Time_Series_Forecasting_ML.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Time_Series_Forecasting_ML.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "UJ0Cz6QGg05b"
      },
      "source": [
        "import pandas as pd\n",
        "df=pd.DataFrame()"
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UV7Nv-cdofN_"
      },
      "source": [
        "df = pd.read_csv('/content/Alcohol_Sales.csv',index_col='DATE',parse_dates=True)\n",
        "df.index.freq = 'MS'"
      ],
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "Q7mpZYaUolP5",
        "outputId": "4febfc3f-228f-473c-8aee-0901aa566d90"
      },
      "source": [
        "df.tail()"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>S4248SM144NCEN</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DATE</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>12396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>13914</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>14174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>15504</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-01</th>\n",
              "      <td>10718</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            S4248SM144NCEN\n",
              "DATE                      \n",
              "2018-09-01           12396\n",
              "2018-10-01           13914\n",
              "2018-11-01           14174\n",
              "2018-12-01           15504\n",
              "2019-01-01           10718"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "DxtdaUjnhTtM",
        "outputId": "bcc8f5a4-8c60-475f-cb3c-1d153a0484c9"
      },
      "source": [
        "df.columns = ['Sales']\n",
        "df.plot(figsize=(12,8))"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f37a68440d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "id": "kKO7D16Uh6IT",
        "outputId": "35a7f0cc-26c3-479f-e99a-c1d0c8b27abf"
      },
      "source": [
        "df['Sale_LastMonth']=df['Sales'].shift(+1)\n",
        "df['Sale_2Monthsback']=df['Sales'].shift(+2)\n",
        "df['Sale_3Monthsback']=df['Sales'].shift(+3)\n",
        "df"
      ],
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sales</th>\n",
              "      <th>Sale_LastMonth</th>\n",
              "      <th>Sale_2Monthsback</th>\n",
              "      <th>Sale_3Monthsback</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DATE</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1992-01-01</th>\n",
              "      <td>3459</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-02-01</th>\n",
              "      <td>3458</td>\n",
              "      <td>3459.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-03-01</th>\n",
              "      <td>4002</td>\n",
              "      <td>3458.0</td>\n",
              "      <td>3459.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-04-01</th>\n",
              "      <td>4564</td>\n",
              "      <td>4002.0</td>\n",
              "      <td>3458.0</td>\n",
              "      <td>3459.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-05-01</th>\n",
              "      <td>4221</td>\n",
              "      <td>4564.0</td>\n",
              "      <td>4002.0</td>\n",
              "      <td>3458.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>12396</td>\n",
              "      <td>14257.0</td>\n",
              "      <td>12640.0</td>\n",
              "      <td>14583.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>13914</td>\n",
              "      <td>12396.0</td>\n",
              "      <td>14257.0</td>\n",
              "      <td>12640.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>14174</td>\n",
