exercise7-1_diabetes_deep_net.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from torch.utils.data import Dataset, DataLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DiabeteDataset(Dataset):\n",
    "    def __init__(self, csv_file, transform=None):\n",
    "        xy = np.loadtxt(csv_file, delimiter=',', dtype=np.float32, skiprows=1)\n",
    "        self.len = xy.shape[0]\n",
    "        self.x_data = torch.from_numpy(xy[:, 0:-1]).clone().detach()\n",
    "        self.y_data = torch.from_numpy(xy[:, [-1]]).clone().detach()\n",
    "    def __len__(self):\n",
    "        return self.len\n",
    "    def __getitem__(self, index):\n",
    "        return  self.x_data[index], bool(int(self.y_data[index]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# UCI\n",
    "https://github.com/MateLabs/Public-Datasets/blob/master/Datasets/diabetes.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sampler import ImbalancedDatasetSampler\n",
    "\n",
    "# train_dataset = DiabeteDataset('diabetes_train.csv') # 768 rows\n",
    "\n",
    "train_dataset = DiabeteDataset('diabetes_train.csv')\n",
    "test_dataset = DiabeteDataset('diabetes_test.csv')\n",
    "\n",
    "train_loader = DataLoader(train_dataset, sampler=ImbalancedDatasetSampler(train_dataset), batch_size=2, num_workers=2)\n",
    "test_loader = DataLoader(dataset=test_dataset, shuffle=True, num_workers=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "350"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "class ModelDeep(torch.nn.Module):\n",
    "    def __init__(self):\n",
    "        \"\"\"\n",
    "        Input layer is (8 , 8)\n",
    "        Hidder layer is (8, 8)\n",
    "        Ouput layser is (8, 1)\n",
    "        3 layers loss is ~5\n",
    "        8 layers loss is ~4\n",
    "        21 layer losss is ~4\n",
    "        \"\"\"\n",
    "        super().__init__()\n",
    "        self.l1 = torch.nn.Linear(8, 8)\n",
    "        self.l2 = torch.nn.Linear(8, 8)\n",
    "        self.l3 = torch.nn.Linear(8, 8)\n",
    "        self.l4 = torch.nn.Linear(8, 8)\n",
    "        self.l5 = torch.nn.Linear(8, 8)\n",
    "        self.l6 = torch.nn.Linear(8, 8)\n",
    "        self.l7 = torch.nn.Linear(8, 8)\n",
    "        self.l8 = torch.nn.Linear(8, 8)\n",
    "        self.l9 = torch.nn.Linear(8, 8)\n",
    "        self.l10 = torch.nn.Linear(8, 8)\n",
    "        self.l11 = torch.nn.Linear(8, 8)\n",
    "        self.l12 = torch.nn.Linear(8, 8)\n",
    "        self.l13 = torch.nn.Linear(8, 8)\n",
    "        self.l14 = torch.nn.Linear(8, 8)\n",
    "        self.l15 = torch.nn.Linear(8, 8)\n",
    "        self.l16 = torch.nn.Linear(8, 8)\n",
    "        self.l17 = torch.nn.Linear(8, 8)\n",
    "        self.l18 = torch.nn.Linear(8, 8)\n",
    "        self.l19 = torch.nn.Linear(8, 8)\n",
    "        self.l20 = torch.nn.Linear(8, 8)\n",
    "        self.l21 = torch.nn.Linear(8, 1)\n",
    "    \n",
    "        # Activation function\n",
    "        self.activation_fn = torch.nn.LeakyReLU()\n",
    "        self.sigmoid = torch.nn.Sigmoid()\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.activation_fn(self.l1(x))\n",
    "        x = self.activation_fn(self.l2(x))\n",
    "        x = self.activation_fn(self.l3(x))\n",
    "        x = self.activation_fn(self.l4(x))\n",
    "        x = self.activation_fn(self.l5(x))\n",
    "        x = self.activation_fn(self.l6(x))\n",
    "        x = self.activation_fn(self.l7(x))\n",
    "        x = self.activation_fn(self.l8(x))\n",
    "        x = self.activation_fn(self.l9(x))\n",
    "        x = self.activation_fn(self.l10(x))        \n",
    "        x = self.activation_fn(self.l11(x))\n",
    "        x = self.activation_fn(self.l12(x))        \n",
    "        x = self.activation_fn(self.l13(x))\n",
    "        x = self.activation_fn(self.l14(x))\n",
    "        x = self.activation_fn(self.l15(x))\n",
    "        x = self.activation_fn(self.l16(x))        \n",
    "        x = self.activation_fn(self.l17(x))\n",
    "        x = self.activation_fn(self.l18(x))        \n",
    "        x = self.activation_fn(self.l19(x))\n",
    "        x = self.activation_fn(self.l20(x))        \n",
    "        x = self.sigmoid(self.l21(x))\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ModelWide(torch.nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.l1 = torch.nn.Linear(8, 60)\n",
    "        self.l2 = torch.nn.Linear(60, 60)\n",
    "        self.l3 = torch.nn.Linear(60, 60)\n",
    "        self.l4 = torch.nn.Linear(60, 60)\n",
    "        self.l5 = torch.nn.Linear(60, 60)\n",
    "        self.l6 = torch.nn.Linear(60, 60)\n",
    "        self.l7 = torch.nn.Linear(60, 60)\n",
    "        self.l8 = torch.nn.Linear(60, 60)\n",
    "        self.l9 = torch.nn.Linear(60, 60)\n",
    "        self.l10 = torch.nn.Linear(60, 60)\n",
    "        self.l11 = torch.nn.Linear(60, 60)\n",
    "        self.l12 = torch.nn.Linear(60, 60)\n",
    "        self.l13 = torch.nn.Linear(60, 60)\n",
    "        self.l14 = torch.nn.Linear(60, 1)\n",
    "    \n",
    "        # Activation function\n",
    "        self.activation_fn = torch.nn.ReLU()\n",
    "    def forward(self, x):\n",
    "        x = self.activation_fn(self.l1(x))\n",
    "        x = self.activation_fn(self.l2(x))\n",
    "        x = self.activation_fn(self.l3(x))\n",
    "        x = self.activation_fn(self.l4(x))\n",
    "        x = self.activation_fn(self.l5(x))\n",
    "        x = self.activation_fn(self.l6(x))\n",
    "        x = self.activation_fn(self.l7(x))\n",
    "        x = self.activation_fn(self.l8(x))\n",
    "        x = self.activation_fn(self.l9(x))\n",
    "        x = self.activation_fn(self.l10(x))        \n",
    "        x = self.activation_fn(self.l11(x))\n",
    "        x = self.activation_fn(self.l12(x))        \n",
    "        x = self.activation_fn(self.l13(x))\n",
    "        x = self.activation_fn(self.l14(x))\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "class KopxionAkramsystems(torch.nn.Module):\n",
    "    \"\"\"\n",
    "    loss ~0.6\n",
    "    \"\"\"\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.l1 = torch.nn.Linear(8, 32)\n",
    "        self.l2 = torch.nn.Linear(32, 16)\n",
    "        self.l3 = torch.nn.Linear(16, 1)\n",
    "        self.activation_fn = torch.nn.LeakyReLU()\n",
    "        self.sigmoid = torch.nn.Sigmoid()\n",
    "    def forward(self, x):\n",
    "        x = self.activation_fn(self.l1(x))\n",
    "        x = self.activation_fn(self.l2(x))\n",
    "        x = self.sigmoid(self.l3(x))\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = ModelDeep()\n",
    "criterion = torch.nn.BCEWithLogitsLoss()\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 0 [0/700 (0%)]\tLoss: 0.472662\n",
      "Train Epoch: 0 [20/700 (3%)]\tLoss: 0.978356\n",
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      "Train Epoch: 4 [640/700 (91%)]\tLoss: 0.835746\n",
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      "Train Epoch: 4 [680/700 (97%)]\tLoss: 0.589661\n",
      "Train Epoch: 5 [0/700 (0%)]\tLoss: 0.975048\n",
      "Train Epoch: 5 [20/700 (3%)]\tLoss: 0.430225\n",
      "Train Epoch: 5 [40/700 (6%)]\tLoss: 0.682709\n",
      "Train Epoch: 5 [60/700 (9%)]\tLoss: 0.580927\n",
      "Train Epoch: 5 [80/700 (11%)]\tLoss: 0.807306\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 5 [100/700 (14%)]\tLoss: 0.991527\n",
      "Train Epoch: 5 [120/700 (17%)]\tLoss: 0.741051\n",
      "Train Epoch: 5 [140/700 (20%)]\tLoss: 0.673577\n",
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      "Train Epoch: 9 [600/700 (86%)]\tLoss: 0.344031\n",
      "Train Epoch: 9 [620/700 (89%)]\tLoss: 0.507771\n",
      "Train Epoch: 9 [640/700 (91%)]\tLoss: 0.353375\n",
      "Train Epoch: 9 [660/700 (94%)]\tLoss: 0.421585\n",
      "Train Epoch: 9 [680/700 (97%)]\tLoss: 0.694327\n"
     ]
    }
   ],
   "source": [
    "# Training\n",
    "model.train()\n",
    "for epoch in range(10):\n",
    "    for batch_idx, (data, target) in enumerate(train_loader):\n",
    "        optimizer.zero_grad()\n",
    "        output = model(data)\n",
    "        resized_target = target.view(output.shape[0], -1)\n",
    "        loss = criterion(output, resized_target.float())\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if batch_idx % 10 == 0:\n",
    "            print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
    "                epoch, batch_idx * len(data), len(train_loader.dataset),\n",
    "                100. * batch_idx / len(train_loader), loss.item()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import torch.nn.functional as F\n",
    "import matplotlib.pyplot as plt\n",
    "import itertools\n",
    "\n",
    "\n",
    "classes = (True, False)\n",
    "\n",
    "def boolean_output(output):\n",
    "    return bool(output.view(1) > torch.tensor([0.5]))\n",
    "\n",
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.Blues):\n",
    "    \"\"\"\n",
    "    This function prints and plots the confusion matrix.\n",
    "    Normalization can be applied by setting `normalize=True`.\n",
    "    \"\"\"\n",
    "    print(cm)\n",
    "    plt.figure(figsize=(10, 10))\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "\n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt),\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.tight_layout()\n",
