time_series_analysis_and_forecasting.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
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        "<a href=\"https://colab.research.google.com/github/Kavya-812/ML-models/blob/main/time_series_analysis_and_forecasting.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Z4ZVgqfROGz0"
      },
      "outputs": [],
      "source": [
        "import pandas as pd "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "demo_date = \"03/10/2022\"   \n",
        "print(demo_date)\n",
        "print(type(demo_date))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oTS_kS3PO0YV",
        "outputId": "142f6d82-afc7-4e67-d7df-64379242996d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "03/10/2022\n",
            "<class 'str'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "op = pd.to_datetime(demo_date)\n",
        "op"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zH5wnq6hPCMF",
        "outputId": "6a8df7ce-b64e-45b5-8976-a998ea8fa7e1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2022-03-10 00:00:00')"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(op)"
      ],
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        "id": "eE8c2bJkPpa0",
        "outputId": "1dd79a80-b941-4537-84ed-c1c07e0696d4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas._libs.tslibs.timestamps.Timestamp"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "demo_date2 = \"03/10/2022 20:05:59\"   \n",
        "op2 = pd.to_datetime(demo_date2)\n",
        "op2\n"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "qucq-WIiPsIw",
        "outputId": "a7e5e6f9-5253-4ee4-ff97-a93cacda250c"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2022-03-10 20:05:59')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "demo_date2 = \"03-10-2022 20/05/59\"   \n",
        "op2 = pd.to_datetime(demo_date2)\n",
        "op2\n"
      ],
      "metadata": {
        "id": "RwxG1L9BQhpw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "demo_date3 = '03|10'2022; 20$05_59'   \n",
        "op3 = pd.to_datetime(demo_date3)\n",
        "op3"
      ],
      "metadata": {
        "id": "6CMk-aCyQqKq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# FORMAT CODES IN DATETIME/TIMESTAMP LIBRARY OF PANDAS\n",
        "# %Y - year\n",
        "# %m - month \n",
        "# %d - date\n",
        "# %H - hours\n",
        "# %M - minutes\n",
        "# %S - seconds "
      ],
      "metadata": {
        "id": "spRvpJ-6Q4DM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "demo_date2 = \"10-03>2022 20/05=59\"   \n",
        "op2 = pd.to_datetime(demo_date2,format =\"%d-%m>%Y %H/%M=%S\") \n",
        "op2"
      ],
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        "id": "lWFOgdSrRZxE",
        "outputId": "3ac9d83d-eaaa-4c19-c01d-246546449fa3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2022-03-10 20:05:59')"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 03|10'2022; 20$05_59\n",
        "demo_date3 = \"03|10'2022; 20$05_59\"   \n",
        "op3 = pd.to_datetime(demo_date3,format = \"%m|%d'%Y; %H$%M_%S\")\n",
        "op3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h5k5j2DjR8MI",
        "outputId": "f5894325-4494-48ea-9b57-5a7b3b5683f4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2022-03-10 20:05:59')"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import datetime \n",
        "print(datetime.now())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vwbs0eILTO5l",
        "outputId": "6a31fe1f-1a4a-42dd-f62c-8acd1b0d5c0c"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2022-03-10 14:59:31.597811\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd "
      ],
      "metadata": {
        "id": "6Ug_NViAV09m"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_html(\"/content/DailyWiseMarketArrivals.html\")\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7_vr_W6RYTyv",
        "outputId": "129d230f-b88c-4a04-b2a8-1bc8233292a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[                                      0\n",
              " 0  DATE WISE MARKET ARRIVALS AND PRICES,\n",
              "           0                                                  1        2  \\\n",
              " 0    Crop :              Select  Garlic  Onion  Potato  Tomato   Year :   \n",
              " 1  Market :  All  ABOHAR(PB)  AGRA(UP)  AHMEDABAD(GUJ)  AHM...  Month :   \n",
              " 2       NaN                                                NaN      NaN   \n",
              " \n",
              "                                                    3  \n",
              " 0  All  2022  2021  2020  2019  2018  2017  2016 ...  \n",
              " 1  All  January  February  March  April  May  Jun...  \n",
              " 2                                                NaN  ,\n",
              "                                                  0\n",
              " 0  DATE WISE MARKET ARRIVALS AND PRICES FOR POTATO,\n",
