Fundamental_tensorflow.ipynb

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      "authorship_tag": "ABX9TyNnFTorG3qtVj3YkGQi2Hvq",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/darshbaxi/Tensorflow-Practice/blob/main/Fundamental_tensorflow.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "rrY2cffP-1If"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "matrix=tf.constant([[[1,2,3],[1,2,3]],[[4,5,6],[7,8,9]],[[8,9,7],[8,5,6]],[[8,9,7],[8,5,6]]])"
      ],
      "metadata": {
        "id": "qcDGGc91_BHB"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "matrix"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8tsvh_uL_vM_",
        "outputId": "3343954d-5407-49c7-f6db-d89cf473fa93"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(4, 2, 3), dtype=int32, numpy=\n",
              "array([[[1, 2, 3],\n",
              "        [1, 2, 3]],\n",
              "\n",
              "       [[4, 5, 6],\n",
              "        [7, 8, 9]],\n",
              "\n",
              "       [[8, 9, 7],\n",
              "        [8, 5, 6]],\n",
              "\n",
              "       [[8, 9, 7],\n",
              "        [8, 5, 6]]], dtype=int32)>"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "matrix.ndim"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9Uk4Xm4F_w4z",
        "outputId": "20c93abf-50f9-417b-fc33-1a95f67ec2fa"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a=np.array([[0],[1],[2]])\n",
        "b=np.array([[0],[1],[2]])"
      ],
      "metadata": {
        "id": "dj3MH1Jg_7x5"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(np.hstack((a,b)));"
      ],
      "metadata": {
        "id": "d_602CZdKynR",
        "outputId": "8fc24804-1555-438b-8445-62ca95a6a4a6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0 0]\n",
            " [1 1]\n",
            " [2 2]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "df=pd.read_csv(\"50_Startups.csv\")"
      ],
      "metadata": {
        "id": "N8Mume6rK7ce"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "df = df.sample(frac = 1) #### for suffling the data;\n",
        "\n",
        "df"
      ],
      "metadata": {
        "id": "56eu4fXJLTe5",
        "outputId": "183d747f-930d-4234-aebb-06c975b134ba",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     R&DSpend  Administration  MarketingSpend       State     Profit\n",
              "11  100671.96        91790.61             NaN  California  144259.40\n",
              "41   27892.92             NaN       164470.71     Florida   77798.83\n",
              "8   120542.52       148718.95             NaN    New York  152211.77\n",
              "37   44069.95        51283.14       197029.42  California   89949.14\n",
              "32   63408.86       129219.61        46085.25  California   97427.84\n",
              "18   91749.16       114175.79       294919.57     Florida  124266.90\n",
              "43        NaN       127382.30        35534.17    New York   69758.98\n",
              "46    1315.46       115816.21       297114.46     Florida   49490.75\n",
              "10        NaN       110594.11       229160.95     Florida  146121.95\n",
              "34   46426.07             NaN       210797.67  California   96712.80\n",
              "28   66051.52       182645.56       118148.20     Florida  103282.38\n",
              "20   76253.86       113867.30       298664.47  California  118474.03\n",
              "4   142107.34        91391.77       366168.42     Florida  166187.94\n",
              "19        NaN       153514.11             NaN    New York  122776.86\n",
              "13   91992.39       135495.07       252664.93  California  134307.35\n",
              "15  114523.61       122616.84       261776.23    New York  129917.04\n",
              "23   67532.53       105751.03       304768.73     Florida  108733.99\n",
              "36   28663.76       127056.21       201126.82     Florida   90708.19\n",
              "35   46014.02        85047.44       205517.64    New York   96479.51\n",
              "42   23640.93        96189.63       148001.11  California   71498.49\n",
              "30   61994.48       115641.28        91131.24     Florida   99937.59\n",
              "31   61136.38       152701.92             NaN    New York   97483.56\n",
              "2   153441.51       101145.55       407934.54     Florida  191050.39\n",
              "21   78389.47       153773.43       299737.29    New York  111313.02\n",
              "12   93863.75       127320.38       249839.44     Florida  141585.52\n",
              "24   77044.01        99281.34             NaN    New York  108552.04\n",
              "5         NaN        99814.71       362861.36    New York  156991.12\n",
              "0   165349.20       136897.80       471784.10    New York  192261.83\n",
              "33        NaN       103057.49       214634.81     Florida   96778.92\n",
              "25        NaN             NaN       137962.62  California  107404.34\n",
              "47        NaN       135426.92             NaN  California   42559.73\n",