    "\n",
    "def test(model, device, test_loader):\n",
    "    model.eval()\n",
    "    test_loss = 0\n",
    "    correct = 0\n",
    "    y_test = []\n",
    "    y_pred = []\n",
    "    with torch.no_grad():\n",
    "        for data, target in test_loader:\n",
    "            data, target = data.to(device), target.to(device)\n",
    "            output = model(data)\n",
    "            bool_output = boolean_output(output)\n",
    "            bool_target = bool(target)\n",
    "            y_test.append(bool_target)\n",
    "            y_pred.append(bool_output)\n",
    "            if bool_output == bool_target:\n",
    "                correct += 1\n",
    "    accuracy = correct/len(test_loader.dataset)\n",
    "    print(f\"accuracy: {accuracy}\")\n",
    "    # Confusion matrix\n",
    "    confusion_mtx = confusion_matrix(y_test, y_pred)\n",
    "    plot_confusion_matrix(confusion_mtx, classes=classes, normalize=True,\n",
    "                          title='Confusion matrix')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy: 0.6764705882352942\n",
      "[[37  4]\n",
      " [18  9]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test(model, \"cpu\", test_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('diabetes.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "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>Number of times pregnant</th>\n",
       "      <th>Plasma glucose concentration</th>\n",
       "      <th>Diastolic blood pressure</th>\n",
       "      <th>Triceps skin fold thickness</th>\n",
       "      <th>2-Hour serum insulin</th>\n",
       "      <th>Body mass index</th>\n",
       "      <th>Diabetes pedigree function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>116</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25.6</td>\n",
       "      <td>0.201</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3</td>\n",
       "      <td>78</td>\n",
       "      <td>50</td>\n",
       "      <td>32</td>\n",
       "      <td>88</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.248</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.3</td>\n",
       "      <td>0.134</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2</td>\n",
       "      <td>197</td>\n",
       "      <td>70</td>\n",
       "      <td>45</td>\n",
       "      <td>543</td>\n",
       "      <td>30.5</td>\n",
       "      <td>0.158</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>125</td>\n",
       "      <td>96</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.232</td>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4</td>\n",
       "      <td>110</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37.6</td>\n",
       "      <td>0.191</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10</td>\n",
       "      <td>168</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.537</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10</td>\n",
       "      <td>139</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.1</td>\n",
       "      <td>1.441</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1</td>\n",
       "      <td>189</td>\n",
       "      <td>60</td>\n",
       "      <td>23</td>\n",
       "      <td>846</td>\n",
       "      <td>30.1</td>\n",
       "      <td>0.398</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5</td>\n",
       "      <td>166</td>\n",
       "      <td>72</td>\n",
       "      <td>19</td>\n",
       "      <td>175</td>\n",
       "      <td>25.8</td>\n",
       "      <td>0.587</td>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.484</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>118</td>\n",
       "      <td>84</td>\n",
       "      <td>47</td>\n",
       "      <td>230</td>\n",
       "      <td>45.8</td>\n",
       "      <td>0.551</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7</td>\n",
       "      <td>107</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>29.6</td>\n",
       "      <td>0.254</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>103</td>\n",
       "      <td>30</td>\n",
       "      <td>38</td>\n",
       "      <td>83</td>\n",
       "      <td>43.3</td>\n",
       "      <td>0.183</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1</td>\n",
       "      <td>115</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>96</td>\n",
       "      <td>34.6</td>\n",
       "      <td>0.529</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>3</td>\n",
       "      <td>126</td>\n",
       "      <td>88</td>\n",
       "      <td>41</td>\n",
       "      <td>235</td>\n",
       "      <td>39.3</td>\n",
       "      <td>0.704</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8</td>\n",
       "      <td>99</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.4</td>\n",
       "      <td>0.388</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>7</td>\n",
       "      <td>196</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39.8</td>\n",
       "      <td>0.451</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>9</td>\n",
       "      <td>119</td>\n",
       "      <td>80</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.263</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>11</td>\n",
       "      <td>143</td>\n",
       "      <td>94</td>\n",
       "      <td>33</td>\n",
       "      <td>146</td>\n",
       "      <td>36.6</td>\n",
       "      <td>0.254</td>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10</td>\n",
       "      <td>125</td>\n",
       "      <td>70</td>\n",
       "      <td>26</td>\n",
       "      <td>115</td>\n",
       "      <td>31.1</td>\n",
       "      <td>0.205</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7</td>\n",
       "      <td>147</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39.4</td>\n",
       "      <td>0.257</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>97</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>140</td>\n",
       "      <td>23.2</td>\n",
       "      <td>0.487</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>13</td>\n",
       "      <td>145</td>\n",
       "      <td>82</td>\n",
       "      <td>19</td>\n",
       "      <td>110</td>\n",
       "      <td>22.2</td>\n",
       "      <td>0.245</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>5</td>\n",
       "      <td>117</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34.1</td>\n",
       "      <td>0.337</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>738</th>\n",
       "      <td>2</td>\n",
       "      <td>99</td>\n",
       "      <td>60</td>\n",
       "      <td>17</td>\n",
       "      <td>160</td>\n",
       "      <td>36.6</td>\n",
       "      <td>0.453</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>739</th>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39.5</td>\n",
       "      <td>0.293</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>740</th>\n",
       "      <td>11</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>37</td>\n",
       "      <td>150</td>\n",
       "      <td>42.3</td>\n",
       "      <td>0.785</td>\n",
       "      <td>48</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>3</td>\n",
       "      <td>102</td>\n",
       "      <td>44</td>\n",
       "      <td>20</td>\n",
       "      <td>94</td>\n",
       "      <td>30.8</td>\n",
       "      <td>0.400</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>1</td>\n",
       "      <td>109</td>\n",
       "      <td>58</td>\n",
       "      <td>18</td>\n",
       "      <td>116</td>\n",
       "      <td>28.5</td>\n",
       "      <td>0.219</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>9</td>\n",
       "      <td>140</td>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32.7</td>\n",
       "      <td>0.734</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>13</td>\n",
       "      <td>153</td>\n",
       "      <td>88</td>\n",
       "      <td>37</td>\n",
       "      <td>140</td>\n",
       "      <td>40.6</td>\n",
       "      <td>1.174</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>745</th>\n",
       "      <td>12</td>\n",
       "      <td>100</td>\n",
       "      <td>84</td>\n",
       "      <td>33</td>\n",
       "      <td>105</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.488</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>1</td>\n",
       "      <td>147</td>\n",
       "      <td>94</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>49.3</td>\n",
       "      <td>0.358</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>747</th>\n",
       "      <td>1</td>\n",
       "      <td>81</td>\n",
       "      <td>74</td>\n",
       "      <td>41</td>\n",
       "      <td>57</td>\n",
       "      <td>46.3</td>\n",
       "      <td>1.096</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>748</th>\n",
       "      <td>3</td>\n",
       "      <td>187</td>\n",
       "      <td>70</td>\n",
       "      <td>22</td>\n",
       "      <td>200</td>\n",
       "      <td>36.4</td>\n",
       "      <td>0.408</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749</th>\n",
       "      <td>6</td>\n",
       "      <td>162</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24.3</td>\n",