              "              Date  Market  Arrival(q) Price Minimum (Rs/q)  \\\n",
              " 0     01/Jan/2005  MUMBAI       13200                  250   \n",
              " 1     03/Jan/2005  MUMBAI       11700                  250   \n",
              " 2     05/Jan/2005  MUMBAI       12100                  250   \n",
              " 3     06/Jan/2005  MUMBAI        9130                  200   \n",
              " 4     07/Jan/2005  MUMBAI        9350                  200   \n",
              " ...           ...     ...         ...                  ...   \n",
              " 4317  09/Mar/2022  MUMBAI        8087                 1000   \n",
              " 4318  10/Mar/2022  MUMBAI        7534                 1000   \n",
              " 4319  11/Mar/2022  MUMBAI       11752                  900   \n",
              " 4320  12/Mar/2022  MUMBAI       13245                  900   \n",
              " 4321          NaN   Total    46869537             848(Avg)   \n",
              " \n",
              "      Price Maximum (Rs/q) Modal Price (Rs/q)  \n",
              " 0                     650                450  \n",
              " 1                     650                450  \n",
              " 2                     650                450  \n",
              " 3                     650                425  \n",
              " 4                     700                450  \n",
              " ...                   ...                ...  \n",
              " 4317                 1500               1250  \n",
              " 4318                 1500               1250  \n",
              " 4319                 1500               1200  \n",
              " 4320                 1500               1200  \n",
              " 4321            1322(Avg)          1088(Avg)  \n",
              " \n",
              " [4322 rows x 6 columns]]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(df)"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EnoOze3JbNpo",
        "outputId": "d1ea1e01-48df-48fb-9ee8-6431880a708d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df)"
      ],
      "metadata": {
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# df[0]\n",
        "# df[1]\n",
        "# df[2]\n",
        "df[3]\n",
        "df[-1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "cBBckthobyKi",
        "outputId": "70bab4a2-8b9d-419a-d5c8-81644164a138"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Date  Market  Arrival(q) Price Minimum (Rs/q)  \\\n",
              "0     01/Jan/2005  MUMBAI       13200                  250   \n",
              "1     03/Jan/2005  MUMBAI       11700                  250   \n",
              "2     05/Jan/2005  MUMBAI       12100                  250   \n",
              "3     06/Jan/2005  MUMBAI        9130                  200   \n",
              "4     07/Jan/2005  MUMBAI        9350                  200   \n",
              "...           ...     ...         ...                  ...   \n",
              "4317  09/Mar/2022  MUMBAI        8087                 1000   \n",
              "4318  10/Mar/2022  MUMBAI        7534                 1000   \n",
              "4319  11/Mar/2022  MUMBAI       11752                  900   \n",
              "4320  12/Mar/2022  MUMBAI       13245                  900   \n",
              "4321          NaN   Total    46869537             848(Avg)   \n",
              "\n",
              "     Price Maximum (Rs/q) Modal Price (Rs/q)  \n",
              "0                     650                450  \n",
              "1                     650                450  \n",
              "2                     650                450  \n",
              "3                     650                425  \n",
              "4                     700                450  \n",
              "...                   ...                ...  \n",
              "4317                 1500               1250  \n",
              "4318                 1500               1250  \n",
              "4319                 1500               1200  \n",
              "4320                 1500               1200  \n",
              "4321            1322(Avg)          1088(Avg)  \n",
              "\n",
              "[4322 rows x 6 columns]"
            ],
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              "\n",
              "  <div id=\"df-f29cb937-b1c3-4a67-ba85-686cfa1eddc6\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Market</th>\n",
              "      <th>Arrival(q)</th>\n",
              "      <th>Price Minimum (Rs/q)</th>\n",
              "      <th>Price Maximum (Rs/q)</th>\n",
              "      <th>Modal Price (Rs/q)</th>\n",
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              "      <th>0</th>\n",
              "      <td>01/Jan/2005</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>13200</td>\n",
              "      <td>250</td>\n",
              "      <td>650</td>\n",
