Model_2.ipynb

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      "source": [
        "DS404 Khushi Agarwal"
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        "id": "I_Rt1qFaoGe6"
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      "cell_type": "markdown",
      "source": [
        "INSURANCE DATASET (Medical Cost Prediction)"
      ],
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        "id": "alyLFWo-k-Qb"
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      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "\n",
        "sns.set_theme(style='darkgrid', palette='deep')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "url=\"https://drive.google.com/file/d/1TTgXeOdfHW3HAx0shpqIy-An5Pwuubxw/view?usp=sharing\"\n",
        "url='https://drive.google.com/uc?id=' + url.split('/')[-2]\n",
        "df = pd.read_csv(url)"
      ],
      "metadata": {
        "id": "7KapYa0brVl4"
      },
      "execution_count": 2,
      "outputs": []
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    {
      "cell_type": "code",
      "source": [
        "df.head(10)"
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              "   age     sex     bmi  children smoker     region      charges\n",
              "0   19  female  27.900         0    yes  southwest  16884.92400\n",
              "1   18    male  33.770         1     no  southeast   1725.55230\n",
              "2   28    male  33.000         3     no  southeast   4449.46200\n",
              "3   33    male  22.705         0     no  northwest  21984.47061\n",
              "4   32    male  28.880         0     no  northwest   3866.85520\n",
              "5   31  female  25.740         0     no  southeast   3756.62160\n",
              "6   46  female  33.440         1     no  southeast   8240.58960\n",
              "7   37  female  27.740         3     no  northwest   7281.50560\n",
              "8   37    male  29.830         2     no  northeast   6406.41070\n",
              "9   60  female  25.840         0     no  northwest  28923.13692"
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              "      <th>8</th>\n",
              "      <td>37</td>\n",
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              "      <td>29.830</td>\n",
              "      <td>2</td>\n",
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              "      <td>northeast</td>\n",
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              "      <th>9</th>\n",
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          "data": {
            "text/plain": [
              "               age          bmi     children       charges\n",
              "count  1338.000000  1338.000000  1338.000000   1338.000000\n",
              "mean     39.207025    30.663397     1.094918  13270.422265\n",
              "std      14.049960     6.098187     1.205493  12110.011237\n",
              "min      18.000000    15.960000     0.000000   1121.873900\n",
              "25%      27.000000    26.296250     0.000000   4740.287150\n",
              "50%      39.000000    30.400000     1.000000   9382.033000\n",
              "75%      51.000000    34.693750     2.000000  16639.912515\n",
              "max      64.000000    53.130000     5.000000  63770.428010"
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              "      <th>mean</th>\n",
              "      <td>39.207025</td>\n",
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              "      <td>13270.422265</td>\n",
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              "      <th>std</th>\n",
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              "      <td>18.000000</td>\n",
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              "      <th>25%</th>\n",
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              "      <th>50%</th>\n",
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              "      <th>75%</th>\n",
              "      <td>51.000000</td>\n",
              "      <td>34.693750</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>16639.912515</td>\n",
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              "      <th>max</th>\n",
              "      <td>64.000000</td>\n",
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              "               age       bmi  children   charges\n",
              "age       1.000000  0.109272  0.042469  0.299008\n",
              "bmi       0.109272  1.000000  0.012759  0.198341\n",
              "children  0.042469  0.012759  1.000000  0.067998\n",
              "charges   0.299008  0.198341  0.067998  1.000000"
            ],
