_Fiber        50        4    0     140   14.0    8.0   \n",
       "Almond_Delight                  110        2    2     200    1.0   14.0   \n",
       "\n",
       "                           sugars  potass  vitamins  shelf  weight  cups  \\\n",
       "name                                                                       \n",
       "100%_Bran                     6.0   280.0        25      3     1.0  0.33   \n",
       "100%_Natural_Bran             8.0   135.0         0      3     1.0  1.00   \n",
       "All-Bran                      5.0   320.0        25      3     1.0  0.33   \n",
       "All-Bran_with_Extra_Fiber     0.0   330.0        25      3     1.0  0.50   \n",
       "Almond_Delight                8.0     NaN        25      3     1.0  0.75   \n",
       "\n",
       "                              rating  \n",
       "name                                  \n",
       "100%_Bran                  68.402973  \n",
       "100%_Natural_Bran          33.983679  \n",
       "All-Bran                   59.425505  \n",
       "All-Bran_with_Extra_Fiber  93.704912  \n",
       "Almond_Delight             34.384843  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 77 entries, 100%_Bran to Wheaties_Honey_Gold\n",
      "Data columns (total 13 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   calories  77 non-null     int64  \n",
      " 1   protein   77 non-null     int64  \n",
      " 2   fat       77 non-null     int64  \n",
      " 3   sodium    77 non-null     int64  \n",
      " 4   fiber     77 non-null     float64\n",
      " 5   carbo     77 non-null     float64\n",
      " 6   sugars    77 non-null     float64\n",
      " 7   potass    77 non-null     float64\n",
      " 8   vitamins  77 non-null     int64  \n",
      " 9   shelf     77 non-null     int64  \n",
      " 10  weight    77 non-null     float64\n",
      " 11  cups      77 non-null     float64\n",
      " 12  rating    77 non-null     float64\n",
      "dtypes: float64(7), int64(6)\n",
      "memory usage: 10.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AVrh_VTbCesk"
   },
   "source": [
    "## Check for NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "6RqpuJeYCesk",
    "outputId": "cc72666e-f638-4721-8345-ae61b06225e7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "calories    0\n",
       "protein     0\n",
       "fat         0\n",
       "sodium      0\n",
       "fiber       0\n",
       "carbo       1\n",
       "sugars      1\n",
       "potass      2\n",
       "vitamins    0\n",
       "shelf       0\n",
       "weight      0\n",
       "cups        0\n",
       "rating      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "GYu4w0yBCesl"
   },
   "outputs": [],
   "source": [
    "df = df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "id": "cbgMToxXCesm",
    "outputId": "7d9191f1-a38d-420e-f4b9-afdf1d4aa76f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                 rating   R-squared:                       1.000\n",
      "Model:                            OLS   Adj. R-squared:                  1.000\n",
      "Method:                 Least Squares   F-statistic:                 3.732e+07\n",
      "Date:                Sun, 06 Oct 2024   Prob (F-statistic):          6.27e-163\n",
      "Time:                        17:30:11   Log-Likelihood:                 238.83\n",
      "No. Observations:                  61   AIC:                            -451.7\n",
      "Df Residuals:                      48   BIC:                            -424.2\n",
      "Df Model:                          12                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const         54.9110      0.007   7800.566      0.000      54.897      54.925\n",
      "calories      -0.2229      0.000  -1576.658      0.000      -0.223      -0.223\n",
      "protein        3.2750      0.001   3062.104      0.000       3.273       3.277\n",
      "fat           -1.6895      0.001  -1159.619      0.000      -1.692      -1.687\n",
      "sodium        -0.0545   1.02e-05  -5355.322      0.000      -0.055      -0.054\n",
      "fiber          3.4463      0.001   3909.770      0.000       3.445       3.448\n",
      "carbo          1.0931      0.001   1654.240      0.000       1.092       1.094\n",
      "sugars        -0.7243      0.001  -1127.216      0.000      -0.726      -0.723\n",
      "potass        -0.0341   3.02e-05  -1128.690      0.000      -0.034      -0.034\n",
      "vitamins      -0.0513   3.79e-05  -1353.576      0.000      -0.051      -0.051\n",
      "shelf          0.0021      0.001      2.045      0.046    3.59e-05       0.004\n",
      "weight         0.0164      0.010      1.650      0.105      -0.004       0.036\n",
      "cups           0.0026      0.004      0.698      0.488      -0.005       0.010\n",
      "==============================================================================\n",