              "      <td>450</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>03/Jan/2005</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>11700</td>\n",
              "      <td>250</td>\n",
              "      <td>650</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>05/Jan/2005</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>12100</td>\n",
              "      <td>250</td>\n",
              "      <td>650</td>\n",
              "      <td>450</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>06/Jan/2005</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>9130</td>\n",
              "      <td>200</td>\n",
              "      <td>650</td>\n",
              "      <td>425</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>07/Jan/2005</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>9350</td>\n",
              "      <td>200</td>\n",
              "      <td>700</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4317</th>\n",
              "      <td>09/Mar/2022</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>8087</td>\n",
              "      <td>1000</td>\n",
              "      <td>1500</td>\n",
              "      <td>1250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4318</th>\n",
              "      <td>10/Mar/2022</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>7534</td>\n",
              "      <td>1000</td>\n",
              "      <td>1500</td>\n",
              "      <td>1250</td>\n",
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              "    <tr>\n",
              "      <th>4319</th>\n",
              "      <td>11/Mar/2022</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>11752</td>\n",
              "      <td>900</td>\n",
              "      <td>1500</td>\n",
              "      <td>1200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4320</th>\n",
              "      <td>12/Mar/2022</td>\n",
              "      <td>MUMBAI</td>\n",
              "      <td>13245</td>\n",
              "      <td>900</td>\n",
              "      <td>1500</td>\n",
              "      <td>1200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4321</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Total</td>\n",
              "      <td>46869537</td>\n",
              "      <td>848(Avg)</td>\n",
              "      <td>1322(Avg)</td>\n",
              "      <td>1088(Avg)</td>\n",
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              "<p>4322 rows × 6 columns</p>\n",
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              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_html(\"/content/DailyWiseMarketArrivals.html\")[-1]\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "HDIey2WFb1qY",
        "outputId": "54c23fee-1d98-430f-df1f-80b26e263e8d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Date  Market  Arrival(q) Price Minimum (Rs/q)  \\\n",
              "0     01/Jan/2005  MUMBAI       13200                  250   \n",
              "1     03/Jan/2005  MUMBAI       11700                  250   \n",
              "2     05/Jan/2005  MUMBAI       12100                  250   \n",
              "3     06/Jan/2005  MUMBAI        9130                  200   \n",
              "4     07/Jan/2005  MUMBAI        9350                  200   \n",
              "...           ...     ...         ...                  ...   \n",
              "4317  09/Mar/2022  MUMBAI        8087                 1000   \n",
              "4318  10/Mar/2022  MUMBAI        7534                 1000   \n",
              "4319  11/Mar/2022  MUMBAI       11752                  900   \n",
              "4320  12/Mar/2022  MUMBAI       13245                  900   \n",
              "4321          NaN   Total    46869537             848(Avg)   \n",
              "\n",
              "     Price Maximum (Rs/q) Modal Price (Rs/q)  \n",
              "0                     650                450  \n",
              "1                     650                450  \n",
              "2                     650                450  \n",
              "3                     650                425  \n",
              "4                     700                450  \n",
              "...                   ...                ...  \n",
              "4317                 1500               1250  \n",
              "4318                 1500               1250  \n",
              "4319                 1500               1200  \n",
              "4320                 1500               1200  \n",
              "4321            1322(Avg)          1088(Avg)  \n",
              "\n",
              "[4322 rows x 6 columns]"
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              "      <td>09/Mar/2022</td>\n",
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              "      <td>1322(Avg)</td>\n",
              "      <td>1088(Avg)</td>\n",