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              "      <th>bmi</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>age</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.109272</td>\n",
              "      <td>0.042469</td>\n",
              "      <td>0.299008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bmi</th>\n",
              "      <td>0.109272</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.012759</td>\n",
              "      <td>0.198341</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>children</th>\n",
              "      <td>0.042469</td>\n",
              "      <td>0.012759</td>\n",
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              "      <td>0.067998</td>\n",
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              "    <tr>\n",
              "      <th>charges</th>\n",
              "      <td>0.299008</td>\n",
              "      <td>0.198341</td>\n",
              "      <td>0.067998</td>\n",
              "      <td>1.000000</td>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-78ec2c0b-71fb-4039-abaa-a24ef30c4144 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-78ec2c0b-71fb-4039-abaa-a24ef30c4144');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.pairplot(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 743
        },
        "id": "tJCsKSVrvpCK",
        "outputId": "278c3c97-fce6-41a5-c4aa-c7e1b48ae799"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7f8175d3f390>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 20 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TanBiE4GwlMz",
        "outputId": "dbd3b35e-bc08-4d39-94cd-2ed852ad7243"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age            39.207025\n",
              "bmi            30.663397\n",
              "children        1.094918\n",
              "charges     13270.422265\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g8H6aG3qwrol",
        "outputId": "d92e18a5-2bbc-4a9b-adfa-39fe34a19440"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age  sex     bmi     children  smoker  region     charges    \n",
              "19   male    30.590  0         no      northwest  1639.56310     2\n",
              "47   male    29.830  3         no      northwest  9620.33070     1\n",
              "48   female  25.850  3         yes     southeast  24180.93350    1\n",
              "             22.800  0         no      southwest  8269.04400     1\n",
              "47   male    47.520  1         no      southeast  8083.91980     1\n",
              "                                                                ..\n",
              "31   female  25.740  0         no      southeast  3756.62160     1\n",
              "             23.600  2         no      southwest  4931.64700     1\n",
              "             21.755  0         no      northwest  4134.08245     1\n",
              "30   male    44.220  2         no      southeast  4266.16580     1\n",
              "64   male    40.480  0         no      southeast  13831.11520    1\n",
              "Length: 1337, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YfPxPDqpww67",
        "outputId": "062431f0-b081-46f9-8e98-daa2fd01ef4e"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['age', 'sex', 'bmi', 'children', 'smoker', 'region', 'charges'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vx-Fg1iqwzRF",
        "outputId": "71286428-4e0e-46d8-e704-c4d41bbc93d7"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age           int64\n",
              "sex          object\n",
              "bmi         float64\n",
              "children      int64\n",
              "smoker       object\n",
              "region       object\n",
              "charges     float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.duplicated().value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UbtSzS0Vw6lP",
        "outputId": "fb7c086f-0d50-4556-bd6f-80aa54caf586"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    1337\n",
              "True        1\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['age']=df['age'].astype(float)\n",
        "df['children']=df['children'].astype(float)"
      ],
      "metadata": {
        "id": "k3agjH-5xGg6"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U_qNFb4bxJOZ",
        "outputId": "c0781884-0202-4ab5-b797-ab61deeafc57"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age         0\n",
              "sex         0\n",
              "bmi         0\n",
              "children    0\n",
              "smoker      0\n",
              "region      0\n",