      "Omnibus:                       53.622   Durbin-Watson:                   1.926\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              271.045\n",
      "Skew:                           2.465   Prob(JB):                     1.39e-59\n",
      "Kurtosis:                      12.074   Cond. No.                     3.49e+03\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "[2] The condition number is large, 3.49e+03. This might indicate that there are\n",
      "strong multicollinearity or other numerical problems.\n",
      "Training MSE 0.00\n",
      "Testing MSE 0.01\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "import statsmodels.api as sm\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "X = df.drop(columns=\"rating\")\n",
    "y = df.rating\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=101)\n",
    "\n",
    "# Build the initial MLR model using statsmodels\n",
    "\n",
    "X_train_const = sm.add_constant(X_train)\n",
    "mlr_model = sm.OLS(y_train, X_train_const).fit()\n",
    "\n",
    "\n",
    "y_train_pred = mlr_model.predict(X_train_const)\n",
    "X_test_const = sm.add_constant(X_test)\n",
    "y_pred_initial = mlr_model.predict(X_test_const)\n",
    "# Print the summary of the model\n",
    "print(mlr_model.summary())\n",
    "\n",
    "# calculate MSE\n",
    "mse_initial_test = mean_squared_error(y_test, y_pred_initial)\n",
    "mse_initial_train = mean_squared_error(y_train, y_train_pred)\n",
    "\n",
    "print(\"Training MSE {:.2f}\\nTesting MSE {:.2f}\".format(mse_initial_train, mse_initial_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MOz1kyFXHFWu",
    "tags": []
   },
   "source": [
    "## Standardize data\n",
    "\n",
    "PCA is largely affected by scales and different features might have different scales. So it is better to standardize data before finding PCA components. Sklearn's [StandardScaler](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html#sklearn.preprocessing.StandardScaler) scales data to scale of zero mean and unit variance. It is important step in many of the machine learning algorithms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "2x8FIje2w7Bb"
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler().fit(X_train)\n",
    "\n",
    "x_train_scaled = scaler.transform(X_train)\n",
    "x_train_scaled = pd.DataFrame(x_train_scaled, columns=X_train.columns)\n",
    "\n",
    "x_test_scaled = scaler.transform(X_test)\n",
    "x_test_scaled = pd.DataFrame(x_test_scaled, columns=X_train.columns)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KQbD_x_yHUzV"
   },
   "source": [
    "## Getting PCA Components\n",
    "\n",
    "Calculating PCA involves following steps:\n",
    "\n",
    "1.   Calculating the covariance matrix\n",
    "2.   Calculating the eigenvalues and eigenvector\n",
    "3.   Forming Principal Components\n",
    "4.   Projection into the new feature space\n",
    "\n",
    "\n",
    "This post is more about visualizing PCA components than to calculate and fortunately sklearn provides[ PCA module](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA) for getting PCA components\n",
    "\n",
    "In PCA(), `n_components` specifies how many components are returned after fit and tranformation.\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "id": "n4XqzKkyxfNS",
    "outputId": "86eeda7f-770d-4bf6-a07a-e0dea36536ac"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(61, 12)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "pcamodel = PCA(n_components=12)\n",
    "pca_model = pcamodel.fit(x_train_scaled)\n",
    "\n",
    "pca = pca_model.transform(x_train_scaled)\n",
    "pca.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tABjJEM6jvGN"
   },
   "source": [
    "## PCA model attribute plots\n",
    "\n",
    "PCA components and their significance can be explained using following attributes\n",
    "\n",
    "**Explained variance** is the amount of variance explained by each of the selected components. This attribute is associated with the sklearn PCA model as `explained_variance_`\n",
    "\n",
    "**Explained variance ratio** is the percentage of variance explained by each of the selected components. It's attribute is `explained_variance_ratio_`\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "id": "ueQTuWALzq5q",
    "outputId": "23ec0bdd-f820-4868-cc87-b5b818e66363"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.19358446, 2.74602148, 1.75328053, 1.09688938, 1.06156961,\n",
       "       0.7852154 , 0.66913392, 0.39167533, 0.3085047 , 0.10792792,\n",
       "       0.06433315, 0.02186411])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pcamodel.explained_variance_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "id": "ArlNDXbaozHa",
    "outputId": "b8766cf5-68a4-4d80-d47c-c32f4f329fdc"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.26176922, 0.22508373, 0.14371152, 0.08990897, 0.0870139 ,\n",
