11: Time_Series_using_FBProphet_Trend_Non_Stationary_Amazon_Revenue_Data.ipynb

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      "name": "Time_Series_using_FBProphet_Trend_Non-Stationary_Amazon_Revenue_Data.ipynb",
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      "include_colab_link": true
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      "name": "python3",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/gulabpatel/TimeSeries/blob/main/Time_Series_using_FBProphet_Trend_Non_Stationary_Amazon_Revenue_Data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ze0vbcQHWq-X"
      },
      "source": [
        "Link to video explaining the code - https://www.youtube.com/watch?v=iuwcHhGNb8A"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NUe7BW37S6VA",
        "colab": {
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        "outputId": "f22ac0c9-a27e-4f00-9155-52fe7d830408"
      },
      "source": [
        "!pip install fbprophet"
      ],
      "execution_count": 1,
      "outputs": [
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            "Requirement already satisfied: fbprophet in /usr/local/lib/python3.6/dist-packages (0.7.1)\n",
            "Requirement already satisfied: Cython>=0.22 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (0.29.21)\n",
            "Requirement already satisfied: cmdstanpy==0.9.5 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (0.9.5)\n",
            "Requirement already satisfied: pystan>=2.14 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (2.19.1.1)\n",
            "Requirement already satisfied: numpy>=1.15.4 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (1.18.5)\n",
            "Requirement already satisfied: pandas>=1.0.4 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (1.1.4)\n",
            "Requirement already satisfied: matplotlib>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (3.2.2)\n",
            "Requirement already satisfied: LunarCalendar>=0.0.9 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (0.0.9)\n",
            "Requirement already satisfied: convertdate>=2.1.2 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (2.3.0)\n",
            "Requirement already satisfied: holidays>=0.10.2 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (0.10.3)\n",
            "Requirement already satisfied: setuptools-git>=1.2 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.0 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (2.8.1)\n",
            "Requirement already satisfied: tqdm>=4.36.1 in /usr/local/lib/python3.6/dist-packages (from fbprophet) (4.41.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=1.0.4->fbprophet) (2018.9)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.0.0->fbprophet) (2.4.7)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.0.0->fbprophet) (0.10.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.0.0->fbprophet) (1.3.1)\n",
            "Requirement already satisfied: ephem>=3.7.5.3 in /usr/local/lib/python3.6/dist-packages (from LunarCalendar>=0.0.9->fbprophet) (3.7.7.1)\n",
            "Requirement already satisfied: pymeeus<=1,>=0.3.6 in /usr/local/lib/python3.6/dist-packages (from convertdate>=2.1.2->fbprophet) (0.3.7)\n",
            "Requirement already satisfied: korean-lunar-calendar in /usr/local/lib/python3.6/dist-packages (from holidays>=0.10.2->fbprophet) (0.2.1)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from holidays>=0.10.2->fbprophet) (1.15.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CY5G7SE9PLEB"
      },
      "source": [
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import os\n",
        "from datetime import datetime\n",
        "import pandas as pd\n",
        "import plotly.express as px\n",
        "\n",
        "mpl.rcParams['figure.figsize'] = (10, 8)\n",
        "mpl.rcParams['axes.grid'] = False\n"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PJaoc_EcR1pB"
      },
      "source": [
        "df = pd.read_csv('https://raw.githubusercontent.com/srivatsan88/YouTubeLI/master/dataset/amazon_revenue_profit.csv')"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "2_g6laZM8yUz",
        "outputId": "6024d894-6951-4327-b815-19a40e148640"
      },
      "source": [
        "df.sample(10)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>Quarter</th>\n",
              "      <th>Revenue</th>\n",
              "      <th>Net Income</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>3/31/2015</td>\n",
              "      <td>22717</td>\n",
              "      <td>-57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>12/31/2018</td>\n",
              "      <td>72383</td>\n",
              "      <td>3027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>12/31/2016</td>\n",
              "      <td>43741</td>\n",
              "      <td>749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>9/30/2006</td>\n",
              "      <td>2307</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>3/31/2005</td>\n",
              "      <td>1902</td>\n",
              "      <td>78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>6/30/2016</td>\n",