       "      <td>0.178</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>750</th>\n",
       "      <td>4</td>\n",
       "      <td>136</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31.2</td>\n",
       "      <td>1.182</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>1</td>\n",
       "      <td>121</td>\n",
       "      <td>78</td>\n",
       "      <td>39</td>\n",
       "      <td>74</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.261</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>3</td>\n",
       "      <td>108</td>\n",
       "      <td>62</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.223</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>0</td>\n",
       "      <td>181</td>\n",
       "      <td>88</td>\n",
       "      <td>44</td>\n",
       "      <td>510</td>\n",
       "      <td>43.3</td>\n",
       "      <td>0.222</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>8</td>\n",
       "      <td>154</td>\n",
       "      <td>78</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>32.4</td>\n",
       "      <td>0.443</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>1</td>\n",
       "      <td>128</td>\n",
       "      <td>88</td>\n",
       "      <td>39</td>\n",
       "      <td>110</td>\n",
       "      <td>36.5</td>\n",
       "      <td>1.057</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756</th>\n",
       "      <td>7</td>\n",
       "      <td>137</td>\n",
       "      <td>90</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.391</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>757</th>\n",
       "      <td>0</td>\n",
       "      <td>123</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>36.3</td>\n",
       "      <td>0.258</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758</th>\n",
       "      <td>1</td>\n",
       "      <td>106</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37.5</td>\n",
       "      <td>0.197</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>6</td>\n",
       "      <td>190</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.5</td>\n",
       "      <td>0.278</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>2</td>\n",
       "      <td>88</td>\n",
       "      <td>58</td>\n",
       "      <td>26</td>\n",
       "      <td>16</td>\n",
       "      <td>28.4</td>\n",
       "      <td>0.766</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>9</td>\n",
       "      <td>170</td>\n",
       "      <td>74</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.403</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>9</td>\n",
       "      <td>89</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>0.142</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>763</th>\n",
       "      <td>10</td>\n",
       "      <td>101</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>180</td>\n",
       "      <td>32.9</td>\n",
       "      <td>0.171</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>764</th>\n",
       "      <td>2</td>\n",
       "      <td>122</td>\n",
       "      <td>70</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>36.8</td>\n",
       "      <td>0.340</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>765</th>\n",
       "      <td>5</td>\n",
       "      <td>121</td>\n",
       "      <td>72</td>\n",
       "      <td>23</td>\n",
       "      <td>112</td>\n",
       "      <td>26.2</td>\n",
       "      <td>0.245</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>1</td>\n",
       "      <td>126</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.1</td>\n",
       "      <td>0.349</td>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>1</td>\n",
       "      <td>93</td>\n",
       "      <td>70</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>30.4</td>\n",
       "      <td>0.315</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>768 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Number of times pregnant  Plasma glucose concentration  \\\n",
       "0                           6                           148   \n",
       "1                           1                            85   \n",
       "2                           8                           183   \n",
       "3                           1                            89   \n",
       "4                           0                           137   \n",
       "5                           5                           116   \n",
       "6                           3                            78   \n",
       "7                          10                           115   \n",
       "8                           2                           197   \n",
       "9                           8                           125   \n",
       "10                          4                           110   \n",
       "11                         10                           168   \n",
       "12                         10                           139   \n",
       "13                          1                           189   \n",
       "14                          5                           166   \n",
       "15                          7                           100   \n",
       "16                          0                           118   \n",
       "17                          7                           107   \n",
       "18                          1                           103   \n",
       "19                          1                           115   \n",
       "20                          3                           126   \n",
       "21                          8                            99   \n",
       "22                          7                           196   \n",
       "23                          9                           119   \n",
       "24                         11                           143   \n",
       "25                         10                           125   \n",
       "26                          7                           147   \n",
       "27                          1                            97   \n",
       "28                         13                           145   \n",
       "29                          5                           117   \n",
       "..                        ...                           ...   \n",
       "738                         2                            99   \n",
       "739                         1                           102   \n",
       "740                        11                           120   \n",
       "741                         3                           102   \n",
       "742                         1                           109   \n",
       "743                         9                           140   \n",
       "744                        13                           153   \n",
       "745                        12                           100   \n",
       "746                         1                           147   \n",
       "747                         1                            81   \n",
       "748                         3                           187   \n",
       "749                         6                           162   \n",
       "750                         4                           136   \n",
       "751                         1                           121   \n",
       "752                         3                           108   \n",
       "753                         0                           181   \n",
       "754                         8                           154   \n",
       "755                         1                           128   \n",
       "756                         7                           137   \n",
       "757                         0                           123   \n",
       "758                         1                           106   \n",
       "759                         6                           190   \n",
       "760                         2                            88   \n",
       "761                         9                           170   \n",
       "762                         9                            89   \n",
       "763                        10                           101   \n",
       "764                         2                           122   \n",
       "765                         5                           121   \n",
       "766                         1                           126   \n",
       "767                         1                            93   \n",
       "\n",
       "     Diastolic blood pressure  Triceps skin fold thickness  \\\n",
       "0                          72                           35   \n",
       "1                          66                           29   \n",
       "2                          64                            0   \n",
       "3                          66                           23   \n",
       "4                          40                           35   \n",
       "5                          74                            0   \n",
       "6                          50                           32   \n",
       "7                           0                            0   \n",