       "       0.06436192, 0.05484704, 0.03210454, 0.02528727, 0.00884655,\n",
       "       0.00527321, 0.00179214])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pcamodel.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oF26Mceco_RC"
   },
   "source": [
    "### `explained_variance_` and it's cumulative sum Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 378
    },
    "id": "AHQ22nZo00yT",
    "outputId": "2a8c04fc-361f-4ef6-dcd8-6ad0909d3ea1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1685b5760>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(range(1,len(pcamodel.explained_variance_ )+1),pcamodel.explained_variance_ )\n",
    "plt.ylabel('Explained variance')\n",
    "plt.xlabel('Components')\n",
    "plt.plot(range(1,len(pcamodel.explained_variance_ )+1),\n",
    "         np.cumsum(pcamodel.explained_variance_),\n",
    "         c='red',\n",
    "         label=\"Cumulative Explained Variance\")\n",
    "plt.legend(loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "g67XoHHCpfjE"
   },
   "source": [
    "### explained_variance_ratio_ Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 361
    },
    "id": "1m70XtcC0lQx",
    "outputId": "6235335e-7ece-42a0-975c-693de343f860"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(pcamodel.explained_variance_ratio_)\n",
    "plt.xlabel('number of components')\n",
    "plt.ylabel('explained variance')\n",
    "plt.show()\n",
    "\n",
    "#PCA1 is at 0 in xscale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iwdAjQfRmE5Q"
   },
   "source": [
    "It can be seen from plots that, PCA-1 explains most of the variance than subsequent components. In other words, most of the features are explained and encompassed by PCA1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "s8EGzbzWHg1d"
   },
   "source": [
    "## Scatter plot of PCA1 and PCA2\n",
    "\n",
    "`pca` helds all PCA components. First two of them can be visualized using scatter plot.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 364
    },
    "id": "kb4zguHixkiv",
    "outputId": "771994c6-4c75-4f72-d0c3-41b528d837b0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1686c9010>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(pca[:, 0], pca[:, 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iuqM5Ne8Cesz"
   },
   "source": [
    "# 3D Scatter Plot"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "id": "K1c0Gp9_Cesz",
    "scrolled": true
   },
   "source": [
    "import plotly.graph_objs as go\n",
    "import plotly.offline as pyo\n",
    "\n",
    "\n",
    "# Create the 3D scatter plot trace\n",
    "fig1 = go.Scatter3d(\n",
    "    x=pca[:, 0],  # PCA1 values\n",
    "    y=pca[:, 1],  # PCA2 values\n",
    "    z=pca[:, 2],  # PCA3 values\n",
    "    marker=dict(\n",
    "        opacity=0.9,\n",
    "        reversescale=True,\n",
    "        colorscale='Blues',  # Blue color scale for points\n",
    "        size=5  # Marker size\n",
    "    ),\n",
    "    line=dict(\n",
    "        width=0.02  # Thin line for markers\n",
    "    ),\n",
    "    mode='markers'  # Plot markers only\n",
    ")\n",
    "\n",
    "# Create the layout for the plot\n",
    "mylayout = go.Layout(\n",
    "    scene=dict(\n",
    "        xaxis=dict(title=\"PCA1\"),  # X-axis label\n",
    "        yaxis=dict(title=\"PCA2\"),  # Y-axis label\n",
    "        zaxis=dict(title=\"PCA3\")   # Z-axis label\n",
    "    ),\n",
    "    title=\"3D Scatter Plot of PCA Components\",  # Add a plot title\n",
    "    width=1200,  # Increased width\n",
    "    height=800   # Increased height\n",
    ")\n",
    "\n",
    "# Create a Figure object and plot\n",
    "fig = go.Figure(data=[fig1], layout=mylayout, )\n",
    "\n",
    "# Show the plot\n",
    "pyo.iplot(fig)  # Use pyo.plot(fig) to save or display outside a notebook\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "raLw8kT6Ces0"
   },
   "source": [
    "# Linear Regression on PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "7y9rCeqECes1",
    "outputId": "7927edab-37b3-4651-fa97-b8759db7714c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   R-squared:                       0.983\n",
      "Model:                            OLS   Adj. R-squared:                  0.981\n",
      "Method:                 Least Squares   F-statistic:                     380.6\n",
      "Date:                Sun, 06 Oct 2024   Prob (F-statistic):           2.48e-43\n",
      "Time:                        17:40:39   Log-Likelihood:                -126.01\n",
      "No. Observations:                  61   AIC:                             270.0\n",
      "Df Residuals:                      52   BIC:                             289.0\n",
      "Df Model:                           8                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const         42.7933      0.265    161.611      0.000      42.262      43.325\n",