              "      <td>13914.0</td>\n",
              "      <td>12396.0</td>\n",
              "      <td>14257.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>15504</td>\n",
              "      <td>14174.0</td>\n",
              "      <td>13914.0</td>\n",
              "      <td>12396.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-01</th>\n",
              "      <td>10718</td>\n",
              "      <td>15504.0</td>\n",
              "      <td>14174.0</td>\n",
              "      <td>13914.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>325 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Sales  Sale_LastMonth  Sale_2Monthsback  Sale_3Monthsback\n",
              "DATE                                                                 \n",
              "1992-01-01   3459             NaN               NaN               NaN\n",
              "1992-02-01   3458          3459.0               NaN               NaN\n",
              "1992-03-01   4002          3458.0            3459.0               NaN\n",
              "1992-04-01   4564          4002.0            3458.0            3459.0\n",
              "1992-05-01   4221          4564.0            4002.0            3458.0\n",
              "...           ...             ...               ...               ...\n",
              "2018-09-01  12396         14257.0           12640.0           14583.0\n",
              "2018-10-01  13914         12396.0           14257.0           12640.0\n",
              "2018-11-01  14174         13914.0           12396.0           14257.0\n",
              "2018-12-01  15504         14174.0           13914.0           12396.0\n",
              "2019-01-01  10718         15504.0           14174.0           13914.0\n",
              "\n",
              "[325 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "id": "MzLs40rfoOmE",
        "outputId": "286c2990-5d7d-4245-d1da-a8b047807b2a"
      },
      "source": [
        "df=df.dropna()\n",
        "df"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sales</th>\n",
              "      <th>Sale_LastMonth</th>\n",
              "      <th>Sale_2Monthsback</th>\n",
              "      <th>Sale_3Monthsback</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DATE</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1992-04-01</th>\n",
              "      <td>4564</td>\n",
              "      <td>4002.0</td>\n",
              "      <td>3458.0</td>\n",
              "      <td>3459.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-05-01</th>\n",
              "      <td>4221</td>\n",
              "      <td>4564.0</td>\n",
              "      <td>4002.0</td>\n",
              "      <td>3458.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-06-01</th>\n",
              "      <td>4529</td>\n",
              "      <td>4221.0</td>\n",
              "      <td>4564.0</td>\n",
              "      <td>4002.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-07-01</th>\n",
              "      <td>4466</td>\n",
              "      <td>4529.0</td>\n",
              "      <td>4221.0</td>\n",
              "      <td>4564.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-08-01</th>\n",
              "      <td>4137</td>\n",
              "      <td>4466.0</td>\n",
              "      <td>4529.0</td>\n",
              "      <td>4221.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-01</th>\n",
              "      <td>12396</td>\n",
              "      <td>14257.0</td>\n",
              "      <td>12640.0</td>\n",
              "      <td>14583.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-10-01</th>\n",
              "      <td>13914</td>\n",