       "8                          70                           45   \n",
       "9                          96                            0   \n",
       "10                         92                            0   \n",
       "11                         74                            0   \n",
       "12                         80                            0   \n",
       "13                         60                           23   \n",
       "14                         72                           19   \n",
       "15                          0                            0   \n",
       "16                         84                           47   \n",
       "17                         74                            0   \n",
       "18                         30                           38   \n",
       "19                         70                           30   \n",
       "20                         88                           41   \n",
       "21                         84                            0   \n",
       "22                         90                            0   \n",
       "23                         80                           35   \n",
       "24                         94                           33   \n",
       "25                         70                           26   \n",
       "26                         76                            0   \n",
       "27                         66                           15   \n",
       "28                         82                           19   \n",
       "29                         92                            0   \n",
       "..                        ...                          ...   \n",
       "738                        60                           17   \n",
       "739                        74                            0   \n",
       "740                        80                           37   \n",
       "741                        44                           20   \n",
       "742                        58                           18   \n",
       "743                        94                            0   \n",
       "744                        88                           37   \n",
       "745                        84                           33   \n",
       "746                        94                           41   \n",
       "747                        74                           41   \n",
       "748                        70                           22   \n",
       "749                        62                            0   \n",
       "750                        70                            0   \n",
       "751                        78                           39   \n",
       "752                        62                           24   \n",
       "753                        88                           44   \n",
       "754                        78                           32   \n",
       "755                        88                           39   \n",
       "756                        90                           41   \n",
       "757                        72                            0   \n",
       "758                        76                            0   \n",
       "759                        92                            0   \n",
       "760                        58                           26   \n",
       "761                        74                           31   \n",
       "762                        62                            0   \n",
       "763                        76                           48   \n",
       "764                        70                           27   \n",
       "765                        72                           23   \n",
       "766                        60                            0   \n",
       "767                        70                           31   \n",
       "\n",
       "     2-Hour serum insulin  Body mass index  Diabetes pedigree function  Age  \\\n",
       "0                       0             33.6                       0.627   50   \n",
       "1                       0             26.6                       0.351   31   \n",
       "2                       0             23.3                       0.672   32   \n",
       "3                      94             28.1                       0.167   21   \n",
       "4                     168             43.1                       2.288   33   \n",
       "5                       0             25.6                       0.201   30   \n",
       "6                      88             31.0                       0.248   26   \n",
       "7                       0             35.3                       0.134   29   \n",
       "8                     543             30.5                       0.158   53   \n",
       "9                       0              0.0                       0.232   54   \n",
       "10                      0             37.6                       0.191   30   \n",
       "11                      0             38.0                       0.537   34   \n",
       "12                      0             27.1                       1.441   57   \n",
       "13                    846             30.1                       0.398   59   \n",
       "14                    175             25.8                       0.587   51   \n",
       "15                      0             30.0                       0.484   32   \n",
       "16                    230             45.8                       0.551   31   \n",
       "17                      0             29.6                       0.254   31   \n",
       "18                     83             43.3                       0.183   33   \n",
       "19                     96             34.6                       0.529   32   \n",
       "20                    235             39.3                       0.704   27   \n",
       "21                      0             35.4                       0.388   50   \n",
       "22                      0             39.8                       0.451   41   \n",
       "23                      0             29.0                       0.263   29   \n",
       "24                    146             36.6                       0.254   51   \n",
       "25                    115             31.1                       0.205   41   \n",
       "26                      0             39.4                       0.257   43   \n",
       "27                    140             23.2                       0.487   22   \n",
       "28                    110             22.2                       0.245   57   \n",
       "29                      0             34.1                       0.337   38   \n",
       "..                    ...              ...                         ...  ...   \n",
       "738                   160             36.6                       0.453   21   \n",
       "739                     0             39.5                       0.293   42   \n",
       "740                   150             42.3                       0.785   48   \n",
       "741                    94             30.8                       0.400   26   \n",
       "742                   116             28.5                       0.219   22   \n",
       "743                     0             32.7                       0.734   45   \n",
       "744                   140             40.6                       1.174   39   \n",
       "745                   105             30.0                       0.488   46   \n",
       "746                     0             49.3                       0.358   27   \n",
       "747                    57             46.3                       1.096   32   \n",
       "748                   200             36.4                       0.408   36   \n",
       "749                     0             24.3                       0.178   50   \n",
       "750                     0             31.2                       1.182   22   \n",
       "751                    74             39.0                       0.261   28   \n",
       "752                     0             26.0                       0.223   25   \n",
       "753                   510             43.3                       0.222   26   \n",
       "754                     0             32.4                       0.443   45   \n",
       "755                   110             36.5                       1.057   37   \n",
       "756                     0             32.0                       0.391   39   \n",
       "757                     0             36.3                       0.258   52   \n",
       "758                     0             37.5                       0.197   26   \n",
       "759                     0             35.5                       0.278   66   \n",
       "760                    16             28.4                       0.766   22   \n",
       "761                     0             44.0                       0.403   43   \n",
       "762                     0             22.5                       0.142   33   \n",
       "763                   180             32.9                       0.171   63   \n",
       "764                     0             36.8                       0.340   27   \n",
       "765                   112             26.2                       0.245   30   \n",