      "x1             0.1469      0.149      0.983      0.330      -0.153       0.447\n",
      "x2            -7.7479      0.161    -48.088      0.000      -8.071      -7.425\n",
      "x3             4.8637      0.202     24.121      0.000       4.459       5.268\n",
      "x4            -1.6930      0.255     -6.641      0.000      -2.205      -1.181\n",
      "x5             0.7037      0.259      2.716      0.009       0.184       1.224\n",
      "x6            -1.0605      0.301     -3.520      0.001      -1.665      -0.456\n",
      "x7            -3.0189      0.326     -9.249      0.000      -3.674      -2.364\n",
      "x8             0.1256      0.427      0.295      0.770      -0.730       0.982\n",
      "==============================================================================\n",
      "Omnibus:                        0.892   Durbin-Watson:                   1.835\n",
      "Prob(Omnibus):                  0.640   Jarque-Bera (JB):                0.758\n",
      "Skew:                           0.268   Prob(JB):                        0.685\n",
      "Kurtosis:                       2.892   Cond. No.                         2.86\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "\n",
      "Training MSE 0.00\n",
      "Testing MSE 0.01\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "import statsmodels.api as sm\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "\n",
    "X_train_const = sm.add_constant(pca[:, :8])\n",
    "mlr_model = sm.OLS(y_train.values, X_train_const).fit()\n",
    "\n",
    "\n",
    "\n",
    "y_train_pred_pca = mlr_model.predict(X_train_const)\n",
    "\n",
    "pca_test = pca_model.transform(x_test_scaled)\n",
    "\n",
    "X_test_const = sm.add_constant(pca_test[:, :8])\n",
    "y_test_pred_pca = mlr_model.predict(X_test_const)\n",
    "# Print the summary of the model\n",
    "print(mlr_model.summary())\n",
    "\n",
    "# calculate MSE\n",
    "mse_pca_test = mean_squared_error(y_test, y_test_pred_pca)\n",
    "mse_pca_train = mean_squared_error(y_train, y_train_pred_pca)\n",
    "\n",
    "print(\"\\nTraining MSE {:.2f}\\nTesting MSE {:.2f}\".format(mse_initial_train, mse_initial_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wePFKL17pzpY",
    "tags": []
   },
   "source": [
    "## Effect of variables on each components\n",
    "\n",
    " `components_` attribute provides principal axes in feature space, representing the directions of maximum variance in the data. This means, we can see influence on each of the components by features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 287
    },
    "id": "Ik43Cjtc1CDa",
    "outputId": "34c58d49-a9f0-4ab9-f75f-af425521a2f6"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.heatmap(pcamodel.components_,\n",
    "                 cmap='YlGnBu',\n",
    "                 yticklabels=[ \"PCA\"+str(x) for x in range(1,pcamodel.n_components_+1)],\n",
    "                 xticklabels=list(x_train_scaled.columns),\n",
    "                 cbar_kws={\"orientation\": \"horizontal\"})\n",
    "ax.set_aspect(\"equal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bO0zJEUFpyDB"
   },
   "source": [
    "## PCA Biplot\n",
    "\n",
    "Biplot is an interesting plot and contains lot of useful information.\n",
    "\n",
    "It contains two plots:\n",
    "\n",
    "1.   *PCA scatter plot* which shows first two component ( We already plotted this above)\n",
    "2.   *PCA loading plot* which shows how strongly each characteristic influences a principal component.\n",
    "\n",
    "**PCA Loading Plot:**  All vectors start at origin and their projected values on components explains how much weight they have on that component. Also , angles between individual vectors tells about correlation between them.\n",
    "\n",
    "More about biplot [here](http://www.nonlinear.com/support/progenesis/comet/faq/v2.0/pca.aspx)\n",
    "\n",
    "Let's plot for our data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 361
    },
    "id": "MjXKvuzO21pc",
    "outputId": "a504ad7b-db88-421c-b496-0c2c245415c3"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def myplot(score,coeff,labels=None):\n",
    "    xs = score[:,0]\n",
    "    ys = score[:,1]\n",
    "    n = coeff.shape[0]\n",
    "    scalex = 1.0/(xs.max() - xs.min())\n",
    "    scaley = 1.0/(ys.max() - ys.min())\n",
    "    plt.scatter(xs * scalex,ys * scaley,s=5)\n",
    "    plt.xticks(rotation=90)\n",
    "    for i in range(n):\n",
    "        plt.arrow(0, 0, coeff[i,0]*2, coeff[i,1]*2,color = 'r',alpha = 0.5)\n",
    "        if labels is None:\n",
    "            plt.text(coeff[i,0]* 1.15, coeff[i,1] * 1.15, \"Var\"+str(i+1), color = 'green', ha = 'center', va = 'center')\n",
    "        else:\n",
    "            plt.text(coeff[i,0]* 2.15, coeff[i,1] *2.15, labels[i], color = 'g', ha = 'center', va = 'center', rotation=30)\n",
    "\n",
    "    plt.xlabel(\"PC{}\".format(1))\n",