              "      <td>30404</td>\n",
              "      <td>857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>12/31/2005</td>\n",
              "      <td>2977</td>\n",
              "      <td>199</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>3/31/2006</td>\n",
              "      <td>2279</td>\n",
              "      <td>51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>6/30/2007</td>\n",
              "      <td>2886</td>\n",
              "      <td>78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>3/31/2017</td>\n",
              "      <td>35714</td>\n",
              "      <td>724</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Quarter  Revenue  Net Income\n",
              "20   3/31/2015    22717         -57\n",
              "5   12/31/2018    72383        3027\n",
              "13  12/31/2016    43741         749\n",
              "54   9/30/2006     2307          19\n",
              "60   3/31/2005     1902          78\n",
              "15   6/30/2016    30404         857\n",
              "57  12/31/2005     2977         199\n",
              "56   3/31/2006     2279          51\n",
              "51   6/30/2007     2886          78\n",
              "12   3/31/2017    35714         724"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LIQPcZqF83ua",
        "outputId": "99b02fb4-05b0-40ba-ad88-c7a8da57113e"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 61 entries, 0 to 60\n",
            "Data columns (total 3 columns):\n",
            " #   Column      Non-Null Count  Dtype \n",
            "---  ------      --------------  ----- \n",
            " 0   Quarter     61 non-null     object\n",
            " 1   Revenue     61 non-null     int64 \n",
            " 2   Net Income  61 non-null     int64 \n",
            "dtypes: int64(2), object(1)\n",
            "memory usage: 1.6+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bEwsXpeG88sX"
      },
      "source": [
        "#Convert quarter into datetime"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vjjJKsOR5GtF"
      },
      "source": [
        "df['Quarter']=pd.to_datetime(df['Quarter'])"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gQjU-JsX58EB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d5afa371-caec-45aa-9422-34f32cb6f13d"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 61 entries, 0 to 60\n",
            "Data columns (total 3 columns):\n",
            " #   Column      Non-Null Count  Dtype         \n",
            "---  ------      --------------  -----         \n",
            " 0   Quarter     61 non-null     datetime64[ns]\n",
            " 1   Revenue     61 non-null     int64         \n",
            " 2   Net Income  61 non-null     int64         \n",
            "dtypes: datetime64[ns](1), int64(2)\n",
            "memory usage: 1.6 KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1ALsQm_eoVsh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "fffacb24-030a-4dea-f3af-d9b41e942d33"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>Quarter</th>\n",
              "      <th>Revenue</th>\n",
              "      <th>Net Income</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-03-31</td>\n",
              "      <td>75452</td>\n",
              "      <td>2535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-12-31</td>\n",
              "      <td>87437</td>\n",
              "      <td>3268</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-09-30</td>\n",
              "      <td>69981</td>\n",
              "      <td>2134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-06-30</td>\n",
              "      <td>63404</td>\n",
              "      <td>2625</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-03-31</td>\n",
              "      <td>59700</td>\n",
              "      <td>3561</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Quarter  Revenue  Net Income\n",
              "0 2020-03-31    75452        2535\n",
              "1 2019-12-31    87437        3268\n",
              "2 2019-09-30    69981        2134\n",
              "3 2019-06-30    63404        2625\n",
              "4 2019-03-31    59700        3561"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hiAzV_Uv9I7n",
        "outputId": "af603d34-2852-4a9a-e9fe-b739708db3fd"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 61 entries, 0 to 60\n",
            "Data columns (total 3 columns):\n",
            " #   Column      Non-Null Count  Dtype         \n",
            "---  ------      --------------  -----         \n",
            " 0   Quarter     61 non-null     datetime64[ns]\n",
            " 1   Revenue     61 non-null     int64         \n",
            " 2   Net Income  61 non-null     int64         \n",
            "dtypes: datetime64[ns](1), int64(2)\n",
            "memory usage: 1.6 KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Lkozon5gA6GI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "2735926f-7877-4d9f-dc49-c2697739ae20"
      },
      "source": [
        "fig = px.line(df, x='Quarter', y='Revenue', title='Amazon Profits')\n",