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              "<p>4322 rows × 6 columns</p>\n",
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              "\n",
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              "          const element = document.querySelector('#df-0b9bc664-05d0-4042-af1a-eb2108070734');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YVk-3SGpcH4I",
        "outputId": "73b1a00f-44de-4ac0-fc14-a28ba3701fb3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 4322 entries, 0 to 4321\n",
            "Data columns (total 6 columns):\n",
            " #   Column                Non-Null Count  Dtype \n",
            "---  ------                --------------  ----- \n",
            " 0   Date                  4321 non-null   object\n",
            " 1   Market                4322 non-null   object\n",
            " 2   Arrival(q)            4322 non-null   int64 \n",
            " 3   Price Minimum (Rs/q)  4322 non-null   object\n",
            " 4   Price Maximum (Rs/q)  4322 non-null   object\n",
            " 5   Modal Price (Rs/q)    4322 non-null   object\n",
            "dtypes: int64(1), object(5)\n",
            "memory usage: 202.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BuldGhbicjM4",
        "outputId": "61618e36-80a7-460c-a2ad-4b4d755a5855"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date                    1\n",
              "Market                  0\n",
              "Arrival(q)              0\n",
              "Price Minimum (Rs/q)    0\n",
              "Price Maximum (Rs/q)    0\n",
              "Modal Price (Rs/q)      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.dropna() #drops all the rows where there is a null value \n",
        "# df.fillna(0)"
      ],
      "metadata": {
        "id": "96Y42rhAcriz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QhzRN-Ybdkfw",
        "outputId": "2cb15131-d2da-41cd-f52d-a56c4aac2865"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date                    0\n",
              "Market                  0\n",
              "Arrival(q)              0\n",
              "Price Minimum (Rs/q)    0\n",
              "Price Maximum (Rs/q)    0\n",
              "Modal Price (Rs/q)      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3_-zCGV-ednN",
        "outputId": "1b7b3690-41ee-43fd-ea32-ff73d82a52d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 4321 entries, 0 to 4320\n",
            "Data columns (total 6 columns):\n",
            " #   Column                Non-Null Count  Dtype \n",
            "---  ------                --------------  ----- \n",
            " 0   Date                  4321 non-null   object\n",
            " 1   Market                4321 non-null   object\n",
            " 2   Arrival(q)            4321 non-null   int64 \n",
            " 3   Price Minimum (Rs/q)  4321 non-null   object\n",
            " 4   Price Maximum (Rs/q)  4321 non-null   object\n",
            " 5   Modal Price (Rs/q)    4321 non-null   object\n",
            "dtypes: int64(1), object(5)\n",
            "memory usage: 236.3+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "SuBiadIueffO",
        "outputId": "2546b763-400d-4fae-8304-f422245dd670"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "             Date  Market  Arrival(q) Price Minimum (Rs/q)  \\\n",
              "4316  08/Mar/2022  MUMBAI        9556                 1000   \n",
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              "4320  12/Mar/2022  MUMBAI       13245                  900   \n",
              "\n",
              "     Price Maximum (Rs/q) Modal Price (Rs/q)  \n",
              "4316                 1600               1300  \n",
              "4317                 1500               1250  \n",
              "4318                 1500               1250  \n",
              "4319                 1500               1200  \n",
              "4320                 1500               1200  "
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e1aa4184-9aae-4c6e-89d7-61b537ccbf62 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e1aa4184-9aae-4c6e-89d7-61b537ccbf62');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv('crop_data.csv')"
      ],
      "metadata": {
        "id": "OwZFcxvRfPWs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.rename(columns = {'Modal Price (Rs/q)':'y','Date':'ds'},inplace=True)\n",
        "# by default it creates a duplicate dataframe \n",
        "# to not create any duplicate dataframe we give inplace=True"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RgJQ7B2efbB4",
        "outputId": "c3fb244b-4e0c-4993-8aa2-da183bded46a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/frame.py:5047: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  errors=errors,\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8_2K4-LbgVWN",
        "outputId": "0b65025d-43cb-4a0d-978e-21bf5793fb98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 4321 entries, 0 to 4320\n",