              "14  119943.24       156547.42       256512.92     Florida  132602.65\n",
              "22   73994.56       122782.75       303319.26     Florida  110352.25\n",
              "16   78013.11             NaN       264346.06  California  126992.93\n",
              "26   75328.87       144135.98       134050.07     Florida  105733.54\n",
              "9   123334.88       108679.17       304981.62  California  149759.96\n",
              "7   130298.13       145530.06       323876.68     Florida  155752.60\n",
              "39   38558.51        82982.09             NaN  California   81005.76\n",
              "27   72107.60       127864.55       353183.81    New York  105008.31\n",
              "29   65605.48       153032.06       107138.38    New York  101004.64\n",
              "1   162597.70       151377.59       443898.53  California  191792.06\n",
              "45    1000.23       124153.04         1903.93    New York   64926.08\n",
              "38   20229.59        65947.93       185265.10    New York   81229.06\n",
              "40   28754.33       118546.05       172795.67  California   78239.91\n",
              "48     542.05        51743.15             NaN    New York   35673.41\n",
              "3   144372.41       118671.85       383199.62    New York  182901.99\n",
              "44   22177.74       154806.14        28334.72  California   65200.33\n",
              "49        NaN       116983.80        45173.06  California   14681.40\n",
              "6   134615.46       147198.87       127716.82  California  156122.51\n",
              "17   94657.16       145077.58       282574.31    New York  125370.37"
            ],
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>R&amp;DSpend</th>\n",
              "      <th>Administration</th>\n",
              "      <th>MarketingSpend</th>\n",
              "      <th>State</th>\n",
              "      <th>Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>100671.96</td>\n",
              "      <td>91790.61</td>\n",
              "      <td>NaN</td>\n",
              "      <td>California</td>\n",
              "      <td>144259.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>27892.92</td>\n",
              "      <td>NaN</td>\n",
              "      <td>164470.71</td>\n",
              "      <td>Florida</td>\n",
              "      <td>77798.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>120542.52</td>\n",
              "      <td>148718.95</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "      <td>152211.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>44069.95</td>\n",
              "      <td>51283.14</td>\n",
              "      <td>197029.42</td>\n",
              "      <td>California</td>\n",
              "      <td>89949.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>63408.86</td>\n",
              "      <td>129219.61</td>\n",
              "      <td>46085.25</td>\n",
              "      <td>California</td>\n",
              "      <td>97427.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>91749.16</td>\n",
              "      <td>114175.79</td>\n",
              "      <td>294919.57</td>\n",
              "      <td>Florida</td>\n",
              "      <td>124266.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>NaN</td>\n",
              "      <td>127382.30</td>\n",
              "      <td>35534.17</td>\n",
              "      <td>New York</td>\n",
              "      <td>69758.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>1315.46</td>\n",
              "      <td>115816.21</td>\n",
              "      <td>297114.46</td>\n",
              "      <td>Florida</td>\n",
              "      <td>49490.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>NaN</td>\n",
              "      <td>110594.11</td>\n",
              "      <td>229160.95</td>\n",
              "      <td>Florida</td>\n",
              "      <td>146121.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>46426.07</td>\n",
              "      <td>NaN</td>\n",
              "      <td>210797.67</td>\n",
              "      <td>California</td>\n",
              "      <td>96712.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>66051.52</td>\n",
              "      <td>182645.56</td>\n",
              "      <td>118148.20</td>\n",
              "      <td>Florida</td>\n",
              "      <td>103282.38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>76253.86</td>\n",
              "      <td>113867.30</td>\n",
              "      <td>298664.47</td>\n",
              "      <td>California</td>\n",
              "      <td>118474.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>142107.34</td>\n",
              "      <td>91391.77</td>\n",
              "      <td>366168.42</td>\n",
              "      <td>Florida</td>\n",
              "      <td>166187.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>NaN</td>\n",
              "      <td>153514.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "      <td>122776.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>91992.39</td>\n",
              "      <td>135495.07</td>\n",
