Practise.ipynb

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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "\n"
      ]
    },
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      "source": [
        "df=pd.read_csv('CAR.csv')"
      ],
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        "df.head()"
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              "                       name  year  selling_price  km_driven    fuel  \\\n",
              "0             Maruti 800 AC  2007          60000      70000  Petrol   \n",
              "1  Maruti Wagon R LXI Minor  2007         135000      50000  Petrol   \n",
              "2      Hyundai Verna 1.6 SX  2012         600000     100000  Diesel   \n",
              "3    Datsun RediGO T Option  2017         250000      46000  Petrol   \n",
              "4     Honda Amaze VX i-DTEC  2014         450000     141000  Diesel   \n",
              "\n",
              "  seller_type transmission         owner  \n",
              "0  Individual       Manual   First Owner  \n",
              "1  Individual       Manual   First Owner  \n",
              "2  Individual       Manual   First Owner  \n",
              "3  Individual       Manual   First Owner  \n",
              "4  Individual       Manual  Second Owner  "
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              "                                     name  year  selling_price  km_driven  \\\n",
              "4335  Hyundai i20 Magna 1.4 CRDi (Diesel)  2014         409999      80000   \n",
              "4336           Hyundai i20 Magna 1.4 CRDi  2014         409999      80000   \n",
              "4337                  Maruti 800 AC BSIII  2009         110000      83000   \n",
              "4338     Hyundai Creta 1.6 CRDi SX Option  2016         865000      90000   \n",
              "4339                     Renault KWID RXT  2016         225000      40000   \n",
              "\n",
              "        fuel seller_type transmission         owner  \n",
              "4335  Diesel  Individual       Manual  Second Owner  \n",
              "4336  Diesel  Individual       Manual  Second Owner  \n",
              "4337  Petrol  Individual       Manual  Second Owner  \n",
              "4338  Diesel  Individual       Manual   First Owner  \n",
              "4339  Petrol  Individual       Manual   First Owner  "
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              "              year  selling_price      km_driven\n",
              "count  4340.000000   4.340000e+03    4340.000000\n",
              "mean   2013.090783   5.041273e+05   66215.777419\n",
              "std       4.215344   5.785487e+05   46644.102194\n",
              "min    1992.000000   2.000000e+04       1.000000\n",
              "25%    2011.000000   2.087498e+05   35000.000000\n",
              "50%    2014.000000   3.500000e+05   60000.000000\n",
              "75%    2016.000000   6.000000e+05   90000.000000\n",
              "max    2020.000000   8.900000e+06  806599.000000"
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              "      <th>mean</th>\n",
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              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>4.215344</td>\n",
              "      <td>5.785487e+05</td>\n",
              "      <td>46644.102194</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1992.000000</td>\n",
              "      <td>2.000000e+04</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2011.000000</td>\n",
              "      <td>2.087498e+05</td>\n",
              "      <td>35000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2014.000000</td>\n",
              "      <td>3.500000e+05</td>\n",
              "      <td>60000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2016.000000</td>\n",
              "      <td>6.000000e+05</td>\n",
              "      <td>90000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2020.000000</td>\n",
              "      <td>8.900000e+06</td>\n",
              "      <td>806599.000000</td>\n",
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      "outputs": [
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 4340 entries, 0 to 4339\n",
            "Data columns (total 8 columns):\n",
            " #   Column         Non-Null Count  Dtype \n",
            "---  ------         --------------  ----- \n",
            " 0   name           4340 non-null   object\n",
            " 1   year           4340 non-null   int64 \n",
            " 2   selling_price  4340 non-null   int64 \n",
            " 3   km_driven      4340 non-null   int64 \n",
            " 4   fuel           4340 non-null   object\n",
            " 5   seller_type    4340 non-null   object\n",
            " 6   transmission   4340 non-null   object\n",
            " 7   owner          4340 non-null   object\n",
            "dtypes: int64(3), object(5)\n",
            "memory usage: 271.4+ KB\n"
          ]
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    {
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        "df[['name']].value_counts()"
      ],
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                                \n",
              "Maruti Swift Dzire VDI                  69\n",