    "    plt.ylabel(\"PC{}\".format(2))\n",
    "    plt.grid()\n",
    "\n",
    "\n",
    "plt.figure(figsize=(20,15))\n",
    "myplot(pca[:,0:2],np.transpose(pcamodel.components_[0:2, :]),list(x_train_scaled.columns))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "n8yW8Fw9nG0u"
   },
   "source": [
    "## Interesing reads about PCA:\n",
    "\n",
    "\n",
    "* http://setosa.io/ev/principal-component-analysis/\n",
    "* https://towardsdatascience.com/a-one-stop-shop-for-principal-component-analysis-5582fb7e0a9c\n",
    "* https://blog.bioturing.com/2018/06/18/how-to-read-pca-biplots-and-scree-plots/\n",
    "* https://en.wikipedia.org/wiki/Principal_component_analysis\n",
    "* https://medium.com/@aptrishu/understanding-principle-component-analysis-e32be0253ef0\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NT6ULeJbCes5"
   },
   "source": [
    "# Dimensionality Reduction with PCA: Preserving Image Integrity in the MNIST Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "id": "4bbQnQXQCes5"
   },
   "outputs": [],
   "source": [
    "mnist = pd.read_csv(\"mnist_train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 785)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mnist.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>label</th>\n",
       "      <th>1x1</th>\n",
       "      <th>1x2</th>\n",
       "      <th>1x3</th>\n",
       "      <th>1x4</th>\n",
       "      <th>1x5</th>\n",
       "      <th>1x6</th>\n",
       "      <th>1x7</th>\n",
       "      <th>1x8</th>\n",
       "      <th>1x9</th>\n",
       "      <th>...</th>\n",
       "      <th>28x19</th>\n",
       "      <th>28x20</th>\n",
       "      <th>28x21</th>\n",
       "      <th>28x22</th>\n",
       "      <th>28x23</th>\n",
       "      <th>28x24</th>\n",
       "      <th>28x25</th>\n",
       "      <th>28x26</th>\n",
       "      <th>28x27</th>\n",
       "      <th>28x28</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 785 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   label  1x1  1x2  1x3  1x4  1x5  1x6  1x7  1x8  1x9  ...  28x19  28x20  \\\n",
       "0      5    0    0    0    0    0    0    0    0    0  ...      0      0   \n",
       "1      0    0    0    0    0    0    0    0    0    0  ...      0      0   \n",
       "2      4    0    0    0    0    0    0    0    0    0  ...      0      0   \n",
       "3      1    0    0    0    0    0    0    0    0    0  ...      0      0   \n",
       "4      9    0    0    0    0    0    0    0    0    0  ...      0      0   \n",
       "\n",
       "   28x21  28x22  28x23  28x24  28x25  28x26  28x27  28x28  \n",
       "0      0      0      0      0      0      0      0      0  \n",
       "1      0      0      0      0      0      0      0      0  \n",
       "2      0      0      0      0      0      0      0      0  \n",
       "3      0      0      0      0      0      0      0      0  \n",
       "4      0      0      0      0      0      0      0      0  \n",
       "\n",
       "[5 rows x 785 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mnist.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "id": "mBJP7pcsCes6",
    "outputId": "57b5a005-72d1-4c1e-fb93-918724e05936"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x500 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "X = mnist.drop(columns=\"label\") / 255.0  # Normalize the data\n",
    "y = mnist.label\n",
    "\n",
    "# Reshape the data to 28x28 images for visualization\n",
    "def plot_digits(data, num_rows=2, num_cols=5):\n",
    "    fig, axes = plt.subplots(num_rows, num_cols, figsize=(10, 5))\n",
    "    for i, ax in enumerate(axes.flat):\n",
    "        ax.imshow(data[i].reshape(28, 28), cmap='gray')\n",
    "        ax.axis('off')\n",
    "    plt.show()\n",
    "\n",
    "# Display original images\n",
    "plot_digits(X.values[:10])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "id": "RInu_EN3Ces6",
    "outputId": "4cb621d8-6633-4142-f874-7936d1a41021",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x500 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Apply PCA to reduce dimensions\n",
    "pca_mnist = PCA(n_components=100)  # Reduce to 50 principal components\n",
    "X_pca_mnist = pca_mnist.fit_transform(X)\n",
    "\n",
    "# Inverse transform to reconstruct the images\n",
    "X_reconstructed = pca_mnist.inverse_transform(X_pca_mnist)\n",
    "\n",
    "# Plot reconstructed images (with reduced features)\n",
    "plot_digits(X_reconstructed[:10])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(pca_mnist.explained_variance_ratio_)\n",
    "plt.xlabel('number of components')\n",
    "plt.ylabel('explained variance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ncOL7eqACes7"
   },
   "source": [
    "## Homework\n",
    "\n",
    "Mnist is a 10 class classification problem, fit Logistic Regression on this data set with and without PCA and check the error metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "meloRdvICes7"