        "\n",
        "fig.update_xaxes(\n",
        "    rangeslider_visible=True,\n",
        "    rangeselector=dict(\n",
        "        buttons=list([\n",
        "            dict(count=1, label=\"1y\", step=\"year\", stepmode=\"backward\"),\n",
        "            dict(count=2, label=\"3y\", step=\"year\", stepmode=\"backward\"),\n",
        "            dict(count=3, label=\"5y\", step=\"year\", stepmode=\"backward\"),\n",
        "            dict(step=\"all\")\n",
        "        ])\n",
        "    )\n",
        ")\n",
        "fig.show()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
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[0.0, 1.0], \"title\": {\"text\": \"Revenue\"}}},\n",
              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('05836d9e-bfa7-4916-98cc-df5791b69841');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
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              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
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              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
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              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0jt3yFXudhrE"
      },
      "source": [
        "from fbprophet import Prophet"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LT5FPlA3dhot"
      },
      "source": [
        "amazon_df=df[['Quarter','Revenue']].rename({'Quarter':'ds','Revenue':'y'}, axis='columns')"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zpqAZy3Bdhmv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "c3c3f1e1-683b-44ee-c406-7b64fb61cbd4"
      },
      "source": [
        "amazon_df"
      ],
      "execution_count": 13,
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ds</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-03-31</td>\n",
              "      <td>75452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-12-31</td>\n",
              "      <td>87437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-09-30</td>\n",
              "      <td>69981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-06-30</td>\n",
              "      <td>63404</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-03-31</td>\n",
              "      <td>59700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>2006-03-31</td>\n",
              "      <td>2279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>2005-12-31</td>\n",
              "      <td>2977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>2005-09-30</td>\n",
              "      <td>1858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>2005-06-30</td>\n",
              "      <td>1753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>2005-03-31</td>\n",
              "      <td>1902</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>61 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           ds      y\n",
              "0  2020-03-31  75452\n",
              "1  2019-12-31  87437\n",
              "2  2019-09-30  69981\n",
              "3  2019-06-30  63404\n",
              "4  2019-03-31  59700\n",
              "..        ...    ...\n",
              "56 2006-03-31   2279\n",
              "57 2005-12-31   2977\n",
              "58 2005-09-30   1858\n",
              "59 2005-06-30   1753\n",
              "60 2005-03-31   1902\n",
              "\n",
              "[61 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qkj44Up8dhkA"
      },
      "source": [
        "df_train=amazon_df[(amazon_df['ds'] >= '2005-03-31') & (amazon_df['ds'] <= '2019-03-31')]\n",
        "df_test=amazon_df[(amazon_df['ds'] > '2019-03-31')]"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4mCsdGq2dhf-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "da9e8ed6-ff98-4f7e-bef5-1d8112beac67"
      },
      "source": [
        "df_train.shape"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(57, 2)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ei0NwfB9dhd6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2d501226-b92f-46d5-b26c-05f74d4ccae0"
      },
      "source": [
        "df_test.shape"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4, 2)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ckWH1s5MdhcD"
      },
      "source": [
        "m = Prophet(interval_width=0.95)"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-NbyPxRldhXl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "feff82d8-99bb-4164-f4f9-89747c517d38"
      },
      "source": [
        "m.fit(df_train)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO:numexpr.utils:NumExpr defaulting to 2 threads.\n",
            "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
            "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fbprophet.forecaster.Prophet at 0x7f2813b50da0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iw4iZd6Txyfx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "4dea260f-07a3-4fee-a53c-0e221e3ea0ac"
      },
      "source": [
        "future = m.make_future_dataframe(periods=4, freq='Q')\n",
        "future.tail()"
      ],