       "766                     0             30.1                       0.349   47   \n",
       "767                     0             30.4                       0.315   23   \n",
       "\n",
       "     Class  \n",
       "0        1  \n",
       "1        0  \n",
       "2        1  \n",
       "3        0  \n",
       "4        1  \n",
       "5        0  \n",
       "6        1  \n",
       "7        0  \n",
       "8        1  \n",
       "9        1  \n",
       "10       0  \n",
       "11       1  \n",
       "12       0  \n",
       "13       1  \n",
       "14       1  \n",
       "15       1  \n",
       "16       1  \n",
       "17       1  \n",
       "18       0  \n",
       "19       1  \n",
       "20       0  \n",
       "21       0  \n",
       "22       1  \n",
       "23       1  \n",
       "24       1  \n",
       "25       1  \n",
       "26       1  \n",
       "27       0  \n",
       "28       0  \n",
       "29       0  \n",
       "..     ...  \n",
       "738      0  \n",
       "739      1  \n",
       "740      1  \n",
       "741      0  \n",
       "742      0  \n",
       "743      1  \n",
       "744      0  \n",
       "745      0  \n",
       "746      1  \n",
       "747      0  \n",
       "748      1  \n",
       "749      1  \n",
       "750      1  \n",
       "751      0  \n",
       "752      0  \n",
       "753      1  \n",
       "754      1  \n",
       "755      1  \n",
       "756      0  \n",
       "757      1  \n",
       "758      0  \n",
       "759      1  \n",
       "760      0  \n",
       "761      1  \n",
       "762      0  \n",
       "763      0  \n",
       "764      0  \n",
       "765      0  \n",
       "766      1  \n",
       "767      0  \n",
       "\n",
       "[768 rows x 9 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_df=(df-df.mean())/df.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>Number of times pregnant</th>\n",
       "      <th>Plasma glucose concentration</th>\n",
       "      <th>Diastolic blood pressure</th>\n",
       "      <th>Triceps skin fold thickness</th>\n",
       "      <th>2-Hour serum insulin</th>\n",
       "      <th>Body mass index</th>\n",
       "      <th>Diabetes pedigree function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.639530</td>\n",
       "      <td>0.847771</td>\n",
       "      <td>0.149543</td>\n",
       "      <td>0.906679</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.203880</td>\n",
       "      <td>0.468187</td>\n",
       "      <td>1.425067</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-1.122665</td>\n",
       "      <td>-0.160441</td>\n",
       "      <td>0.530556</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.683976</td>\n",
       "      <td>-0.364823</td>\n",
       "      <td>-0.190548</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.233077</td>\n",
       "      <td>1.942458</td>\n",
       "      <td>-0.263769</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-1.102537</td>\n",
       "      <td>0.604004</td>\n",
       "      <td>-0.105515</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.997558</td>\n",
       "      <td>-0.160441</td>\n",
       "      <td>0.154433</td>\n",
       "      <td>0.123221</td>\n",
       "      <td>-0.493721</td>\n",
       "      <td>-0.920163</td>\n",
       "      <td>-1.040871</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.141108</td>\n",
       "      <td>0.503727</td>\n",
       "      <td>-1.503707</td>\n",
       "      <td>0.906679</td>\n",
       "      <td>0.765337</td>\n",
       "      <td>1.408828</td>\n",
       "      <td>5.481337</td>\n",
       "      <td>-0.020483</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.342757</td>\n",
       "      <td>-0.153085</td>\n",
       "      <td>0.252871</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.810813</td>\n",
       "      <td>-0.817546</td>\n",
       "      <td>-0.275580</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-0.250789</td>\n",
       "      <td>-1.341602</td>\n",
       "      <td>-0.987066</td>\n",
       "      <td>0.718617</td>\n",
       "      <td>0.071158</td>\n",
       "      <td>-0.125895</td>\n",
       "      <td>-0.675693</td>\n",
       "      <td>-0.615709</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.826623</td>\n",
       "      <td>-0.184362</td>\n",
       "      <td>-3.570271</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.419502</td>\n",
       "      <td>-1.019762</td>\n",
       "      <td>-0.360612</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.547562</td>\n",
       "      <td>2.380333</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>1.533551</td>\n",
       "      <td>4.019303</td>\n",
       "      <td>-0.189314</td>\n",
       "      <td>-0.947326</td>\n",
       "      <td>1.680164</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.233077</td>\n",
       "      <td>0.128406</td>\n",
       "      <td>1.389481</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-4.057829</td>\n",
       "      <td>-0.723983</td>\n",
       "      <td>1.765196</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.045984</td>\n",
       "      <td>-0.340746</td>\n",
       "      <td>1.182825</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.711226</td>\n",
       "      <td>-0.847727</td>\n",
       "      <td>-0.275580</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.826623</td>\n",
       "      <td>1.473307</td>\n",
       "      <td>0.252871</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.761961</td>\n",
       "      <td>0.196553</td>\n",
       "      <td>0.064549</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.826623</td>\n",
       "      <td>0.566280</td>\n",
       "      <td>0.562856</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.620558</td>\n",
       "      <td>2.924962</td>\n",
       "      <td>2.020293</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>2.130119</td>\n",
       "      <td>-0.470426</td>\n",
       "      <td>0.154433</td>\n",
       "      <td>6.648507</td>\n",
       "      <td>-0.240048</td>\n",
       "      <td>-0.222970</td>\n",
       "      <td>2.190358</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.342757</td>\n",
       "      <td>1.410753</td>\n",
       "      <td>0.149543</td>\n",
       "      <td>-0.096316</td>\n",
       "      <td>0.826078</td>\n",
       "      <td>-0.785445</td>\n",
       "      <td>0.347461</td>\n",
       "      <td>1.510099</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.936304</td>\n",
       "      <td>-0.653513</td>\n",
       "      <td>-3.570271</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.252732</td>\n",
       "      <td>0.036591</td>\n",
       "      <td>-0.105515</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-1.141108</td>\n",
       "      <td>-0.090532</td>\n",
       "      <td>0.769512</td>\n",
       "      <td>1.658926</td>\n",
       "      <td>1.303326</td>\n",
       "      <td>1.751286</td>\n",
       "      <td>0.238807</td>\n",
       "      <td>-0.190548</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.936304</td>\n",
       "      <td>-0.434576</td>\n",
       "      <td>0.252871</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.303466</td>\n",
       "      <td>-0.657584</td>\n",
       "      <td>-0.190548</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.559683</td>\n",
       "      <td>-2.020348</td>\n",
       "      <td>1.094741</td>\n",
       "      <td>0.027772</td>\n",
       "      <td>1.434195</td>\n",
       "      <td>-0.871873</td>\n",
       "      <td>-0.020483</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.184362</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>0.593243</td>\n",
       "      <td>0.140576</td>\n",
       "      <td>0.330716</td>\n",
       "      <td>0.172408</td>\n",
       "      <td>-0.105515</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-0.250789</td>\n",
       "      <td>0.159683</td>\n",
       "      <td>0.976169</td>\n",
       "      <td>1.282802</td>\n",
       "      <td>1.346712</td>\n",
       "      <td>0.926848</td>\n",
       "      <td>0.700585</td>\n",
       "      <td>-0.530677</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1.233077</td>\n",
       "      <td>-0.684790</td>\n",
       "      <td>0.769512</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.432186</td>\n",
       "      <td>-0.253151</td>\n",
       "      <td>1.425067</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.936304</td>\n",
       "      <td>2.349056</td>\n",
       "      <td>1.079497</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.990267</td>\n",
       "      <td>-0.063008</td>\n",
       "      <td>0.659776</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1.529850</td>\n",
       "      <td>-0.059255</td>\n",
       "      <td>0.562856</td>\n",
       "      <td>0.906679</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.379568</td>\n",
       "      <td>-0.630420</td>\n",
       "      <td>-0.360612</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2.123396</td>\n",
       "      <td>0.691388</td>\n",
       "      <td>1.286153</td>\n",
       "      <td>0.781305</td>\n",
       "      <td>0.574438</td>\n",
       "      <td>0.584390</td>\n",