   },
   "source": [
    "# Portfolio diversification Using PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "id": "gx4Az02WCes7"
   },
   "outputs": [],
   "source": [
    "\n",
    "sks =  [  'ABFRL',  'ADANIENT', 'ADANIPORTS',  'AXISBANK',  'BAJAJFINSV', 'BAJFINANCE', 'BANKBARODA', \"YESBANK\",\n",
    "        'INFY', 'HDFCBANK', 'ICICIBANK' , 'PERSISTENT',  'SBIN',  'TCS','TECHM',  'UBL','ZYDUSLIFE']\n",
    "\n",
    "sks = [x+\".NS\" for x in sks]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "id": "9rbpYfmFCes7",
    "outputId": "f6db4687-8a3d-4a9d-a016-a7e7adf5e900"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[********************  41%%                      ]  7 of 17 completed"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[**********************82%%*************         ]  14 of 17 completed"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n",
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  17 of 17 completed\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/Caskroom/miniconda/base/envs/accelai/lib/python3.12/site-packages/yfinance/utils.py:771: FutureWarning: The 'unit' keyword in TimedeltaIndex construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.\n",
      "  df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')\n"
     ]
    },
    {
     "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>ABFRL.NS</th>\n",
       "      <th>ADANIENT.NS</th>\n",
       "      <th>ADANIPORTS.NS</th>\n",
       "      <th>AXISBANK.NS</th>\n",
       "      <th>BAJAJFINSV.NS</th>\n",
       "      <th>BAJFINANCE.NS</th>\n",
       "      <th>BANKBARODA.NS</th>\n",
       "      <th>HDFCBANK.NS</th>\n",
       "      <th>ICICIBANK.NS</th>\n",
       "      <th>INFY.NS</th>\n",
       "      <th>PERSISTENT.NS</th>\n",
       "      <th>SBIN.NS</th>\n",
       "      <th>TCS.NS</th>\n",
       "      <th>TECHM.NS</th>\n",
       "      <th>UBL.NS</th>\n",
       "      <th>YESBANK.NS</th>\n",
       "      <th>ZYDUSLIFE.NS</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",
       "      <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>2023-10-04</th>\n",
       "      <td>214.250000</td>\n",
       "      <td>2463.956299</td>\n",
       "      <td>821.077148</td>\n",
       "      <td>994.782227</td>\n",
       "      <td>1531.583740</td>\n",
       "      <td>7814.818359</td>\n",
       "      <td>206.631760</td>\n",
       "      <td>1508.944702</td>\n",
       "      <td>922.111694</td>\n",
       "      <td>1405.915527</td>\n",
       "      <td>2829.596924</td>\n",
       "      <td>576.580933</td>\n",
       "      <td>3478.920410</td>\n",
       "      <td>1170.463257</td>\n",
       "      <td>1541.729370</td>\n",
       "      <td>17.200001</td>\n",
       "      <td>601.948669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-05</th>\n",
       "      <td>219.100006</td>\n",
       "      <td>2465.355957</td>\n",
       "      <td>821.674622</td>\n",
       "      <td>1002.476318</td>\n",
       "      <td>1541.577515</td>\n",
       "      <td>7811.684082</td>\n",
       "      <td>206.777695</td>\n",
       "      <td>1515.061157</td>\n",
       "      <td>932.819519</td>\n",
       "      <td>1424.507324</td>\n",
       "      <td>2852.809814</td>\n",
       "      <td>582.383667</td>\n",
       "      <td>3529.662354</td>\n",
       "      <td>1171.046021</td>\n",
       "      <td>1545.510376</td>\n",
       "      <td>17.150000</td>\n",
       "      <td>603.544678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-06</th>\n",
       "      <td>219.000000</td>\n",
       "      <td>2477.101074</td>\n",
       "      <td>827.200928</td>\n",
       "      <td>1000.178101</td>\n",
       "      <td>1633.619385</td>\n",
       "      <td>8127.747559</td>\n",
       "      <td>209.453003</td>\n",
       "      <td>1513.384155</td>\n",
       "      <td>937.132446</td>\n",
       "      <td>1439.351562</td>\n",
       "      <td>2857.134033</td>\n",
       "      <td>584.448975</td>\n",
       "      <td>3561.179199</td>\n",
       "      <td>1182.022217</td>\n",
       "      <td>1553.023071</td>\n",
       "      <td>17.299999</td>\n",
       "      <td>602.247925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-09</th>\n",
       "      <td>214.949997</td>\n",
       "      <td>2441.615479</td>\n",
       "      <td>786.674744</td>\n",
       "      <td>995.481750</td>\n",
       "      <td>1620.527710</td>\n",
       "      <td>7987.601562</td>\n",
       "      <td>205.999420</td>\n",
       "      <td>1495.823853</td>\n",
       "      <td>930.588745</td>\n",
       "      <td>1436.187988</td>\n",
       "      <td>2781.481689</td>\n",
       "      <td>575.449890</td>\n",
       "      <td>3577.847656</td>\n",
       "      <td>1177.893921</td>\n",