      "execution_count": 19,
      "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>ds</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>2019-03-31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>2019-06-30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>2019-09-30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>2019-12-31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>2020-03-31</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           ds\n",
              "56 2019-03-31\n",
              "57 2019-06-30\n",
              "58 2019-09-30\n",
              "59 2019-12-31\n",
              "60 2020-03-31"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wpNP1pEAxybY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "68e079e8-f99d-40c2-eaa4-d71405050dec"
      },
      "source": [
        "forecast = m.predict(future)\n",
        "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>ds</th>\n",
              "      <th>yhat</th>\n",
              "      <th>yhat_lower</th>\n",
              "      <th>yhat_upper</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>2019-03-31</td>\n",
              "      <td>61089.496722</td>\n",
              "      <td>57296.724726</td>\n",
              "      <td>64997.536621</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>2019-06-30</td>\n",
              "      <td>63195.117248</td>\n",
              "      <td>59024.658111</td>\n",
              "      <td>67340.101851</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>2019-09-30</td>\n",
              "      <td>66153.769201</td>\n",
              "      <td>62113.936814</td>\n",
              "      <td>70108.388246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>2019-12-31</td>\n",
              "      <td>74249.538212</td>\n",
              "      <td>70641.492527</td>\n",
              "      <td>78286.250775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>2020-03-31</td>\n",
              "      <td>70663.367647</td>\n",
              "      <td>66588.625123</td>\n",
              "      <td>75221.260187</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           ds          yhat    yhat_lower    yhat_upper\n",
              "56 2019-03-31  61089.496722  57296.724726  64997.536621\n",
              "57 2019-06-30  63195.117248  59024.658111  67340.101851\n",
              "58 2019-09-30  66153.769201  62113.936814  70108.388246\n",
              "59 2019-12-31  74249.538212  70641.492527  78286.250775\n",
              "60 2020-03-31  70663.367647  66588.625123  75221.260187"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "kykkVPua-5yT",
        "outputId": "557222c0-2f3e-4b75-dd33-4d851efb68a8"
      },
      "source": [
        "pd.concat([amazon_df.set_index('ds')['y'],forecast.set_index('ds')['yhat']],axis=1)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>y</th>\n",
              "      <th>yhat</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ds</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2005-03-31</th>\n",
              "      <td>1902</td>\n",
              "      <td>-638.489958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-06-30</th>\n",
              "      <td>1753</td>\n",
              "      <td>-1055.257099</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-09-30</th>\n",
              "      <td>1858</td>\n",
              "      <td>-223.253205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-12-31</th>\n",
              "      <td>2977</td>\n",
              "      <td>6646.043035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-03-31</th>\n",
              "      <td>2279</td>\n",
              "      <td>912.670901</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-03-31</th>\n",
              "      <td>59700</td>\n",
              "      <td>61089.496722</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-30</th>\n",
              "      <td>63404</td>\n",
              "      <td>63195.117248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-09-30</th>\n",
              "      <td>69981</td>\n",
              "      <td>66153.769201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-31</th>\n",
              "      <td>87437</td>\n",
              "      <td>74249.538212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-31</th>\n",
              "      <td>75452</td>\n",
              "      <td>70663.367647</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>61 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                y          yhat\n",
              "ds                             \n",
              "2005-03-31   1902   -638.489958\n",
              "2005-06-30   1753  -1055.257099\n",
              "2005-09-30   1858   -223.253205\n",
              "2005-12-31   2977   6646.043035\n",
              "2006-03-31   2279    912.670901\n",
              "...           ...           ...\n",
              "2019-03-31  59700  61089.496722\n",
              "2019-06-30  63404  63195.117248\n",
              "2019-09-30  69981  66153.769201\n",
              "2019-12-31  87437  74249.538212\n",
              "2020-03-31  75452  70663.367647\n",