              "charges     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['sex'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TFzpD07UxNDW",
        "outputId": "f3e8b881-2fc0-44e8-91a2-5ba7cb7412e9"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['female', 'male'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['smoker'].unique()"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "39uiOZKQxP_E",
        "outputId": "e3a1b39a-dc9e-4540-ef18-b92d6944b696"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['yes', 'no'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['region'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nctNsuO3xRpR",
        "outputId": "de6506ee-8c90-4ef5-9959-6ccddca31ff9"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['southwest', 'southeast', 'northwest', 'northeast'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in df.columns:\n",
        "    df[i].replace({'..':np.nan},inplace=True)   # single special characters replacing with null values\n",
        "    df"
      ],
      "metadata": {
        "id": "preH08EDxYRM"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "8iFMIftNxlCI",
        "outputId": "e258ef69-1025-43a9-cc91-c539aa77ef35"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
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            "text/plain": [
              "    age     sex     bmi  children smoker     region      charges\n",
              "0  19.0  female  27.900       0.0    yes  southwest  16884.92400\n",
              "1  18.0    male  33.770       1.0     no  southeast   1725.55230\n",
              "2  28.0    male  33.000       3.0     no  southeast   4449.46200\n",
              "3  33.0    male  22.705       0.0     no  northwest  21984.47061\n",
              "4  32.0    male  28.880       0.0     no  northwest   3866.85520"
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          },
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def mea(df,col):#to replace null values with median\n",
        "    \n",
        "    q1=df[col].quantile(0.25)\n",
        "    q3=df[col].quantile(0.75)\n",
        "    IQR=q3-q1\n",
        "    upper=q3+(1.5*IQR)\n",
        "    lower=q1-(1.5*IQR)\n",
        "    median=df[col].median()\n",
        "    df[col]=np.where(df[col]>upper,median,np.where(df[col]<lower,median,df[col]))\n",
        "    sns.boxplot(df[col],data=df)"
      ],
      "metadata": {
        "id": "jZdKvuNixqG-"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.set_option('display.max_rows', 100)\n",
        "df.head(30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "id": "azbnOYgixtsP",
        "outputId": "41d67b13-861b-4442-a9bb-7bfe4ffe1159"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age     sex     bmi  children smoker     region      charges\n",
              "0   19.0  female  27.900       0.0    yes  southwest  16884.92400\n",
              "1   18.0    male  33.770       1.0     no  southeast   1725.55230\n",
              "2   28.0    male  33.000       3.0     no  southeast   4449.46200\n",
              "3   33.0    male  22.705       0.0     no  northwest  21984.47061\n",
              "4   32.0    male  28.880       0.0     no  northwest   3866.85520\n",
              "5   31.0  female  25.740       0.0     no  southeast   3756.62160\n",
              "6   46.0  female  33.440       1.0     no  southeast   8240.58960\n",
              "7   37.0  female  27.740       3.0     no  northwest   7281.50560\n",
              "8   37.0    male  29.830       2.0     no  northeast   6406.41070\n",
              "9   60.0  female  25.840       0.0     no  northwest  28923.13692\n",
              "10  25.0    male  26.220       0.0     no  northeast   2721.32080\n",
              "11  62.0  female  26.290       0.0    yes  southeast  27808.72510\n",
              "12  23.0    male  34.400       0.0     no  southwest   1826.84300\n",
              "13  56.0  female  39.820       0.0     no  southeast  11090.71780\n",
              "14  27.0    male  42.130       0.0    yes  southeast  39611.75770\n",
              "15  19.0    male  24.600       1.0     no  southwest   1837.23700\n",
              "16  52.0  female  30.780       1.0     no  northeast  10797.33620\n",
              "17  23.0    male  23.845       0.0     no  northeast   2395.17155\n",
              "18  56.0    male  40.300       0.0     no  southwest  10602.38500\n",
              "19  30.0    male  35.300       0.0    yes  southwest  36837.46700\n",
              "20  60.0  female  36.005       0.0     no  northeast  13228.84695\n",
              "21  30.0  female  32.400       1.0     no  southwest   4149.73600\n",
              "22  18.0    male  34.100       0.0     no  southeast   1137.01100\n",