       "      <td>-0.657584</td>\n",
       "      <td>1.510099</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.826623</td>\n",
       "      <td>0.128406</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>0.342494</td>\n",
       "      <td>0.305443</td>\n",
       "      <td>-0.113212</td>\n",
       "      <td>-0.805473</td>\n",
       "      <td>0.659776</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.936304</td>\n",
       "      <td>0.816495</td>\n",
       "      <td>0.356200</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.939532</td>\n",
       "      <td>-0.648529</td>\n",
       "      <td>0.829840</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.747344</td>\n",
       "      <td>-0.160441</td>\n",
       "      <td>-0.347065</td>\n",
       "      <td>0.522374</td>\n",
       "      <td>-1.115221</td>\n",
       "      <td>0.045646</td>\n",
       "      <td>-0.955839</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2.716942</td>\n",
       "      <td>0.753941</td>\n",
       "      <td>0.666184</td>\n",
       "      <td>-0.096316</td>\n",
       "      <td>0.262057</td>\n",
       "      <td>-1.242057</td>\n",
       "      <td>-0.684747</td>\n",
       "      <td>2.020293</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.342757</td>\n",
       "      <td>-0.121808</td>\n",
       "      <td>1.182825</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.267298</td>\n",
       "      <td>-0.407077</td>\n",
       "      <td>0.404679</td>\n",
       "      <td>-0.731643</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>738</th>\n",
       "      <td>-0.547562</td>\n",
       "      <td>-0.684790</td>\n",
       "      <td>-0.470426</td>\n",
       "      <td>-0.221691</td>\n",
       "      <td>0.695919</td>\n",
       "      <td>0.584390</td>\n",
       "      <td>-0.056972</td>\n",
       "      <td>-1.040871</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>739</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.590960</td>\n",
       "      <td>0.252871</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.952216</td>\n",
       "      <td>-0.539876</td>\n",
       "      <td>0.744808</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>740</th>\n",
       "      <td>2.123396</td>\n",
       "      <td>-0.027978</td>\n",
       "      <td>0.562856</td>\n",
       "      <td>1.032053</td>\n",
       "      <td>0.609147</td>\n",
       "      <td>1.307358</td>\n",
       "      <td>0.945055</td>\n",
       "      <td>1.255002</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>-0.250789</td>\n",
       "      <td>-0.590960</td>\n",
       "      <td>-1.297051</td>\n",
       "      <td>-0.033629</td>\n",
       "      <td>0.123221</td>\n",
       "      <td>-0.151263</td>\n",
       "      <td>-0.216934</td>\n",
       "      <td>-0.615709</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.372022</td>\n",
       "      <td>-0.573754</td>\n",
       "      <td>-0.159003</td>\n",
       "      <td>0.314121</td>\n",
       "      <td>-0.442987</td>\n",
       "      <td>-0.763219</td>\n",
       "      <td>-0.955839</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>1.529850</td>\n",
       "      <td>0.597557</td>\n",
       "      <td>1.286153</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.089727</td>\n",
       "      <td>0.791129</td>\n",
       "      <td>0.999905</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>2.716942</td>\n",
       "      <td>1.004155</td>\n",
       "      <td>0.976169</td>\n",
       "      <td>1.032053</td>\n",
       "      <td>0.522374</td>\n",
       "      <td>1.091736</td>\n",
       "      <td>2.119116</td>\n",
       "      <td>0.489711</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>745</th>\n",
       "      <td>2.420169</td>\n",
       "      <td>-0.653513</td>\n",
       "      <td>0.769512</td>\n",
       "      <td>0.781305</td>\n",
       "      <td>0.218671</td>\n",
       "      <td>-0.252732</td>\n",
       "      <td>0.048664</td>\n",
       "      <td>1.084937</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>0.816495</td>\n",
       "      <td>1.286153</td>\n",
       "      <td>1.282802</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>2.195214</td>\n",
       "      <td>-0.343696</td>\n",
       "      <td>-0.530677</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>747</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-1.247772</td>\n",
       "      <td>0.252871</td>\n",
       "      <td>1.282802</td>\n",
       "      <td>-0.197837</td>\n",
       "      <td>1.814705</td>\n",
       "      <td>1.883700</td>\n",
       "      <td>-0.105515</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>748</th>\n",
       "      <td>-0.250789</td>\n",
       "      <td>2.067565</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>0.091745</td>\n",
       "      <td>1.043009</td>\n",
       "      <td>0.559022</td>\n",
       "      <td>-0.192788</td>\n",
       "      <td>0.234614</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749</th>\n",
       "      <td>0.639530</td>\n",
       "      <td>1.285646</td>\n",
       "      <td>-0.367098</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.975700</td>\n",
       "      <td>-0.886963</td>\n",
       "      <td>1.425067</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>750</th>\n",
       "      <td>0.045984</td>\n",
       "      <td>0.472450</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.100528</td>\n",
       "      <td>2.143261</td>\n",
       "      <td>-0.955839</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>0.003299</td>\n",
       "      <td>0.459528</td>\n",
       "      <td>1.157428</td>\n",
       "      <td>-0.050323</td>\n",
       "      <td>0.888797</td>\n",
       "      <td>-0.636457</td>\n",
       "      <td>-0.445645</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>-0.250789</td>\n",
       "      <td>-0.403299</td>\n",
       "      <td>-0.367098</td>\n",
       "      <td>0.217120</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.760078</td>\n",
       "      <td>-0.751146</td>\n",
       "      <td>-0.700742</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>-1.141108</td>\n",
       "      <td>1.879904</td>\n",
       "      <td>0.976169</td>\n",
       "      <td>1.470864</td>\n",
       "      <td>3.732954</td>\n",
       "      <td>1.434195</td>\n",
       "      <td>-0.754165</td>\n",
       "      <td>-0.615709</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>1.233077</td>\n",
       "      <td>1.035432</td>\n",
       "      <td>0.459528</td>\n",
       "      <td>0.718617</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.051676</td>\n",
       "      <td>-0.087153</td>\n",
       "      <td>0.999905</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>0.222236</td>\n",
       "      <td>0.976169</td>\n",
       "      <td>1.157428</td>\n",
       "      <td>0.262057</td>\n",
       "      <td>0.571706</td>\n",
       "      <td>1.765992</td>\n",
       "      <td>0.319646</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756</th>\n",
       "      <td>0.936304</td>\n",
       "      <td>0.503727</td>\n",
       "      <td>1.079497</td>\n",
       "      <td>1.282802</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.000941</td>\n",
       "      <td>-0.244097</td>\n",
       "      <td>0.489711</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>757</th>\n",
       "      <td>-1.141108</td>\n",
       "      <td>0.065852</td>\n",
       "      <td>0.149543</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.546339</td>\n",
       "      <td>-0.645511</td>\n",
       "      <td>1.595131</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.465853</td>\n",
       "      <td>0.356200</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.698543</td>\n",
       "      <td>-0.829618</td>\n",
       "      <td>-0.615709</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>0.639530</td>\n",
       "      <td>2.161395</td>\n",
       "      <td>1.182825</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.444869</td>\n",
       "      <td>-0.585148</td>\n",
       "      <td>2.785584</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>-0.547562</td>\n",
       "      <td>-1.028834</td>\n",
       "      <td>-0.573754</td>\n",
       "      <td>0.342494</td>\n",
       "      <td>-0.553603</td>\n",
       "      <td>-0.455670</td>\n",
       "      <td>0.887710</td>\n",
       "      <td>-0.955839</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>1.529850</td>\n",
       "      <td>1.535860</td>\n",
       "      <td>0.252871</td>\n",
       "      <td>0.655930</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>1.522980</td>\n",
       "      <td>-0.207879</td>\n",
       "      <td>0.829840</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>1.529850</td>\n",
       "      <td>-0.997558</td>\n",
       "      <td>-0.367098</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-1.204006</td>\n",
       "      <td>-0.995617</td>\n",
       "      <td>-0.020483</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>763</th>\n",
       "      <td>1.826623</td>\n",
       "      <td>-0.622237</td>\n",
       "      <td>0.356200</td>\n",
       "      <td>1.721613</td>\n",