              "\n",
              "[61 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zn1lJ_xZq4N_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "outputId": "deb67dc4-dea8-4e28-f806-2ca304b2134f"
      },
      "source": [
        "pd.concat([amazon_df.set_index('ds')['y'],forecast.set_index('ds')['yhat']],axis=1).plot()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2806999198>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SUhl1klTxyYo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "outputId": "2c2164a7-0b9d-4529-b66d-cde1bca95862"
      },
      "source": [
        "fig1 = m.plot(forecast)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MRY3ZMDKxyVX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "outputId": "7ca932b0-5928-4f7b-a2e3-9c0655b86536"
      },
      "source": [
        "fig2 = m.plot_components(forecast)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EvTLuLm_v1vD"
      },
      "source": [
        "holiday_sale = pd.DataFrame({\n",
        "  'holiday': 'dec_jan_sale',\n",
        "  'ds': pd.to_datetime(['\t2019-12-31', '2018-12-31', '2017-12-31', '2016-12-31',\n",
        "                        '2015-12-31', '2014-12-31','2013-12-31','2012-12-31','2011-12-31','2010-12-31','2009-12-31','2008-12-31','2007-12-31',\n",
        "                        '2006-12-31','2005-12-31']),\n",
        "  'lower_window': 0,\n",
        "  'upper_window': 1,\n",
        "})"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "U1yV8NAK_tcS",
        "outputId": "feb87d47-8b24-4582-cb51-8b07280945ac"
      },
      "source": [
        "holiday_sale"
      ],
      "execution_count": 26,
      "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>holiday</th>\n",
              "      <th>ds</th>\n",
              "      <th>lower_window</th>\n",
              "      <th>upper_window</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2019-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2018-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2017-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2016-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2015-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2014-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2013-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2012-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2011-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2010-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2009-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2008-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2007-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2006-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>dec_jan_sale</td>\n",
              "      <td>2005-12-31</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         holiday         ds  lower_window  upper_window\n",
              "0   dec_jan_sale 2019-12-31             0             1\n",
              "1   dec_jan_sale 2018-12-31             0             1\n",
              "2   dec_jan_sale 2017-12-31             0             1\n",
              "3   dec_jan_sale 2016-12-31             0             1\n",
              "4   dec_jan_sale 2015-12-31             0             1\n",
              "5   dec_jan_sale 2014-12-31             0             1\n",
              "6   dec_jan_sale 2013-12-31             0             1\n",
              "7   dec_jan_sale 2012-12-31             0             1\n",
              "8   dec_jan_sale 2011-12-31             0             1\n",
              "9   dec_jan_sale 2010-12-31             0             1\n",
              "10  dec_jan_sale 2009-12-31             0             1\n",
              "11  dec_jan_sale 2008-12-31             0             1\n",
              "12  dec_jan_sale 2007-12-31             0             1\n",
              "13  dec_jan_sale 2006-12-31             0             1\n",
              "14  dec_jan_sale 2005-12-31             0             1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yujF-6U2A0V8"
      },
      "source": [
        "#There is multiplicative seasonality in the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w5fgyKtyxk_E"
      },
      "source": [
        "m2 = Prophet(interval_width=0.95, seasonality_mode='multiplicative', holidays=holiday_sale)"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HePvvhy5xk7o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "581e8f7a-74ca-48eb-f5cb-dfd03fda3dec"
      },
      "source": [
        "m2.fit(df_train)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
            "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fbprophet.forecaster.Prophet at 0x7f280665c4a8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aydKo98Vxkxp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "2e12fbdd-98ee-4486-f2a3-db03dcb4b9f1"
      },
      "source": [
        "forecast = m2.predict(future)\n",
        "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>ds</th>\n",
              "      <th>yhat</th>\n",
              "      <th>yhat_lower</th>\n",