              "      <td>252664.93</td>\n",
              "      <td>California</td>\n",
              "      <td>134307.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>114523.61</td>\n",
              "      <td>122616.84</td>\n",
              "      <td>261776.23</td>\n",
              "      <td>New York</td>\n",
              "      <td>129917.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>67532.53</td>\n",
              "      <td>105751.03</td>\n",
              "      <td>304768.73</td>\n",
              "      <td>Florida</td>\n",
              "      <td>108733.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>28663.76</td>\n",
              "      <td>127056.21</td>\n",
              "      <td>201126.82</td>\n",
              "      <td>Florida</td>\n",
              "      <td>90708.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>46014.02</td>\n",
              "      <td>85047.44</td>\n",
              "      <td>205517.64</td>\n",
              "      <td>New York</td>\n",
              "      <td>96479.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>23640.93</td>\n",
              "      <td>96189.63</td>\n",
              "      <td>148001.11</td>\n",
              "      <td>California</td>\n",
              "      <td>71498.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>61994.48</td>\n",
              "      <td>115641.28</td>\n",
              "      <td>91131.24</td>\n",
              "      <td>Florida</td>\n",
              "      <td>99937.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>61136.38</td>\n",
              "      <td>152701.92</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "      <td>97483.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>153441.51</td>\n",
              "      <td>101145.55</td>\n",
              "      <td>407934.54</td>\n",
              "      <td>Florida</td>\n",
              "      <td>191050.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>78389.47</td>\n",
              "      <td>153773.43</td>\n",
              "      <td>299737.29</td>\n",
              "      <td>New York</td>\n",
              "      <td>111313.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>93863.75</td>\n",
              "      <td>127320.38</td>\n",
              "      <td>249839.44</td>\n",
              "      <td>Florida</td>\n",
              "      <td>141585.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>77044.01</td>\n",
              "      <td>99281.34</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "      <td>108552.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>NaN</td>\n",
              "      <td>99814.71</td>\n",
              "      <td>362861.36</td>\n",
              "      <td>New York</td>\n",
              "      <td>156991.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>165349.20</td>\n",
              "      <td>136897.80</td>\n",
              "      <td>471784.10</td>\n",
              "      <td>New York</td>\n",
              "      <td>192261.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>NaN</td>\n",
              "      <td>103057.49</td>\n",
              "      <td>214634.81</td>\n",
              "      <td>Florida</td>\n",
              "      <td>96778.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>137962.62</td>\n",
              "      <td>California</td>\n",
              "      <td>107404.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>NaN</td>\n",
              "      <td>135426.92</td>\n",
              "      <td>NaN</td>\n",
              "      <td>California</td>\n",
              "      <td>42559.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>119943.24</td>\n",
              "      <td>156547.42</td>\n",
              "      <td>256512.92</td>\n",
              "      <td>Florida</td>\n",
              "      <td>132602.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>73994.56</td>\n",
              "      <td>122782.75</td>\n",
              "      <td>303319.26</td>\n",
              "      <td>Florida</td>\n",
              "      <td>110352.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>78013.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>264346.06</td>\n",
              "      <td>California</td>\n",
              "      <td>126992.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>75328.87</td>\n",
              "      <td>144135.98</td>\n",
              "      <td>134050.07</td>\n",
              "      <td>Florida</td>\n",
              "      <td>105733.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>123334.88</td>\n",
              "      <td>108679.17</td>\n",
              "      <td>304981.62</td>\n",
              "      <td>California</td>\n",
              "      <td>149759.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>130298.13</td>\n",
              "      <td>145530.06</td>\n",
              "      <td>323876.68</td>\n",
              "      <td>Florida</td>\n",
              "      <td>155752.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>38558.51</td>\n",
              "      <td>82982.09</td>\n",