       "      <td>0.869464</td>\n",
       "      <td>0.115094</td>\n",
       "      <td>-0.908090</td>\n",
       "      <td>2.530487</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>764</th>\n",
       "      <td>-0.547562</td>\n",
       "      <td>0.034575</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>0.405181</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>0.609757</td>\n",
       "      <td>-0.398023</td>\n",
       "      <td>-0.530677</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>765</th>\n",
       "      <td>0.342757</td>\n",
       "      <td>0.003299</td>\n",
       "      <td>0.149543</td>\n",
       "      <td>0.154433</td>\n",
       "      <td>0.279412</td>\n",
       "      <td>-0.734711</td>\n",
       "      <td>-0.684747</td>\n",
       "      <td>-0.275580</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>0.159683</td>\n",
       "      <td>-0.470426</td>\n",
       "      <td>-1.287373</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.240048</td>\n",
       "      <td>-0.370859</td>\n",
       "      <td>1.169970</td>\n",
       "      <td>1.365006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>-0.844335</td>\n",
       "      <td>-0.872451</td>\n",
       "      <td>0.046215</td>\n",
       "      <td>0.655930</td>\n",
       "      <td>-0.692439</td>\n",
       "      <td>-0.201997</td>\n",
       "      <td>-0.473476</td>\n",
       "      <td>-0.870806</td>\n",
       "      <td>-0.731643</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>768 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Number of times pregnant  Plasma glucose concentration  \\\n",
       "0                    0.639530                      0.847771   \n",
       "1                   -0.844335                     -1.122665   \n",
       "2                    1.233077                      1.942458   \n",
       "3                   -0.844335                     -0.997558   \n",
       "4                   -1.141108                      0.503727   \n",
       "5                    0.342757                     -0.153085   \n",
       "6                   -0.250789                     -1.341602   \n",
       "7                    1.826623                     -0.184362   \n",
       "8                   -0.547562                      2.380333   \n",
       "9                    1.233077                      0.128406   \n",
       "10                   0.045984                     -0.340746   \n",
       "11                   1.826623                      1.473307   \n",
       "12                   1.826623                      0.566280   \n",
       "13                  -0.844335                      2.130119   \n",
       "14                   0.342757                      1.410753   \n",
       "15                   0.936304                     -0.653513   \n",
       "16                  -1.141108                     -0.090532   \n",
       "17                   0.936304                     -0.434576   \n",
       "18                  -0.844335                     -0.559683   \n",
       "19                  -0.844335                     -0.184362   \n",
       "20                  -0.250789                      0.159683   \n",
       "21                   1.233077                     -0.684790   \n",
       "22                   0.936304                      2.349056   \n",
       "23                   1.529850                     -0.059255   \n",
       "24                   2.123396                      0.691388   \n",
       "25                   1.826623                      0.128406   \n",
       "26                   0.936304                      0.816495   \n",
       "27                  -0.844335                     -0.747344   \n",
       "28                   2.716942                      0.753941   \n",
       "29                   0.342757                     -0.121808   \n",
       "..                        ...                           ...   \n",
       "738                 -0.547562                     -0.684790   \n",
       "739                 -0.844335                     -0.590960   \n",
       "740                  2.123396                     -0.027978   \n",
       "741                 -0.250789                     -0.590960   \n",
       "742                 -0.844335                     -0.372022   \n",
       "743                  1.529850                      0.597557   \n",
       "744                  2.716942                      1.004155   \n",
       "745                  2.420169                     -0.653513   \n",
       "746                 -0.844335                      0.816495   \n",
       "747                 -0.844335                     -1.247772   \n",
       "748                 -0.250789                      2.067565   \n",
       "749                  0.639530                      1.285646   \n",
       "750                  0.045984                      0.472450   \n",
       "751                 -0.844335                      0.003299   \n",
       "752                 -0.250789                     -0.403299   \n",
       "753                 -1.141108                      1.879904   \n",
       "754                  1.233077                      1.035432   \n",
       "755                 -0.844335                      0.222236   \n",
       "756                  0.936304                      0.503727   \n",
       "757                 -1.141108                      0.065852   \n",
       "758                 -0.844335                     -0.465853   \n",
       "759                  0.639530                      2.161395   \n",
       "760                 -0.547562                     -1.028834   \n",
       "761                  1.529850                      1.535860   \n",
       "762                  1.529850                     -0.997558   \n",
       "763                  1.826623                     -0.622237   \n",
       "764                 -0.547562                      0.034575   \n",
       "765                  0.342757                      0.003299   \n",
       "766                 -0.844335                      0.159683   \n",
       "767                 -0.844335                     -0.872451   \n",
       "\n",
       "     Diastolic blood pressure  Triceps skin fold thickness  \\\n",
       "0                    0.149543                     0.906679   \n",
       "1                   -0.160441                     0.530556   \n",
       "2                   -0.263769                    -1.287373   \n",
       "3                   -0.160441                     0.154433   \n",
       "4                   -1.503707                     0.906679   \n",
       "5                    0.252871                    -1.287373   \n",
       "6                   -0.987066                     0.718617   \n",
       "7                   -3.570271                    -1.287373   \n",
       "8                    0.046215                     1.533551   \n",
       "9                    1.389481                    -1.287373   \n",
       "10                   1.182825                    -1.287373   \n",
       "11                   0.252871                    -1.287373   \n",
       "12                   0.562856                    -1.287373   \n",
       "13                  -0.470426                     0.154433   \n",
       "14                   0.149543                    -0.096316   \n",
       "15                  -3.570271                    -1.287373   \n",
       "16                   0.769512                     1.658926   \n",
       "17                   0.252871                    -1.287373   \n",
       "18                  -2.020348                     1.094741   \n",
       "19                   0.046215                     0.593243   \n",
       "20                   0.976169                     1.282802   \n",
       "21                   0.769512                    -1.287373   \n",
       "22                   1.079497                    -1.287373   \n",
       "23                   0.562856                     0.906679   \n",
       "24                   1.286153                     0.781305   \n",
       "25                   0.046215                     0.342494   \n",
       "26                   0.356200                    -1.287373   \n",
       "27                  -0.160441                    -0.347065   \n",
       "28                   0.666184                    -0.096316   \n",
       "29                   1.182825                    -1.287373   \n",
       "..                        ...                          ...   \n",
       "738                 -0.470426                    -0.221691   \n",
       "739                  0.252871                    -1.287373   \n",
       "740                  0.562856                     1.032053   \n",
       "741                 -1.297051                    -0.033629   \n",
       "742                 -0.573754                    -0.159003   \n",
       "743                  1.286153                    -1.287373   \n",
       "744                  0.976169                     1.032053   \n",
       "745                  0.769512                     0.781305   \n",
       "746                  1.286153                     1.282802   \n",
       "747                  0.252871                     1.282802   \n",