              "23  34.0  female  31.920       1.0    yes  northeast  37701.87680\n",
              "24  37.0    male  28.025       2.0     no  northwest   6203.90175\n",
              "25  59.0  female  27.720       3.0     no  southeast  14001.13380\n",
              "26  63.0  female  23.085       0.0     no  northeast  14451.83515\n",
              "27  55.0  female  32.775       2.0     no  northwest  12268.63225\n",
              "28  23.0    male  17.385       1.0     no  northwest   2775.19215\n",
              "29  31.0    male  36.300       2.0    yes  southwest  38711.00000"
            ],
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              "      <th>5</th>\n",
              "      <td>31.0</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>46.0</td>\n",
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              "      <td>1.0</td>\n",
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              "      <th>7</th>\n",
              "      <td>37.0</td>\n",
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              "      <td>3.0</td>\n",
              "      <td>no</td>\n",
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              "      <td>7281.50560</td>\n",
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              "      <th>8</th>\n",
              "      <td>37.0</td>\n",
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              "      <td>29.830</td>\n",
              "      <td>2.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>6406.41070</td>\n",
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              "      <td>60.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>28923.13692</td>\n",
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              "      <th>10</th>\n",
              "      <td>25.0</td>\n",
              "      <td>male</td>\n",
              "      <td>26.220</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>2721.32080</td>\n",
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              "      <th>11</th>\n",
              "      <td>62.0</td>\n",
              "      <td>female</td>\n",
              "      <td>26.290</td>\n",
              "      <td>0.0</td>\n",
              "      <td>yes</td>\n",
              "      <td>southeast</td>\n",
              "      <td>27808.72510</td>\n",
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              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>23.0</td>\n",
              "      <td>male</td>\n",
              "      <td>34.400</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southwest</td>\n",
              "      <td>1826.84300</td>\n",
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              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>56.0</td>\n",
              "      <td>female</td>\n",
              "      <td>39.820</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southeast</td>\n",
              "      <td>11090.71780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>27.0</td>\n",
              "      <td>male</td>\n",
              "      <td>42.130</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>southeast</td>\n",
              "      <td>39611.75770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>19.0</td>\n",
              "      <td>male</td>\n",
              "      <td>24.600</td>\n",
              "      <td>1.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southwest</td>\n",
              "      <td>1837.23700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>52.0</td>\n",
              "      <td>female</td>\n",
              "      <td>30.780</td>\n",
              "      <td>1.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>10797.33620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>23.0</td>\n",
              "      <td>male</td>\n",
              "      <td>23.845</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>2395.17155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>56.0</td>\n",
              "      <td>male</td>\n",
              "      <td>40.300</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southwest</td>\n",
              "      <td>10602.38500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>30.0</td>\n",
              "      <td>male</td>\n",
              "      <td>35.300</td>\n",
              "      <td>0.0</td>\n",
              "      <td>yes</td>\n",
              "      <td>southwest</td>\n",
              "      <td>36837.46700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>60.0</td>\n",
              "      <td>female</td>\n",