              "      <td>NaN</td>\n",
              "      <td>California</td>\n",
              "      <td>81005.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>72107.60</td>\n",
              "      <td>127864.55</td>\n",
              "      <td>353183.81</td>\n",
              "      <td>New York</td>\n",
              "      <td>105008.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>65605.48</td>\n",
              "      <td>153032.06</td>\n",
              "      <td>107138.38</td>\n",
              "      <td>New York</td>\n",
              "      <td>101004.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>162597.70</td>\n",
              "      <td>151377.59</td>\n",
              "      <td>443898.53</td>\n",
              "      <td>California</td>\n",
              "      <td>191792.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>1000.23</td>\n",
              "      <td>124153.04</td>\n",
              "      <td>1903.93</td>\n",
              "      <td>New York</td>\n",
              "      <td>64926.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>20229.59</td>\n",
              "      <td>65947.93</td>\n",
              "      <td>185265.10</td>\n",
              "      <td>New York</td>\n",
              "      <td>81229.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>28754.33</td>\n",
              "      <td>118546.05</td>\n",
              "      <td>172795.67</td>\n",
              "      <td>California</td>\n",
              "      <td>78239.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>542.05</td>\n",
              "      <td>51743.15</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "      <td>35673.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>144372.41</td>\n",
              "      <td>118671.85</td>\n",
              "      <td>383199.62</td>\n",
              "      <td>New York</td>\n",
              "      <td>182901.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>22177.74</td>\n",
              "      <td>154806.14</td>\n",
              "      <td>28334.72</td>\n",
              "      <td>California</td>\n",
              "      <td>65200.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>NaN</td>\n",
              "      <td>116983.80</td>\n",
              "      <td>45173.06</td>\n",
              "      <td>California</td>\n",
              "      <td>14681.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>134615.46</td>\n",
              "      <td>147198.87</td>\n",
              "      <td>127716.82</td>\n",
              "      <td>California</td>\n",
              "      <td>156122.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>94657.16</td>\n",
              "      <td>145077.58</td>\n",
              "      <td>282574.31</td>\n",
              "      <td>New York</td>\n",
              "      <td>125370.37</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x=df.iloc[:,:-1]"
      ],
      "metadata": {
        "id": "PzWSF6ZHNpdA"
      },
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x.shape"
      ],
      "metadata": {
        "id": "XxojC52ENwIA",
        "outputId": "618b5eff-063d-4a72-9fcf-d4337f917af4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=df.iloc[:,-1]\n",
        "y"
      ],
      "metadata": {
        "id": "P227Z_FIN2Ub",
        "outputId": "cf7edf9f-3b5d-456b-8ce6-2927c9f91c7d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     192261.83\n",
              "1     191792.06\n",
              "2     191050.39\n",
              "3     182901.99\n",
              "4     166187.94\n",
              "5     156991.12\n",
              "6     156122.51\n",
              "7     155752.60\n",
              "8     152211.77\n",
              "9     149759.96\n",
              "10    146121.95\n",
              "11    144259.40\n",
              "12    141585.52\n",
              "13    134307.35\n",
              "14    132602.65\n",
              "15    129917.04\n",
              "16    126992.93\n",
              "17    125370.37\n",
              "18    124266.90\n",
              "19    122776.86\n",
              "20    118474.03\n",
              "21    111313.02\n",
              "22    110352.25\n",
              "23    108733.99\n",
              "24    108552.04\n",
              "25    107404.34\n",
              "26    105733.54\n",
              "27    105008.31\n",
              "28    103282.38\n",
              "29    101004.64\n",
              "30     99937.59\n",
              "31     97483.56\n",
              "32     97427.84\n",
              "33     96778.92\n",
              "34     96712.80\n",
              "35     96479.51\n",
              "36     90708.19\n",
              "37     89949.14\n",
              "38     81229.06\n",
              "39     81005.76\n",
              "40     78239.91\n",
              "41     77798.83\n",
              "42     71498.49\n",
              "43     69758.98\n",
              "44     65200.33\n",
              "45     64926.08\n",
              "46     49490.75\n",
              "47     42559.73\n",
              "48     35673.41\n",