       "      <td>1556.256958</td>\n",
       "      <td>16.900000</td>\n",
       "      <td>599.704224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-10</th>\n",
       "      <td>219.800003</td>\n",
       "      <td>2497.292969</td>\n",
       "      <td>815.998962</td>\n",
       "      <td>1011.469360</td>\n",
       "      <td>1632.070312</td>\n",
       "      <td>8043.222168</td>\n",
       "      <td>208.480164</td>\n",
       "      <td>1504.307983</td>\n",
       "      <td>943.081238</td>\n",
       "      <td>1455.363892</td>\n",
       "      <td>2861.657471</td>\n",
       "      <td>581.891907</td>\n",
       "      <td>3568.554199</td>\n",
       "      <td>1192.561157</td>\n",
       "      <td>1574.118042</td>\n",
       "      <td>17.049999</td>\n",
       "      <td>598.507202</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-27</th>\n",
       "      <td>352.100006</td>\n",
       "      <td>3130.300049</td>\n",
       "      <td>1456.699951</td>\n",
       "      <td>1273.150024</td>\n",
       "      <td>2010.699951</td>\n",
       "      <td>7756.000000</td>\n",
       "      <td>249.600006</td>\n",
       "      <td>1752.650024</td>\n",
       "      <td>1306.599976</td>\n",
       "      <td>1906.750000</td>\n",
       "      <td>5437.000000</td>\n",
       "      <td>802.650024</td>\n",
       "      <td>4308.700195</td>\n",
       "      <td>1609.250000</td>\n",
       "      <td>2180.899902</td>\n",
       "      <td>22.740000</td>\n",
       "      <td>1075.949951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
       "      <td>349.200012</td>\n",
       "      <td>3135.850098</td>\n",
       "      <td>1448.199951</td>\n",
       "      <td>1232.199951</td>\n",
       "      <td>1973.400024</td>\n",
       "      <td>7703.000000</td>\n",
       "      <td>247.800003</td>\n",
       "      <td>1732.050049</td>\n",
       "      <td>1273.000000</td>\n",
       "      <td>1875.599976</td>\n",
       "      <td>5450.399902</td>\n",
       "      <td>787.900024</td>\n",
       "      <td>4268.500000</td>\n",
       "      <td>1577.199951</td>\n",
       "      <td>2175.449951</td>\n",
       "      <td>22.480000</td>\n",
       "      <td>1068.550049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-01</th>\n",
       "      <td>352.350006</td>\n",
       "      <td>3186.100098</td>\n",
       "      <td>1467.500000</td>\n",
       "      <td>1226.650024</td>\n",
       "      <td>1975.250000</td>\n",
       "      <td>7703.000000</td>\n",
       "      <td>248.910004</td>\n",
       "      <td>1726.199951</td>\n",
       "      <td>1274.400024</td>\n",
       "      <td>1904.349976</td>\n",
       "      <td>5487.750000</td>\n",
       "      <td>796.950012</td>\n",
       "      <td>4287.899902</td>\n",
       "      <td>1625.400024</td>\n",
       "      <td>2163.350098</td>\n",
       "      <td>22.420000</td>\n",
       "      <td>1080.349976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-03</th>\n",
       "      <td>344.350006</td>\n",
       "      <td>3116.000000</td>\n",
       "      <td>1425.199951</td>\n",
       "      <td>1175.699951</td>\n",
       "      <td>1913.400024</td>\n",
       "      <td>7433.850098</td>\n",
       "      <td>245.059998</td>\n",
       "      <td>1682.000000</td>\n",
       "      <td>1256.349976</td>\n",
       "      <td>1893.400024</td>\n",
       "      <td>5250.250000</td>\n",
       "      <td>794.099976</td>\n",
       "      <td>4232.750000</td>\n",
       "      <td>1604.050049</td>\n",
       "      <td>2147.350098</td>\n",
       "      <td>21.860001</td>\n",
       "      <td>1069.050049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-04</th>\n",
       "      <td>333.000000</td>\n",
       "      <td>3110.649902</td>\n",
       "      <td>1413.699951</td>\n",
       "      <td>1178.400024</td>\n",
       "      <td>1884.550049</td>\n",
       "      <td>7211.350098</td>\n",
       "      <td>250.589996</td>\n",
       "      <td>1657.650024</td>\n",
       "      <td>1239.750000</td>\n",
       "      <td>1918.150024</td>\n",
       "      <td>5141.299805</td>\n",
       "      <td>796.650024</td>\n",
       "      <td>4252.250000</td>\n",
       "      <td>1616.449951</td>\n",
       "      <td>2105.100098</td>\n",
       "      <td>21.950001</td>\n",
       "      <td>1057.349976</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>246 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ABFRL.NS  ADANIENT.NS  ADANIPORTS.NS  AXISBANK.NS  \\\n",
       "Date                                                              \n",
       "2023-10-04  214.250000  2463.956299     821.077148   994.782227   \n",
       "2023-10-05  219.100006  2465.355957     821.674622  1002.476318   \n",
       "2023-10-06  219.000000  2477.101074     827.200928  1000.178101   \n",
       "2023-10-09  214.949997  2441.615479     786.674744   995.481750   \n",