       "748                  0.046215                     0.091745   \n",
       "749                 -0.367098                    -1.287373   \n",
       "750                  0.046215                    -1.287373   \n",
       "751                  0.459528                     1.157428   \n",
       "752                 -0.367098                     0.217120   \n",
       "753                  0.976169                     1.470864   \n",
       "754                  0.459528                     0.718617   \n",
       "755                  0.976169                     1.157428   \n",
       "756                  1.079497                     1.282802   \n",
       "757                  0.149543                    -1.287373   \n",
       "758                  0.356200                    -1.287373   \n",
       "759                  1.182825                    -1.287373   \n",
       "760                 -0.573754                     0.342494   \n",
       "761                  0.252871                     0.655930   \n",
       "762                 -0.367098                    -1.287373   \n",
       "763                  0.356200                     1.721613   \n",
       "764                  0.046215                     0.405181   \n",
       "765                  0.149543                     0.154433   \n",
       "766                 -0.470426                    -1.287373   \n",
       "767                  0.046215                     0.655930   \n",
       "\n",
       "     2-Hour serum insulin  Body mass index  Diabetes pedigree function  \\\n",
       "0               -0.692439         0.203880                    0.468187   \n",
       "1               -0.692439        -0.683976                   -0.364823   \n",
       "2               -0.692439        -1.102537                    0.604004   \n",
       "3                0.123221        -0.493721                   -0.920163   \n",
       "4                0.765337         1.408828                    5.481337   \n",
       "5               -0.692439        -0.810813                   -0.817546   \n",
       "6                0.071158        -0.125895                   -0.675693   \n",
       "7               -0.692439         0.419502                   -1.019762   \n",
       "8                4.019303        -0.189314                   -0.947326   \n",
       "9               -0.692439        -4.057829                   -0.723983   \n",
       "10              -0.692439         0.711226                   -0.847727   \n",
       "11              -0.692439         0.761961                    0.196553   \n",
       "12              -0.692439        -0.620558                    2.924962   \n",
       "13               6.648507        -0.240048                   -0.222970   \n",
       "14               0.826078        -0.785445                    0.347461   \n",
       "15              -0.692439        -0.252732                    0.036591   \n",
       "16               1.303326         1.751286                    0.238807   \n",
       "17              -0.692439        -0.303466                   -0.657584   \n",
       "18               0.027772         1.434195                   -0.871873   \n",
       "19               0.140576         0.330716                    0.172408   \n",
       "20               1.346712         0.926848                    0.700585   \n",
       "21              -0.692439         0.432186                   -0.253151   \n",
       "22              -0.692439         0.990267                   -0.063008   \n",
       "23              -0.692439        -0.379568                   -0.630420   \n",
       "24               0.574438         0.584390                   -0.657584   \n",
       "25               0.305443        -0.113212                   -0.805473   \n",
       "26              -0.692439         0.939532                   -0.648529   \n",
       "27               0.522374        -1.115221                    0.045646   \n",
       "28               0.262057        -1.242057                   -0.684747   \n",
       "29              -0.692439         0.267298                   -0.407077   \n",
       "..                    ...              ...                         ...   \n",
       "738              0.695919         0.584390                   -0.056972   \n",
       "739             -0.692439         0.952216                   -0.539876   \n",
       "740              0.609147         1.307358                    0.945055   \n",
       "741              0.123221        -0.151263                   -0.216934   \n",
       "742              0.314121        -0.442987                   -0.763219   \n",
       "743             -0.692439         0.089727                    0.791129   \n",
       "744              0.522374         1.091736                    2.119116   \n",
       "745              0.218671        -0.252732                    0.048664   \n",
       "746             -0.692439         2.195214                   -0.343696   \n",
       "747             -0.197837         1.814705                    1.883700   \n",
       "748              1.043009         0.559022                   -0.192788   \n",
       "749             -0.692439        -0.975700                   -0.886963   \n",
       "750             -0.692439        -0.100528                    2.143261   \n",
       "751             -0.050323         0.888797                   -0.636457   \n",
       "752             -0.692439        -0.760078                   -0.751146   \n",
       "753              3.732954         1.434195                   -0.754165   \n",
       "754             -0.692439         0.051676                   -0.087153   \n",
       "755              0.262057         0.571706                    1.765992   \n",
       "756             -0.692439         0.000941                   -0.244097   \n",
       "757             -0.692439         0.546339                   -0.645511   \n",
       "758             -0.692439         0.698543                   -0.829618   \n",
       "759             -0.692439         0.444869                   -0.585148   \n",
       "760             -0.553603        -0.455670                    0.887710   \n",
       "761             -0.692439         1.522980                   -0.207879   \n",
       "762             -0.692439        -1.204006                   -0.995617   \n",
       "763              0.869464         0.115094                   -0.908090   \n",
       "764             -0.692439         0.609757                   -0.398023   \n",
       "765              0.279412        -0.734711                   -0.684747   \n",
       "766             -0.692439        -0.240048                   -0.370859   \n",
       "767             -0.692439        -0.201997                   -0.473476   \n",
       "\n",
       "          Age     Class  \n",
       "0    1.425067  1.365006  \n",
       "1   -0.190548 -0.731643  \n",
       "2   -0.105515  1.365006  \n",
       "3   -1.040871 -0.731643  \n",
       "4   -0.020483  1.365006  \n",
       "5   -0.275580 -0.731643  \n",
       "6   -0.615709  1.365006  \n",
       "7   -0.360612 -0.731643  \n",
       "8    1.680164  1.365006  \n",
       "9    1.765196  1.365006  \n",
       "10  -0.275580 -0.731643  \n",
       "11   0.064549  1.365006  \n",
       "12   2.020293 -0.731643  \n",
       "13   2.190358  1.365006  \n",
       "14   1.510099  1.365006  \n",
       "15  -0.105515  1.365006  \n",
       "16  -0.190548  1.365006  \n",
       "17  -0.190548  1.365006  \n",
       "18  -0.020483 -0.731643  \n",
       "19  -0.105515  1.365006  \n",
       "20  -0.530677 -0.731643  \n",
       "21   1.425067 -0.731643  \n",
       "22   0.659776  1.365006  \n",
       "23  -0.360612  1.365006  \n",
       "24   1.510099  1.365006  \n",
       "25   0.659776  1.365006  \n",
       "26   0.829840  1.365006  \n",
       "27  -0.955839 -0.731643  \n",
       "28   2.020293 -0.731643  \n",
       "29   0.404679 -0.731643  \n",
       "..        ...       ...  \n",
       "738 -1.040871 -0.731643  \n",
       "739  0.744808  1.365006  \n",
       "740  1.255002  1.365006  \n",
       "741 -0.615709 -0.731643  \n",
       "742 -0.955839 -0.731643  \n",
       "743  0.999905  1.365006  \n",
       "744  0.489711 -0.731643  \n",
       "745  1.084937 -0.731643  \n",
       "746 -0.530677  1.365006  \n",
       "747 -0.105515 -0.731643  \n",
       "748  0.234614  1.365006  \n",
       "749  1.425067  1.365006  \n",
       "750 -0.955839  1.365006  \n",
       "751 -0.445645 -0.731643  \n",
       "752 -0.700742 -0.731643  \n",
       "753 -0.615709  1.365006  \n",
       "754  0.999905  1.365006  \n",
       "755  0.319646  1.365006  \n",
       "756  0.489711 -0.731643  \n",
       "757  1.595131  1.365006  \n",
       "758 -0.615709 -0.731643  \n",
       "759  2.785584  1.365006  \n",
       "760 -0.955839 -0.731643  \n",
       "761  0.829840  1.365006  \n",
       "762 -0.020483 -0.731643  \n",
       "763  2.530487 -0.731643  \n",
       "764 -0.530677 -0.731643  \n",
       "765 -0.275580 -0.731643  \n",
       "766  1.169970  1.365006  \n",
       "767 -0.870806 -0.731643  \n",
       "\n",
       "[768 rows x 9 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normalized_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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