              "      <th>yhat_upper</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>2019-03-31</td>\n",
              "      <td>60098.589527</td>\n",
              "      <td>58245.140095</td>\n",
              "      <td>61868.903566</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>2019-06-30</td>\n",
              "      <td>62627.734827</td>\n",
              "      <td>60797.709609</td>\n",
              "      <td>64371.223131</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>2019-09-30</td>\n",
              "      <td>67792.982748</td>\n",
              "      <td>65909.554004</td>\n",
              "      <td>69535.789268</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>2019-12-31</td>\n",
              "      <td>89317.926197</td>\n",
              "      <td>87451.947327</td>\n",
              "      <td>91280.568175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>2020-03-31</td>\n",
              "      <td>66836.358707</td>\n",
              "      <td>64869.051622</td>\n",
              "      <td>68834.258923</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           ds          yhat    yhat_lower    yhat_upper\n",
              "56 2019-03-31  60098.589527  58245.140095  61868.903566\n",
              "57 2019-06-30  62627.734827  60797.709609  64371.223131\n",
              "58 2019-09-30  67792.982748  65909.554004  69535.789268\n",
              "59 2019-12-31  89317.926197  87451.947327  91280.568175\n",
              "60 2020-03-31  66836.358707  64869.051622  68834.258923"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "t6ErXkjcBKz7",
        "outputId": "4df264e0-98ef-432f-8682-ce0e1043eb84"
      },
      "source": [
        "pd.concat([amazon_df.set_index('ds')['y'],forecast.set_index('ds')['yhat']],axis=1)"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>y</th>\n",
              "      <th>yhat</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ds</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2005-03-31</th>\n",
              "      <td>1902</td>\n",
              "      <td>1731.170299</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-06-30</th>\n",
              "      <td>1753</td>\n",
              "      <td>1806.507224</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-09-30</th>\n",
              "      <td>1858</td>\n",
              "      <td>1995.894275</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-12-31</th>\n",
              "      <td>2977</td>\n",
              "      <td>2734.398874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-03-31</th>\n",
              "      <td>2279</td>\n",
              "      <td>2268.809330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-03-31</th>\n",
              "      <td>59700</td>\n",
              "      <td>60098.589527</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-30</th>\n",
              "      <td>63404</td>\n",
              "      <td>62627.734827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-09-30</th>\n",
              "      <td>69981</td>\n",
              "      <td>67792.982748</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-31</th>\n",
              "      <td>87437</td>\n",
              "      <td>89317.926197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-31</th>\n",
              "      <td>75452</td>\n",
              "      <td>66836.358707</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>61 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                y          yhat\n",
              "ds                             \n",
              "2005-03-31   1902   1731.170299\n",
              "2005-06-30   1753   1806.507224\n",
              "2005-09-30   1858   1995.894275\n",
              "2005-12-31   2977   2734.398874\n",
              "2006-03-31   2279   2268.809330\n",
              "...           ...           ...\n",
              "2019-03-31  59700  60098.589527\n",
              "2019-06-30  63404  62627.734827\n",
              "2019-09-30  69981  67792.982748\n",
              "2019-12-31  87437  89317.926197\n",
              "2020-03-31  75452  66836.358707\n",
              "\n",
              "[61 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rL1nnoFB_XhZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "outputId": "46eb9477-b08d-44d1-83c4-e7ba13150626"
      },
      "source": [
        "pd.concat([amazon_df.set_index('ds')['y'],forecast.set_index('ds')['yhat']],axis=1).plot()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2806664dd8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mTdTFNxW_XdU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "outputId": "57ad3ee9-0b97-46f8-a8b4-4ca681532171"
      },
      "source": [
        "fig1 = m2.plot(forecast)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Pldb3yp_XLO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 657
        },
        "outputId": "ffada047-ef1e-44c5-c655-2b0aa190a186"
      },
      "source": [
        "fig2 = m2.plot_components(forecast)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x648 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}