              "49     14681.40\n",
              "Name: Profit, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import math\n",
        "x_train=math.floor(x.shape[0]*0.80)\n"
      ],
      "metadata": {
        "id": "Ko91UETkN7Zn"
      },
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "x_tarin=x.iloc[:x_train,:]"
      ],
      "metadata": {
        "id": "6AH54D6HN-Of"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_tarin\n"
      ],
      "metadata": {
        "id": "japqortzOcwY",
        "outputId": "cd2ad6ad-213f-4081-bb57-c9e459f45922",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     R&DSpend  Administration  MarketingSpend       State\n",
              "0   165349.20       136897.80       471784.10    New York\n",
              "1   162597.70       151377.59       443898.53  California\n",
              "2   153441.51       101145.55       407934.54     Florida\n",
              "3   144372.41       118671.85       383199.62    New York\n",
              "4   142107.34        91391.77       366168.42     Florida\n",
              "5         NaN        99814.71       362861.36    New York\n",
              "6   134615.46       147198.87       127716.82  California\n",
              "7   130298.13       145530.06       323876.68     Florida\n",
              "8   120542.52       148718.95             NaN    New York\n",
              "9   123334.88       108679.17       304981.62  California\n",
              "10        NaN       110594.11       229160.95     Florida\n",
              "11  100671.96        91790.61             NaN  California\n",
              "12   93863.75       127320.38       249839.44     Florida\n",
              "13   91992.39       135495.07       252664.93  California\n",
              "14  119943.24       156547.42       256512.92     Florida\n",
              "15  114523.61       122616.84       261776.23    New York\n",
              "16   78013.11             NaN       264346.06  California\n",
              "17   94657.16       145077.58       282574.31    New York\n",
              "18   91749.16       114175.79       294919.57     Florida\n",
              "19        NaN       153514.11             NaN    New York\n",
              "20   76253.86       113867.30       298664.47  California\n",
              "21   78389.47       153773.43       299737.29    New York\n",
              "22   73994.56       122782.75       303319.26     Florida\n",
              "23   67532.53       105751.03       304768.73     Florida\n",
              "24   77044.01        99281.34             NaN    New York\n",
              "25        NaN             NaN       137962.62  California\n",
              "26   75328.87       144135.98       134050.07     Florida\n",
              "27   72107.60       127864.55       353183.81    New York\n",
              "28   66051.52       182645.56       118148.20     Florida\n",
              "29   65605.48       153032.06       107138.38    New York\n",
              "30   61994.48       115641.28        91131.24     Florida\n",
              "31   61136.38       152701.92             NaN    New York\n",
              "32   63408.86       129219.61        46085.25  California\n",
              "33        NaN       103057.49       214634.81     Florida\n",
              "34   46426.07             NaN       210797.67  California\n",
              "35   46014.02        85047.44       205517.64    New York\n",
              "36   28663.76       127056.21       201126.82     Florida\n",
              "37   44069.95        51283.14       197029.42  California\n",
              "38   20229.59        65947.93       185265.10    New York\n",
              "39   38558.51        82982.09             NaN  California"
            ],
            "text/html": [
              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>R&amp;DSpend</th>\n",
              "      <th>Administration</th>\n",
              "      <th>MarketingSpend</th>\n",
              "      <th>State</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>165349.20</td>\n",
              "      <td>136897.80</td>\n",
              "      <td>471784.10</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>162597.70</td>\n",
              "      <td>151377.59</td>\n",
              "      <td>443898.53</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>153441.51</td>\n",
              "      <td>101145.55</td>\n",
              "      <td>407934.54</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>144372.41</td>\n",
              "      <td>118671.85</td>\n",
              "      <td>383199.62</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>142107.34</td>\n",
              "      <td>91391.77</td>\n",
              "      <td>366168.42</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>NaN</td>\n",
              "      <td>99814.71</td>\n",
              "      <td>362861.36</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>134615.46</td>\n",
              "      <td>147198.87</td>\n",
              "      <td>127716.82</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>130298.13</td>\n",