              "Maruti Alto 800 LXI                     59\n",
              "Maruti Alto LXi                         47\n",
              "Hyundai EON Era Plus                    35\n",
              "Maruti Alto LX                          35\n",
              "                                        ..\n",
              "Mahindra KUV 100 G80 K4 Plus             1\n",
              "Mahindra KUV 100 mFALCON D75 K8          1\n",
              "Mahindra KUV 100 mFALCON D75 K8 AW       1\n",
              "Mahindra KUV 100 mFALCON G80 K2 Plus     1\n",
              "Volvo XC60 D5 Inscription                1\n",
              "Length: 1491, dtype: int64"
            ]
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          "metadata": {},
          "execution_count": 16
        }
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      "execution_count": null,
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fuel      seller_type       transmission  owner               \n",
              "Petrol    Individual        Manual        First Owner             892\n",
              "Diesel    Individual        Manual        First Owner             835\n",
              "Petrol    Individual        Manual        Second Owner            454\n",
              "Diesel    Individual        Manual        Second Owner            453\n",
              "          Dealer            Manual        First Owner             336\n",
              "Petrol    Dealer            Manual        First Owner             306\n",
              "Diesel    Individual        Manual        Third Owner             142\n",
              "Petrol    Individual        Manual        Third Owner             130\n",
              "Diesel    Dealer            Automatic     First Owner             114\n",
              "Petrol    Dealer            Automatic     First Owner              80\n",
              "Diesel    Individual        Automatic     First Owner              73\n",
              "Petrol    Individual        Automatic     First Owner              67\n",
              "Diesel    Dealer            Manual        Second Owner             56\n",
              "Petrol    Trustmark Dealer  Manual        First Owner              49\n",
              "          Dealer            Manual        Second Owner             44\n",
              "          Individual        Manual        Fourth & Above Owner     41\n",
              "Diesel    Trustmark Dealer  Manual        First Owner              34\n",
              "          Individual        Manual        Fourth & Above Owner     32\n",
              "                            Automatic     Second Owner             31\n",
              "Petrol    Individual        Automatic     Second Owner             20\n",
              "CNG       Individual        Manual        First Owner              14\n",
              "                                          Second Owner             12\n",
              "Diesel    Trustmark Dealer  Automatic     First Owner              12\n",
              "Petrol    Individual        Automatic     Third Owner              10\n",
              "Diesel    Dealer            Automatic     Second Owner             10\n",
              "LPG       Individual        Manual        Second Owner             10\n",
              "Diesel    Individual        Automatic     Third Owner               9\n",
              "Petrol    Dealer            Manual        Test Drive Car            9\n",
              "LPG       Individual        Manual        First Owner               9\n",
              "Petrol    Dealer            Automatic     Second Owner              9\n",
              "CNG       Dealer            Manual        First Owner               7\n",
              "Diesel    Dealer            Manual        Test Drive Car            7\n",
              "Petrol    Dealer            Manual        Third Owner               4\n",
              "          Trustmark Dealer  Automatic     First Owner               3\n",
              "CNG       Individual        Manual        Fourth & Above Owner      3\n",
              "Diesel    Dealer            Manual        Third Owner               3\n",
              "LPG       Individual        Manual        Third Owner               2\n",
              "Petrol    Trustmark Dealer  Automatic     Second Owner              2\n",
              "CNG       Dealer            Manual        Second Owner              2\n",
              "Diesel    Trustmark Dealer  Automatic     Second Owner              2\n",
              "CNG       Individual        Manual        Third Owner               2\n",
              "Diesel    Dealer            Automatic     Third Owner               2\n",
              "                            Manual        Fourth & Above Owner      1\n",
              "Petrol    Individual        Automatic     Fourth & Above Owner      1\n",
              "LPG       Individual        Manual        Fourth & Above Owner      1\n",
              "Diesel    Individual        Automatic     Fourth & Above Owner      1\n",
              "Petrol    Dealer            Manual        Fourth & Above Owner      1\n",
              "LPG       Dealer            Manual        First Owner               1\n",
              "Petrol    Dealer            Automatic     Test Drive Car            1\n",