       "2023-10-10  219.800003  2497.292969     815.998962  1011.469360   \n",
       "...                ...          ...            ...          ...   \n",
       "2024-09-27  352.100006  3130.300049    1456.699951  1273.150024   \n",
       "2024-09-30  349.200012  3135.850098    1448.199951  1232.199951   \n",
       "2024-10-01  352.350006  3186.100098    1467.500000  1226.650024   \n",
       "2024-10-03  344.350006  3116.000000    1425.199951  1175.699951   \n",
       "2024-10-04  333.000000  3110.649902    1413.699951  1178.400024   \n",
       "\n",
       "            BAJAJFINSV.NS  BAJFINANCE.NS  BANKBARODA.NS  HDFCBANK.NS  \\\n",
       "Date                                                                   \n",
       "2023-10-04    1531.583740    7814.818359     206.631760  1508.944702   \n",
       "2023-10-05    1541.577515    7811.684082     206.777695  1515.061157   \n",
       "2023-10-06    1633.619385    8127.747559     209.453003  1513.384155   \n",
       "2023-10-09    1620.527710    7987.601562     205.999420  1495.823853   \n",
       "2023-10-10    1632.070312    8043.222168     208.480164  1504.307983   \n",
       "...                   ...            ...            ...          ...   \n",
       "2024-09-27    2010.699951    7756.000000     249.600006  1752.650024   \n",
       "2024-09-30    1973.400024    7703.000000     247.800003  1732.050049   \n",
       "2024-10-01    1975.250000    7703.000000     248.910004  1726.199951   \n",
       "2024-10-03    1913.400024    7433.850098     245.059998  1682.000000   \n",
       "2024-10-04    1884.550049    7211.350098     250.589996  1657.650024   \n",
       "\n",
       "            ICICIBANK.NS      INFY.NS  PERSISTENT.NS     SBIN.NS       TCS.NS  \\\n",
       "Date                                                                            \n",
       "2023-10-04    922.111694  1405.915527    2829.596924  576.580933  3478.920410   \n",
       "2023-10-05    932.819519  1424.507324    2852.809814  582.383667  3529.662354   \n",
       "2023-10-06    937.132446  1439.351562    2857.134033  584.448975  3561.179199   \n",
       "2023-10-09    930.588745  1436.187988    2781.481689  575.449890  3577.847656   \n",
       "2023-10-10    943.081238  1455.363892    2861.657471  581.891907  3568.554199   \n",
       "...                  ...          ...            ...         ...          ...   \n",
       "2024-09-27   1306.599976  1906.750000    5437.000000  802.650024  4308.700195   \n",
       "2024-09-30   1273.000000  1875.599976    5450.399902  787.900024  4268.500000   \n",
       "2024-10-01   1274.400024  1904.349976    5487.750000  796.950012  4287.899902   \n",
       "2024-10-03   1256.349976  1893.400024    5250.250000  794.099976  4232.750000   \n",
       "2024-10-04   1239.750000  1918.150024    5141.299805  796.650024  4252.250000   \n",
       "\n",
       "               TECHM.NS       UBL.NS  YESBANK.NS  ZYDUSLIFE.NS  \n",
       "Date                                                            \n",
       "2023-10-04  1170.463257  1541.729370   17.200001    601.948669  \n",
       "2023-10-05  1171.046021  1545.510376   17.150000    603.544678  \n",
       "2023-10-06  1182.022217  1553.023071   17.299999    602.247925  \n",
       "2023-10-09  1177.893921  1556.256958   16.900000    599.704224  \n",
       "2023-10-10  1192.561157  1574.118042   17.049999    598.507202  \n",
       "...                 ...          ...         ...           ...  \n",
       "2024-09-27  1609.250000  2180.899902   22.740000   1075.949951  \n",
       "2024-09-30  1577.199951  2175.449951   22.480000   1068.550049  \n",
       "2024-10-01  1625.400024  2163.350098   22.420000   1080.349976  \n",
       "2024-10-03  1604.050049  2147.350098   21.860001   1069.050049  \n",
       "2024-10-04  1616.449951  2105.100098   21.950001   1057.349976  \n",
       "\n",
       "[246 rows x 17 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import yfinance as yf\n",
    "\n",
    "\n",
    "pf_eq = yf.download(sks, period=\"1Y\")\n",
    "pf_eq = pf_eq[\"Adj Close\"]\n",
    "pf_eq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "id": "mVBFYfD4Ces8",
    "outputId": "f10b1c29-bdb5-4d60-cdb2-8e6acd1947e1"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "X_pf = pf_eq.pct_change(fill_method=None)\n",
    "\n",
    "X_pf = X_pf.ffill()\n",
    "X_pf = X_pf.bfill()\n",
    "\n",
    "names =pf_eq.columns\n",
    "# In general, it's a good idea to scale the data prior to PCA.\n",
    "scaler = StandardScaler()\n",
    "scaler.fit(X_pf)\n",
    "X=scaler.transform(X_pf)\n",
    "\n",
    "pca = PCA()\n",
    "x_new = pca.fit_transform(X_pf)\n",
    "\n",
    "#Call the function. Use only the 2 PCs.\n",
    "plt.figure(figsize=(20,15))\n",
    "kmeans = myplot(x_new[:,0:2],np.transpose(pca.components_[0:2, :]), names)\n"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}