              "      <td>12396.0</td>\n",
              "      <td>14257.0</td>\n",
              "      <td>12640.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>14174</td>\n",
              "      <td>13914.0</td>\n",
              "      <td>12396.0</td>\n",
              "      <td>14257.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-01</th>\n",
              "      <td>15504</td>\n",
              "      <td>14174.0</td>\n",
              "      <td>13914.0</td>\n",
              "      <td>12396.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-01</th>\n",
              "      <td>10718</td>\n",
              "      <td>15504.0</td>\n",
              "      <td>14174.0</td>\n",
              "      <td>13914.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>322 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Sales  Sale_LastMonth  Sale_2Monthsback  Sale_3Monthsback\n",
              "DATE                                                                 \n",
              "1992-04-01   4564          4002.0            3458.0            3459.0\n",
              "1992-05-01   4221          4564.0            4002.0            3458.0\n",
              "1992-06-01   4529          4221.0            4564.0            4002.0\n",
              "1992-07-01   4466          4529.0            4221.0            4564.0\n",
              "1992-08-01   4137          4466.0            4529.0            4221.0\n",
              "...           ...             ...               ...               ...\n",
              "2018-09-01  12396         14257.0           12640.0           14583.0\n",
              "2018-10-01  13914         12396.0           14257.0           12640.0\n",
              "2018-11-01  14174         13914.0           12396.0           14257.0\n",
              "2018-12-01  15504         14174.0           13914.0           12396.0\n",
              "2019-01-01  10718         15504.0           14174.0           13914.0\n",
              "\n",
              "[322 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rf0EZs7siAiU"
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "lin_model=LinearRegression()"
      ],
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sOxBkE40uRA1"
      },
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "model=RandomForestRegressor(n_estimators=100,max_features=3, random_state=1)\n"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ahAlfSPVv75K",
        "outputId": "5ea7ee90-2535-494f-df5e-2ae84d7bad2a"
      },
      "source": [
        "import numpy as np\n",
        "x1,x2,x3,y=df['Sale_LastMonth'],df['Sale_2Monthsback'],df['Sale_3Monthsback'],df['Sales']\n",
        "x1,x2,x3,y=np.array(x1),np.array(x2),np.array(x3),np.array(y)\n",
        "x1,x2,x3,y=x1.reshape(-1,1),x2.reshape(-1,1),x3.reshape(-1,1),y.reshape(-1,1)\n",
        "final_x=np.concatenate((x1,x2,x3),axis=1)\n",
        "print(final_x)"
      ],
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[ 4002.  3458.  3459.]\n",
            " [ 4564.  4002.  3458.]\n",
            " [ 4221.  4564.  4002.]\n",
            " [ 4529.  4221.  4564.]\n",
            " [ 4466.  4529.  4221.]\n",
            " [ 4137.  4466.  4529.]\n",
            " [ 4126.  4137.  4466.]\n",
            " [ 4259.  4126.  4137.]\n",
            " [ 4240.  4259.  4126.]\n",
            " [ 4936.  4240.  4259.]\n",
            " [ 3031.  4936.  4240.]\n",
            " [ 3261.  3031.  4936.]\n",
            " [ 4160.  3261.  3031.]\n",
            " [ 4377.  4160.  3261.]\n",
            " [ 4307.  4377.  4160.]\n",
            " [ 4696.  4307.  4377.]\n",
            " [ 4458.  4696.  4307.]\n",
            " [ 4457.  4458.  4696.]\n",