              "      <td>36.005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>13228.84695</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>30.0</td>\n",
              "      <td>female</td>\n",
              "      <td>32.400</td>\n",
              "      <td>1.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southwest</td>\n",
              "      <td>4149.73600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>18.0</td>\n",
              "      <td>male</td>\n",
              "      <td>34.100</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southeast</td>\n",
              "      <td>1137.01100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>34.0</td>\n",
              "      <td>female</td>\n",
              "      <td>31.920</td>\n",
              "      <td>1.0</td>\n",
              "      <td>yes</td>\n",
              "      <td>northeast</td>\n",
              "      <td>37701.87680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>37.0</td>\n",
              "      <td>male</td>\n",
              "      <td>28.025</td>\n",
              "      <td>2.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>6203.90175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>59.0</td>\n",
              "      <td>female</td>\n",
              "      <td>27.720</td>\n",
              "      <td>3.0</td>\n",
              "      <td>no</td>\n",
              "      <td>southeast</td>\n",
              "      <td>14001.13380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>63.0</td>\n",
              "      <td>female</td>\n",
              "      <td>23.085</td>\n",
              "      <td>0.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>14451.83515</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>55.0</td>\n",
              "      <td>female</td>\n",
              "      <td>32.775</td>\n",
              "      <td>2.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>12268.63225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>23.0</td>\n",
              "      <td>male</td>\n",
              "      <td>17.385</td>\n",
              "      <td>1.0</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>2775.19215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>31.0</td>\n",
              "      <td>male</td>\n",
              "      <td>36.300</td>\n",
              "      <td>2.0</td>\n",
              "      <td>yes</td>\n",
              "      <td>southwest</td>\n",
              "      <td>38711.00000</td>\n",
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    {
      "cell_type": "code",
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        "df[df.duplicated()]"
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        "colab": {
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          "height": 81
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        "id": "xHyo7tLQx3ud",
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      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      age   sex    bmi  children smoker     region    charges\n",
              "581  19.0  male  30.59       0.0     no  northwest  1639.5631"
            ],
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              "      <td>1639.5631</td>\n",
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              "            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",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.drop_duplicates(keep='first', inplace = True)"
      ],
      "metadata": {
        "id": "xCUSWrt8x7cD"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sns.heatmap(df.corr(),annot=True)"
      ],
      "metadata": {
        "colab": {
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          "height": 289
        },
        "id": "UnWPpnPQwCWV",
        "outputId": "c4d2055c-d494-4b94-abf0-1b1529451d52"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f81753a6f50>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "le=LabelEncoder()\n",
        "df['sex']= le.fit_transform(df['sex'])\n",
        "df['age']= le.fit_transform(df['age'])\n",
        "df['bmi']= le.fit_transform(df['bmi'])\n",
        "df['charges']= le.fit_transform(df['charges'])\n",
        "df['children']= le.fit_transform(df['children'])\n",
        "df['region']= le.fit_transform(df['region'])\n",
        "df['smoker']= le.fit_transform(df['smoker'])"
      ],
      "metadata": {
        "id": "6kYSWvy5yJix"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KgzxPrU5yL1I",
        "outputId": "75da065d-0b2c-4ec2-c109-27ced4bafb7a"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1337, 7)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(10) \n",