              "Electric  Dealer            Automatic     Second Owner              1\n",
              "dtype: int64"
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          "output_type": "execute_result",
          "data": {
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              "(4340, 8)"
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          "metadata": {},
          "execution_count": 21
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    {
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      "source": [
        "df.replace({'fuel':{'Petrol':0,'Diesel':1,'CNG':2,'LPG':3,'Electric':4}},inplace = True)\n",
        "df.replace({'seller_type':{'Individual':0,'Dealer':1,'Trustmark Dealer':2}},inplace = True)\n",
        "df.replace({'transmission':{'Manual':0,'Automatic':1}},inplace = True)\n",
        "df.replace({'owner':{'First Owner':0,'Second Owner':1,'Third Owner':2,'Fourth & Above Owner':3,'Test Drive Car':4}},inplace = True)\n"
      ],
      "metadata": {
        "id": "um4bo4ITtt7s"
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      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "code",
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        "y=df['selling_price']"
      ],
      "metadata": {
        "id": "550ps77ZxHnZ"
      },
      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "code",
      "source": [
        "x=df[['year','km_driven','fuel','seller_type','transmission','owner']]"
      ],
      "metadata": {
        "id": "tyg8AFDfxfoV"
      },
      "execution_count": null,
      "outputs": []
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              "(4340, 6)"
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              "      year  km_driven  fuel  seller_type  transmission  owner\n",
              "0     2007      70000     0            0             0      0\n",
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              "...    ...        ...   ...          ...           ...    ...\n",
              "4335  2014      80000     1            0             0      1\n",
              "4336  2014      80000     1            0             0      1\n",
              "4337  2009      83000     0            0             0      1\n",
              "4338  2016      90000     1            0             0      0\n",
              "4339  2016      40000     0            0             0      0\n",
              "\n",
              "[4340 rows x 6 columns]"
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              "    .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-a5d5be5d-ea0d-4125-b8cc-26eb5f542dac 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-a5d5be5d-ea0d-4125-b8cc-26eb5f542dac');\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": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "metadata": {
        "id": "8RhTqibIyUUc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3)"
      ],
      "metadata": {
        "id": "UuOF4Ioyylgu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train.shape, x_test.shape, y_train.shape, y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cc5W_jjPzAp8",
        "outputId": "985dd806-103c-4696-b437-837b60926936"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((3038, 6), (1302, 6), (3038,), (1302,))"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LinearRegression\n"
      ],
      "metadata": {
        "id": "SDvNEppGzmv6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lr = LinearRegression()"
      ],
      "metadata": {
        "id": "WfSL3Lqgz3pq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lr.fit(x_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D3glp6Wsz8f0",
        "outputId": "c45c99c7-03f5-423c-ee7f-3c9eb24e7a8b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression()"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred=lr.predict(x_test)\n"
      ],
      "metadata": {
        "id": "gvB1OL_21RLA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "383tXHSX1dD9",
        "outputId": "6e9f4b7c-7c92-4c5d-9f15-c46edd46b6ab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1302,)"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t-K36swQ1giG",
        "outputId": "06dc812f-9589-4987-c9a8-79bd4cca1105"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([415176.49873485, 147660.25646169, 808258.87580273, ...,\n",
              "       501961.09040689, 411901.86028959, 258229.85182078])"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import mean_squared_error"
      ],
      "metadata": {
        "id": "9poeTanI2wqL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_squared_error(y_test,y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B2LnR3Hs3XM1",
        "outputId": "cba0ad80-7ab4-447e-ba0f-93124e3615c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "183057052200.54288"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import mean_absolute_error\n"
      ],
      "metadata": {
        "id": "0nGkB2Rh4Tof"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_absolute_error(y_test,y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HMnyBGCJ44Vs",
        "outputId": "5ddfa14d-68b7-46b8-95f4-fe30f0b50638"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "228246.07334658128"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    }
  ]
}