            " [ 4364.  4457.  4458.]\n",
            " [ 4236.  4364.  4457.]\n",
            " [ 4500.  4236.  4364.]\n",
            " [ 4974.  4500.  4236.]\n",
            " [ 3075.  4974.  4500.]\n",
            " [ 3377.  3075.  4974.]\n",
            " [ 4443.  3377.  3075.]\n",
            " [ 4261.  4443.  3377.]\n",
            " [ 4460.  4261.  4443.]\n",
            " [ 4985.  4460.  4261.]\n",
            " [ 4324.  4985.  4460.]\n",
            " [ 4719.  4324.  4985.]\n",
            " [ 4374.  4719.  4324.]\n",
            " [ 4248.  4374.  4719.]\n",
            " [ 4784.  4248.  4374.]\n",
            " [ 4971.  4784.  4248.]\n",
            " [ 3370.  4971.  4784.]\n",
            " [ 3484.  3370.  4971.]\n",
            " [ 4269.  3484.  3370.]\n",
            " [ 3994.  4269.  3484.]\n",
            " [ 4715.  3994.  4269.]\n",
            " [ 4974.  4715.  3994.]\n",
            " [ 4223.  4974.  4715.]\n",
            " [ 5000.  4223.  4974.]\n",
            " [ 4235.  5000.  4223.]\n",
            " [ 4554.  4235.  5000.]\n",
            " [ 4851.  4554.  4235.]\n",
            " [ 4826.  4851.  4554.]\n",
            " [ 3699.  4826.  4851.]\n",
            " [ 3983.  3699.  4826.]\n",
            " [ 4262.  3983.  3699.]\n",
            " [ 4619.  4262.  3983.]\n",
            " [ 5219.  4619.  4262.]\n",
            " [ 4836.  5219.  4619.]\n",
            " [ 4941.  4836.  5219.]\n",
            " [ 5062.  4941.  4836.]\n",
            " [ 4365.  5062.  4941.]\n",
            " [ 5012.  4365.  5062.]\n",
            " [ 4850.  5012.  4365.]\n",
            " [ 5097.  4850.  5012.]\n",
            " [ 3758.  5097.  4850.]\n",
            " [ 3825.  3758.  5097.]\n",
            " [ 4454.  3825.  3758.]\n",
            " [ 4635.  4454.  3825.]\n",
            " [ 5210.  4635.  4454.]\n",
            " [ 5057.  5210.  4635.]\n",
            " [ 5231.  5057.  5210.]\n",
            " [ 5034.  5231.  5057.]\n",
            " [ 4970.  5034.  5231.]\n",
            " [ 5342.  4970.  5034.]\n",
            " [ 4831.  5342.  4970.]\n",
            " [ 5965.  4831.  5342.]\n",
            " [ 3796.  5965.  4831.]\n",
            " [ 4019.  3796.  5965.]\n",
            " [ 4898.  4019.  3796.]\n",
            " [ 5090.  4898.  4019.]\n",
            " [ 5237.  5090.  4898.]\n",
            " [ 5447.  5237.  5090.]\n",
            " [ 5435.  5447.  5237.]\n",
            " [ 5107.  5435.  5447.]\n",
            " [ 5515.  5107.  5435.]\n",
            " [ 5583.  5515.  5107.]\n",
            " [ 5346.  5583.  5515.]\n",
            " [ 6286.  5346.  5583.]\n",
            " [ 4032.  6286.  5346.]\n",
            " [ 4435.  4032.  6286.]\n",
            " [ 5479.  4435.  4032.]\n",
            " [ 5483.  5479.  4435.]\n",
            " [ 5587.  5483.  5479.]\n",
            " [ 6176.  5587.  5483.]\n",
            " [ 5621.  6176.  5587.]\n",
            " [ 5889.  5621.  6176.]\n",
            " [ 5828.  5889.  5621.]\n",
            " [ 5849.  5828.  5889.]\n",
            " [ 6180.  5849.  5828.]\n",
            " [ 6771.  6180.  5849.]\n",
            " [ 4243.  6771.  6180.]\n",
            " [ 4952.  4243.  6771.]\n",
            " [ 6008.  4952.  4243.]\n",
            " [ 5353.  6008.  4952.]\n",
            " [ 6435.  5353.  6008.]\n",
            " [ 6673.  6435.  5353.]\n",
            " [ 5636.  6673.  6435.]\n",
            " [ 6630.  5636.  6673.]\n",
            " [ 5887.  6630.  5636.]\n",
            " [ 6322.  5887.  6630.]\n",
            " [ 6520.  6322.  5887.]\n",
            " [ 6678.  6520.  6322.]\n",
            " [ 5082.  6678.  6520.]\n",
            " [ 5216.  5082.  6678.]\n",
            " [ 5893.  5216.  5082.]\n",