        "# 0=female smoker=1\n",
        "#sw=3,se=2,nw=1,ne=0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "rz9mKKxKyP94",
        "outputId": "9197b98d-1b25-4a33-b56e-8d0177074943"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   age  sex  bmi  children  smoker  region  charges\n",
              "0    1    0  197         0       1       3     1005\n",
              "1    0    1  350         1       0       2       57\n",
              "2   10    1  331         3       0       2      306\n",
              "3   15    1   73         0       0       1     1097\n",
              "4   14    1  223         0       0       1      254\n",
              "5   13    0  144         0       0       2      247\n",
              "6   28    0  342         1       0       2      586\n",
              "7   19    0  193         3       0       1      526\n",
              "8   19    1  250         2       0       0      459\n",
              "9   42    0  147         0       0       1     1169"
            ],
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              "      <td>147</td>\n",
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              "      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-b9154a5e-c9bb-4dec-83e6-2a59bb5e35c9 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-b9154a5e-c9bb-4dec-83e6-2a59bb5e35c9');\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": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x=df.drop(['charges'], axis=1)\n",
        "y=df['charges']"
      ],
      "metadata": {
        "id": "WqgqnWXyyV5C"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=42)"
      ],
      "metadata": {
        "id": "wxXsbVS7yZXU"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "zd9fc_mDyn1U",
        "outputId": "aac179ab-875a-4541-b7cb-1cce67f67200"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      age  sex  bmi  children  smoker  region\n",
              "900    31    1   70         0       0       0\n",
              "1064   11    0  141         4       0       3\n",
              "1256   33    0  412         3       0       1\n",
              "298    13    1  364         3       1       1\n",
              "237    13    1  454         2       0       2\n",
              "...   ...  ...  ...       ...     ...     ...\n",
              "534    46    1  491         0       0       2\n",
              "542    45    0  411         0       0       2\n",
              "760     4    0  369         2       0       0\n",
              "1284   43    1  411         1       1       3\n",
              "1285   29    0  112         0       0       0\n",
              "\n",
              "[268 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-05a5fad3-aa13-4b55-8126-fc688890093e\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>bmi</th>\n",
              "      <th>children</th>\n",
              "      <th>smoker</th>\n",
              "      <th>region</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>900</th>\n",
              "      <td>31</td>\n",
              "      <td>1</td>\n",
              "      <td>70</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1064</th>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "      <td>141</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1256</th>\n",
              "      <td>33</td>\n",
              "      <td>0</td>\n",
              "      <td>412</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>13</td>\n",
              "      <td>1</td>\n",
              "      <td>364</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237</th>\n",
              "      <td>13</td>\n",
              "      <td>1</td>\n",
              "      <td>454</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>46</td>\n",
              "      <td>1</td>\n",
              "      <td>491</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>542</th>\n",
              "      <td>45</td>\n",
              "      <td>0</td>\n",
              "      <td>411</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>760</th>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>369</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>1284</th>\n",
              "      <td>43</td>\n",
              "      <td>1</td>\n",
              "      <td>411</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1285</th>\n",
              "      <td>29</td>\n",
              "      <td>0</td>\n",
              "      <td>112</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>268 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-05a5fad3-aa13-4b55-8126-fc688890093e')\"\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",