              "      <td>145530.06</td>\n",
              "      <td>323876.68</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>120542.52</td>\n",
              "      <td>148718.95</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>123334.88</td>\n",
              "      <td>108679.17</td>\n",
              "      <td>304981.62</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>NaN</td>\n",
              "      <td>110594.11</td>\n",
              "      <td>229160.95</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>100671.96</td>\n",
              "      <td>91790.61</td>\n",
              "      <td>NaN</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>93863.75</td>\n",
              "      <td>127320.38</td>\n",
              "      <td>249839.44</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>91992.39</td>\n",
              "      <td>135495.07</td>\n",
              "      <td>252664.93</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>119943.24</td>\n",
              "      <td>156547.42</td>\n",
              "      <td>256512.92</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>114523.61</td>\n",
              "      <td>122616.84</td>\n",
              "      <td>261776.23</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>78013.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>264346.06</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>94657.16</td>\n",
              "      <td>145077.58</td>\n",
              "      <td>282574.31</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>91749.16</td>\n",
              "      <td>114175.79</td>\n",
              "      <td>294919.57</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>NaN</td>\n",
              "      <td>153514.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>76253.86</td>\n",
              "      <td>113867.30</td>\n",
              "      <td>298664.47</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>78389.47</td>\n",
              "      <td>153773.43</td>\n",
              "      <td>299737.29</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>73994.56</td>\n",
              "      <td>122782.75</td>\n",
              "      <td>303319.26</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>67532.53</td>\n",
              "      <td>105751.03</td>\n",
              "      <td>304768.73</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>77044.01</td>\n",
              "      <td>99281.34</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>137962.62</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>75328.87</td>\n",
              "      <td>144135.98</td>\n",
              "      <td>134050.07</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>72107.60</td>\n",
              "      <td>127864.55</td>\n",
              "      <td>353183.81</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>66051.52</td>\n",
              "      <td>182645.56</td>\n",
              "      <td>118148.20</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>65605.48</td>\n",
              "      <td>153032.06</td>\n",
              "      <td>107138.38</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>61994.48</td>\n",
              "      <td>115641.28</td>\n",
              "      <td>91131.24</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>61136.38</td>\n",
              "      <td>152701.92</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>63408.86</td>\n",
              "      <td>129219.61</td>\n",
              "      <td>46085.25</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>NaN</td>\n",
              "      <td>103057.49</td>\n",
              "      <td>214634.81</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>46426.07</td>\n",
              "      <td>NaN</td>\n",
              "      <td>210797.67</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>46014.02</td>\n",
              "      <td>85047.44</td>\n",
              "      <td>205517.64</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>28663.76</td>\n",
              "      <td>127056.21</td>\n",
              "      <td>201126.82</td>\n",
              "      <td>Florida</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>44069.95</td>\n",
              "      <td>51283.14</td>\n",
              "      <td>197029.42</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>20229.59</td>\n",
              "      <td>65947.93</td>\n",
              "      <td>185265.10</td>\n",
              "      <td>New York</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>38558.51</td>\n",
              "      <td>82982.09</td>\n",
              "      <td>NaN</td>\n",
              "      <td>California</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-00aadda3-38d1-4b5d-a6ae-662963c2f5b4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-00aadda3-38d1-4b5d-a6ae-662963c2f5b4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-00aadda3-38d1-4b5d-a6ae-662963c2f5b4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "f4NVo5SlRLr7"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}