            " [ 5894.  5893.  5216.]\n",
            " [ 6799.  5894.  5893.]\n",
            " [ 6667.  6799.  5894.]\n",
            " [ 6374.  6667.  6799.]\n",
            " [ 6840.  6374.  6667.]\n",
            " [ 5575.  6840.  6374.]\n",
            " [ 6545.  5575.  6840.]\n",
            " [ 6789.  6545.  5575.]\n",
            " [ 7180.  6789.  6545.]\n",
            " [ 5117.  7180.  6789.]\n",
            " [ 5442.  5117.  7180.]\n",
            " [ 6337.  5442.  5117.]\n",
            " [ 6525.  6337.  5442.]\n",
            " [ 7216.  6525.  6337.]\n",
            " [ 6761.  7216.  6525.]\n",
            " [ 6958.  6761.  7216.]\n",
            " [ 7070.  6958.  6761.]\n",
            " [ 6148.  7070.  6958.]\n",
            " [ 6924.  6148.  7070.]\n",
            " [ 6716.  6924.  6148.]\n",
            " [ 7975.  6716.  6924.]\n",
            " [ 5326.  7975.  6716.]\n",
            " [ 5609.  5326.  7975.]\n",
            " [ 6414.  5609.  5326.]\n",
            " [ 6741.  6414.  5609.]\n",
            " [ 7144.  6741.  6414.]\n",
            " [ 7133.  7144.  6741.]\n",
            " [ 7568.  7133.  7144.]\n",
            " [ 7266.  7568.  7133.]\n",
            " [ 6634.  7266.  7568.]\n",
            " [ 7626.  6634.  7266.]\n",
            " [ 6843.  7626.  6634.]\n",
            " [ 8540.  6843.  7626.]\n",
            " [ 5629.  8540.  6843.]\n",
            " [ 5898.  5629.  8540.]\n",
            " [ 7045.  5898.  5629.]\n",
            " [ 7094.  7045.  5898.]\n",
            " [ 7333.  7094.  7045.]\n",
            " [ 7918.  7333.  7094.]\n",
            " [ 7289.  7918.  7333.]\n",
            " [ 7396.  7289.  7918.]\n",
            " [ 7259.  7396.  7289.]\n",
            " [ 7268.  7259.  7396.]\n",
            " [ 7731.  7268.  7259.]\n",
            " [ 9058.  7731.  7268.]\n",
            " [ 5557.  9058.  7731.]\n",
            " [ 6237.  5557.  9058.]\n",
            " [ 7723.  6237.  5557.]\n",
            " [ 7262.  7723.  6237.]\n",
            " [ 8241.  7262.  7723.]\n",
            " [ 8757.  8241.  7262.]\n",
            " [ 7352.  8757.  8241.]\n",
            " [ 8496.  7352.  8757.]\n",
            " [ 7741.  8496.  7352.]\n",
            " [ 7710.  7741.  8496.]\n",
            " [ 8247.  7710.  7741.]\n",
            " [ 8902.  8247.  7710.]\n",
            " [ 6066.  8902.  8247.]\n",
            " [ 6590.  6066.  8902.]\n",
            " [ 7923.  6590.  6066.]\n",
            " [ 7335.  7923.  6590.]\n",
            " [ 8843.  7335.  7923.]\n",
            " [ 9327.  8843.  7335.]\n",
            " [ 7792.  9327.  8843.]\n",
            " [ 9156.  7792.  9327.]\n",
            " [ 8037.  9156.  7792.]\n",
            " [ 8640.  8037.  9156.]\n",
            " [ 9128.  8640.  8037.]\n",
            " [ 9545.  9128.  8640.]\n",
            " [ 6627.  9545.  9128.]\n",
            " [ 6743.  6627.  9545.]\n",
            " [ 8195.  6743.  6627.]\n",
            " [ 7828.  8195.  6743.]\n",
            " [ 9570.  7828.  8195.]\n",
            " [ 9484.  9570.  7828.]\n",
            " [ 8608.  9484.  9570.]\n",
            " [ 9543.  8608.  9484.]\n",
            " [ 8123.  9543.  8608.]\n",
            " [ 9649.  8123.  9543.]\n",
            " [ 9390.  9649.  8123.]\n",
            " [10065.  9390.  9649.]\n",
            " [ 7093. 10065.  9390.]\n",
            " [ 7483.  7093. 10065.]\n",
            " [ 8365.  7483.  7093.]\n",
            " [ 8895.  8365.  7483.]\n",
            " [ 9794.  8895.  8365.]\n",
            " [ 9977.  9794.  8895.]\n",
            " [ 9553.  9977.  9794.]\n",
            " [ 9375.  9553.  9977.]\n",
            " [ 9225.  9375.  9553.]\n",