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              "  </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",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      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-05a5fad3-aa13-4b55-8126-fc688890093e 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-05a5fad3-aa13-4b55-8126-fc688890093e');\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": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[899]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kR9-h6oICCn4",
        "outputId": "90c63ed7-052d-4058-f19b-e8fae0d51580"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age          31\n",
              "sex           1\n",
              "bmi          70\n",
              "children      0\n",
              "smoker        0\n",
              "region        0\n",
              "charges     626\n",
              "Name: 900, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "rf = RandomForestRegressor(n_estimators = 10, random_state = 1)\n",
        "rf.fit(x_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XZ8pZ3O-y5PU",
        "outputId": "65b01f0c-1c70-498c-9daf-833fb9f7f020"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestRegressor(n_estimators=10, random_state=1)"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred_rf = rf.predict(x_test)\n",
        "y_pred_rf"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XKTmlD7fy8Bp",
        "outputId": "481fb82b-52cc-4878-ad4f-8d220fc3a43c"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 653.2,  349.7,  748.6, 1265.3,  454.6,  702.7, 1242.1,  103.2,\n",
              "        591.1,  728.9,  943.8, 1109.9, 1265.7,  914.1,  495.3,  602.4,\n",
              "        529.9, 1257.9,  333.2,  252. ,  289.9, 1076.2,  757.5, 1075.5,\n",
              "       1244.3,  936.3, 1287.3, 1303.1,  714.7,  752.8,  278.1,  642.6,\n",
              "         56.4,  886.3, 1320. ,  686.6,  445.3,  426.3, 1101.2,  615.3,\n",
              "        207.8, 1083.2, 1270.1,  666. ,  618.7,  203.6,  197.7,  634.9,\n",
              "        359.2,  740.1,  346.1,  473.8, 1116.3,  136.6,  561.4,  575.4,\n",
              "        712.6,  210.3, 1271.5,  539.3,  767.4,  440.7,  935.1,   57.3,\n",
              "        805.1,  894.1,  422.7, 1107.5,  997.4,  970.1,  812. ,  989.2,\n",
              "        619.2,  289.1,  850.9,   78.6,  915.3,  425.9,  834.3,  887.9,\n",
              "        595.4,  911.4,  900.1,  658.8, 1167. ,  894.4,  231.5,   56.4,\n",
              "        586.7,  190.3,  983.9, 1008.5,  309.3,  338.5,   72.5, 1284.5,\n",
              "        782.2,  642.7,   49. ,  626.2,  943.2,  866.4, 1133.1,  848.2,\n",
              "       1278.5,   28.8, 1270.3, 1040.1,  871.5,  360.8,  459.6,  848.5,\n",
              "        573.7,  512. ,  128.4,   92.3,  137.8,    8.8,  170. ,  783.4,\n",
              "       1287.8,  446.8,  539.1,  427.3,  675.4,  583.4,  295. ,  914.3,\n",
              "       1256.1, 1316.7, 1166.2,  709.8,  143.8,  752.1,  427.1,  662.5,\n",
              "       1312. , 1088.7, 1017.4,  250.5,  393.9,  763.4, 1301.3,  819.3,\n",
              "         96.5,  416.7,  304.8,  545.2, 1296.6,  920.3,  444.7,  508.7,\n",
              "        362.2,  958.7,  585.8, 1214. , 1281.9,  712.3,  704.5,  705.7,\n",
              "        759.7,  424.1,  812.5,  851.4, 1285.3, 1249.5,  712.7, 1030.8,\n",
              "        493.1,  244.8,  417.6,   39.7,  253.7,  913.8,  683.8,  988. ,\n",
              "        124.3,  707.5,  615.2,  747.1,  977.5,  180.2,  762.7,  841.6,\n",
              "       1251.9,  844.9,  345.6,  405.5,   88.4, 1289.8,  194.9, 1118.9,\n",
              "        805.9,  375.4,  103.5,  219.8, 1251.5,  278.8,  949.9,  955.5,\n",
              "       1196.7, 1039.2,  331.6,  748.9, 1049. ,  550.3,  544.2,  574.7,\n",
              "        314.2, 1271.8, 1157.1,  625.9,  423. ,  561.9,  911.4,   33.7,\n",
              "         94.4,  578.8,  748.4,  215.1,  200.7, 1303.8, 1304.7,  979.5,\n",
              "        666.3, 1310.4, 1269. ,  736.9, 1209.4,  440.7,  903.4, 1242.3,\n",
              "        536. ,  486.8,  873.2,  794.2,  910.2,   42.2,  187.3,  223.2,\n",
              "        280.5,  156.4,  255.7,  782.6,   33. ,  695.5,  341.6,  645.4,\n",
              "        274.6,  651.3,  148.1,  814.6,  894.9,  974.3, 1287.9,  940. ,\n",
              "        868.4,  664.1,  593.3,  750.7, 1226.2, 1312.2,  895.4,  953.7,\n",
              "        965.6,  863.2, 1318.9,  705.4])"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Model Evaluation\n",
        "from sklearn import metrics\n",
        "meanAbErr = metrics.mean_absolute_error(y_test, y_pred_rf)\n",
        "meanSqErr = metrics.mean_squared_error(y_test, y_pred_rf)\n",
        "rootMeanSqErr = np.sqrt(metrics.mean_squared_error(y_test, y_pred_rf))\n",
        "print('R squared: {:.2f}'.format(rf.score(x,y)*100))\n",
        "print('Mean Absolute Error:', meanAbErr)\n",
        "print('Mean Square Error:', meanSqErr)\n",
        "print('Root Mean Square Error:', rootMeanSqErr)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Niybp2YEAE6C",
        "outputId": "8a99c6ce-0602-4aeb-d10a-7f115f113233"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "R squared: 92.04\n",
            "Mean Absolute Error: 88.16753731343285\n",
            "Mean Square Error: 32138.244813432833\n",
            "Root Mean Square Error: 179.27142776648162\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Saving Trained Model"
      ],
      "metadata": {
        "id": "10pr6wfnzMHi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# saving model\n",
        "import pickle\n",
        "\n",
        "with open(\"model2\",\"wb\") as f:\n",
        "    pickle.dump(rf,f)"
      ],
      "metadata": {
        "id": "TP5NkjYHzLXb"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# loading saved model\n",
        "with open(\"model2\",\"rb\") as f:\n",
        "    m2=pickle.load(f)"
      ],
      "metadata": {
        "id": "bwKNw4gDzadw"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "m2.predict(x_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ia9hijugznEV",
        "outputId": "989eb73c-153d-4ecb-fa4a-fc3d364e5e5e"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 653.2,  349.7,  748.6, 1265.3,  454.6,  702.7, 1242.1,  103.2,\n",
              "        591.1,  728.9,  943.8, 1109.9, 1265.7,  914.1,  495.3,  602.4,\n",
              "        529.9, 1257.9,  333.2,  252. ,  289.9, 1076.2,  757.5, 1075.5,\n",
              "       1244.3,  936.3, 1287.3, 1303.1,  714.7,  752.8,  278.1,  642.6,\n",
              "         56.4,  886.3, 1320. ,  686.6,  445.3,  426.3, 1101.2,  615.3,\n",
              "        207.8, 1083.2, 1270.1,  666. ,  618.7,  203.6,  197.7,  634.9,\n",
              "        359.2,  740.1,  346.1,  473.8, 1116.3,  136.6,  561.4,  575.4,\n",
              "        712.6,  210.3, 1271.5,  539.3,  767.4,  440.7,  935.1,   57.3,\n",
              "        805.1,  894.1,  422.7, 1107.5,  997.4,  970.1,  812. ,  989.2,\n",
              "        619.2,  289.1,  850.9,   78.6,  915.3,  425.9,  834.3,  887.9,\n",
              "        595.4,  911.4,  900.1,  658.8, 1167. ,  894.4,  231.5,   56.4,\n",
              "        586.7,  190.3,  983.9, 1008.5,  309.3,  338.5,   72.5, 1284.5,\n",
              "        782.2,  642.7,   49. ,  626.2,  943.2,  866.4, 1133.1,  848.2,\n",
              "       1278.5,   28.8, 1270.3, 1040.1,  871.5,  360.8,  459.6,  848.5,\n",
              "        573.7,  512. ,  128.4,   92.3,  137.8,    8.8,  170. ,  783.4,\n",
              "       1287.8,  446.8,  539.1,  427.3,  675.4,  583.4,  295. ,  914.3,\n",
              "       1256.1, 1316.7, 1166.2,  709.8,  143.8,  752.1,  427.1,  662.5,\n",
              "       1312. , 1088.7, 1017.4,  250.5,  393.9,  763.4, 1301.3,  819.3,\n",
              "         96.5,  416.7,  304.8,  545.2, 1296.6,  920.3,  444.7,  508.7,\n",
              "        362.2,  958.7,  585.8, 1214. , 1281.9,  712.3,  704.5,  705.7,\n",
              "        759.7,  424.1,  812.5,  851.4, 1285.3, 1249.5,  712.7, 1030.8,\n",
              "        493.1,  244.8,  417.6,   39.7,  253.7,  913.8,  683.8,  988. ,\n",
              "        124.3,  707.5,  615.2,  747.1,  977.5,  180.2,  762.7,  841.6,\n",
              "       1251.9,  844.9,  345.6,  405.5,   88.4, 1289.8,  194.9, 1118.9,\n",
              "        805.9,  375.4,  103.5,  219.8, 1251.5,  278.8,  949.9,  955.5,\n",
              "       1196.7, 1039.2,  331.6,  748.9, 1049. ,  550.3,  544.2,  574.7,\n",
              "        314.2, 1271.8, 1157.1,  625.9,  423. ,  561.9,  911.4,   33.7,\n",
              "         94.4,  578.8,  748.4,  215.1,  200.7, 1303.8, 1304.7,  979.5,\n",
              "        666.3, 1310.4, 1269. ,  736.9, 1209.4,  440.7,  903.4, 1242.3,\n",
              "        536. ,  486.8,  873.2,  794.2,  910.2,   42.2,  187.3,  223.2,\n",
              "        280.5,  156.4,  255.7,  782.6,   33. ,  695.5,  341.6,  645.4,\n",
              "        274.6,  651.3,  148.1,  814.6,  894.9,  974.3, 1287.9,  940. ,\n",
              "        868.4,  664.1,  593.3,  750.7, 1226.2, 1312.2,  895.4,  953.7,\n",
              "        965.6,  863.2, 1318.9,  705.4])"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    }
  ]
}