            " [ 9948.  9225.  9375.]\n",
            " [ 8758.  9948.  9225.]\n",
            " [10839.  8758.  9948.]\n",
            " [ 7266. 10839.  8758.]\n",
            " [ 7578.  7266. 10839.]\n",
            " [ 8688.  7578.  7266.]\n",
            " [ 9162.  8688.  7578.]\n",
            " [ 9369.  9162.  8688.]\n",
            " [10167.  9369.  9162.]\n",
            " [ 9507. 10167.  9369.]\n",
            " [ 8923.  9507. 10167.]\n",
            " [ 9272.  8923.  9507.]\n",
            " [ 9075.  9272.  8923.]\n",
            " [ 8949.  9075.  9272.]\n",
            " [10843.  8949.  9075.]\n",
            " [ 6558. 10843.  8949.]\n",
            " [ 7481.  6558. 10843.]\n",
            " [ 9475.  7481.  6558.]\n",
            " [ 9424.  9475.  7481.]\n",
            " [ 9351.  9424.  9475.]\n",
            " [10552.  9351.  9424.]\n",
            " [ 9077. 10552.  9351.]\n",
            " [ 9273.  9077. 10552.]\n",
            " [ 9420.  9273.  9077.]\n",
            " [ 9413.  9420.  9273.]\n",
            " [ 9866.  9413.  9420.]\n",
            " [11455.  9866.  9413.]\n",
            " [ 6901. 11455.  9866.]\n",
            " [ 8014.  6901. 11455.]\n",
            " [ 9832.  8014.  6901.]\n",
            " [ 9281.  9832.  8014.]\n",
            " [ 9967.  9281.  9832.]\n",
            " [11344.  9967.  9281.]\n",
            " [ 9106. 11344.  9967.]\n",
            " [10469.  9106. 11344.]\n",
            " [10085. 10469.  9106.]\n",
            " [ 9612. 10085. 10469.]\n",
            " [10328.  9612. 10085.]\n",
            " [11483. 10328.  9612.]\n",
            " [ 7486. 11483. 10328.]\n",
            " [ 8641.  7486. 11483.]\n",
            " [ 9709.  8641.  7486.]\n",
            " [ 9423.  9709.  8641.]\n",
            " [11342.  9423.  9709.]\n",
            " [11274. 11342.  9423.]\n",
            " [ 9845. 11274. 11342.]\n",
            " [11163.  9845. 11274.]\n",
            " [ 9532. 11163.  9845.]\n",
            " [10754.  9532. 11163.]\n",
            " [10953. 10754.  9532.]\n",
            " [11922. 10953. 10754.]\n",
            " [ 8395. 11922. 10953.]\n",
            " [ 8888.  8395. 11922.]\n",
            " [10110.  8888.  8395.]\n",
            " [10493. 10110.  8888.]\n",
            " [12218. 10493. 10110.]\n",
            " [11385. 12218. 10493.]\n",
            " [11186. 11385. 12218.]\n",
            " [11462. 11186. 11385.]\n",
            " [10494. 11462. 11186.]\n",
            " [11540. 10494. 11462.]\n",
            " [11138. 11540. 10494.]\n",
            " [12709. 11138. 11540.]\n",
            " [ 8557. 12709. 11138.]\n",
            " [ 9059.  8557. 12709.]\n",
            " [10055.  9059.  8557.]\n",
            " [10977. 10055.  9059.]\n",
            " [11792. 10977. 10055.]\n",
            " [11904. 11792. 10977.]\n",
            " [10965. 11904. 11792.]\n",
            " [10981. 10965. 11904.]\n",
            " [10828. 10981. 10965.]\n",
            " [11817. 10828. 10981.]\n",
            " [10470. 11817. 10828.]\n",
            " [13310. 10470. 11817.]\n",
            " [ 8400. 13310. 10470.]\n",
            " [ 9062.  8400. 13310.]\n",
            " [10722.  9062.  8400.]\n",
            " [11107. 10722.  9062.]\n",
            " [11508. 11107. 10722.]\n",
            " [12904. 11508. 11107.]\n",
            " [11869. 12904. 11508.]\n",
            " [11224. 11869. 12904.]\n",
            " [12022. 11224. 11869.]\n",
            " [11983. 12022. 11224.]\n",
            " [11506. 11983. 12022.]\n",
            " [14183. 11506. 11983.]\n",
            " [ 8648. 14183. 11506.]\n",
            " [10321.  8648. 14183.]\n",
            " [12107. 10321.  8648.]\n",
            " [11420. 12107. 10321.]\n",
            " [12238. 11420. 12107.]\n",
            " [13681. 12238. 11420.]\n",
            " [10950. 13681. 12238.]\n",
            " [12700. 10950. 13681.]\n",
            " [12272. 12700. 10950.]\n",
            " [11905. 12272. 12700.]\n",
            " [13016. 11905. 12272.]\n",
            " [14421. 13016. 11905.]\n",
            " [ 9043. 14421. 13016.]\n",
            " [10452.  9043. 14421.]\n",
            " [12481. 10452.  9043.]\n",
            " [11491. 12481. 10452.]\n",
            " [13545. 11491. 12481.]\n",
            " [14730. 13545. 11491.]\n",
            " [11416. 14730. 13545.]\n",
            " [13402. 11416. 14730.]\n",
            " [11907. 13402. 11416.]\n",
            " [12711. 11907. 13402.]\n",
            " [13261. 12711. 11907.]\n",
            " [14265. 13261. 12711.]\n",
            " [ 9564. 14265. 13261.]\n",
            " [10415.  9564. 14265.]\n",
            " [12683. 10415.  9564.]\n",
            " [11919. 12683. 10415.]\n",
            " [14138. 11919. 12683.]\n",
            " [14583. 14138. 11919.]\n",
            " [12640. 14583. 14138.]\n",
            " [14257. 12640. 14583.]\n",
            " [12396. 14257. 12640.]\n",
            " [13914. 12396. 14257.]\n",
            " [14174. 13914. 12396.]\n",
            " [15504. 14174. 13914.]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B99Pp3kHwdYS"
      },
      "source": [
        "X_train,X_test,y_train,y_test=final_x[:-30],final_x[-30:],y[:-30],y[-30:]"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "syZCIXs3p8sW",
        "outputId": "cbe93bdc-3798-4adf-af9c-56dac2a4ae19"
      },
      "source": [
        "model.fit(X_train,y_train)\n",
        "lin_model.fit(X_train,y_train)"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 483
        },
        "id": "FKtiB1vpwivF",
        "outputId": "7e7a0f72-98ae-4030-9869-d700eaf3a6e6"
      },
      "source": [
        "pred=model.predict(X_test)\n",
        "import matplotlib.pyplot as plt\n",
        "plt.rcParams[\"figure.figsize\"] = (12,8)\n",
        "plt.plot(pred,label='Random_Forest_Predictions')\n",
        "plt.plot(y_test,label='Actual Sales')\n",
        "plt.legend(loc=\"upper left\")\n",
        "plt.show()"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "zwtbfMXSq9TU",
        "outputId": "200b2b09-5f3e-4c9c-e687-5ac9ac9af0c0"
      },
      "source": [
        "lin_pred=lin_model.predict(X_test)\n",
        "import matplotlib.pyplot as plt\n",
        "plt.rcParams[\"figure.figsize\"] = (11,6)\n",
        "plt.plot(lin_pred,label='Linear_Regression_Predictions')\n",
        "plt.plot(y_test,label='Actual Sales')\n",
        "plt.legend(loc=\"upper left\")\n",
        "plt.show()"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 792x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-K82kVphnFxT"
      },
      "source": [
        "from sklearn.metrics import mean_squared_error\n",
        "from math import sqrt\n",
        "rmse_rf=sqrt(mean_squared_error(pred,y_test))\n",
        "rmse_lr=sqrt(mean_squared_error(lin_pred,y_test))"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TsrxmqpSwqi6",
        "outputId": "8568673b-4343-40ae-fc74-36af18d37d5e"
      },
      "source": [
        "print('Mean Squared Error for Random Forest Model is:',rmse_rf)\n",
        "print('Mean Squared Error for Linear Regression Model is:',rmse_lr)"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean Squared Error for Random Forest Model is: 1913.7762399350665\n",
            "Mean Squared Error for Linear Regression Model is: 1791.4965232759832\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cWvymQjOwtpI"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}