            "Data columns (total 6 columns):\n",
            " #   Column                Non-Null Count  Dtype \n",
            "---  ------                --------------  ----- \n",
            " 0   ds                    4321 non-null   object\n",
            " 1   Market                4321 non-null   object\n",
            " 2   Arrival(q)            4321 non-null   int64 \n",
            " 3   Price Minimum (Rs/q)  4321 non-null   object\n",
            " 4   Price Maximum (Rs/q)  4321 non-null   object\n",
            " 5   y                     4321 non-null   object\n",
            "dtypes: int64(1), object(5)\n",
            "memory usage: 236.3+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new = df[['ds','y']]\n",
        "df_new"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "sURMoRlHgfE6",
        "outputId": "eb4f31e6-71a6-49bc-958c-8973ef4bd5fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               ds     y\n",
              "0     01/Jan/2005   450\n",
              "1     03/Jan/2005   450\n",
              "2     05/Jan/2005   450\n",
              "3     06/Jan/2005   425\n",
              "4     07/Jan/2005   450\n",
              "...           ...   ...\n",
              "4316  08/Mar/2022  1300\n",
              "4317  09/Mar/2022  1250\n",
              "4318  10/Mar/2022  1250\n",
              "4319  11/Mar/2022  1200\n",
              "4320  12/Mar/2022  1200\n",
              "\n",
              "[4321 rows x 2 columns]"
            ],
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              "  <div id=\"df-e59f8a24-b3a9-4b94-9bb9-94d6fcbd7cfe\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    .dataframe tbody tr th {\n",
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              "      <th>ds</th>\n",
              "      <th>y</th>\n",
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              "      <th>0</th>\n",
              "      <td>01/Jan/2005</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>03/Jan/2005</td>\n",
              "      <td>450</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>05/Jan/2005</td>\n",
              "      <td>450</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>06/Jan/2005</td>\n",
              "      <td>425</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>07/Jan/2005</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "      <th>4316</th>\n",
              "      <td>08/Mar/2022</td>\n",
              "      <td>1300</td>\n",
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              "    <tr>\n",
              "      <th>4317</th>\n",
              "      <td>09/Mar/2022</td>\n",
              "      <td>1250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4318</th>\n",
              "      <td>10/Mar/2022</td>\n",
              "      <td>1250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4319</th>\n",
              "      <td>11/Mar/2022</td>\n",
              "      <td>1200</td>\n",
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              "    <tr>\n",
              "      <th>4320</th>\n",
              "      <td>12/Mar/2022</td>\n",
              "      <td>1200</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>4321 rows × 2 columns</p>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
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              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "      background-color: #3B4455;\n",
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              "\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-e59f8a24-b3a9-4b94-9bb9-94d6fcbd7cfe button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e59f8a24-b3a9-4b94-9bb9-94d6fcbd7cfe');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new['ds'] = pd.to_datetime(df_new['ds']) #convert object to datetime64[ns] datatype\n",
        "df_new['y'] = df_new['y'].astype(int)  #type casting from object to int datatype"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gIuVYwc8hmy3",
        "outputId": "2b300c01-a011-4639-8f10-1779c5251c9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JczB1X9Oh5sb",
        "outputId": "52d18106-8d66-4c09-bb9c-bea9a97b44af"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 4321 entries, 0 to 4320\n",
            "Data columns (total 2 columns):\n",
            " #   Column  Non-Null Count  Dtype         \n",
            "---  ------  --------------  -----         \n",
            " 0   ds      4321 non-null   datetime64[ns]\n",
            " 1   y       4321 non-null   int64         \n",
            "dtypes: datetime64[ns](1), int64(1)\n",
            "memory usage: 101.3 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "plt.figure(figsize=(25,10))\n",
        "plt.scatter(df_new['ds'],df_new['y'])\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "id": "sXX4olFziF-G",
        "outputId": "014e304d-f4dd-4376-8060-2c9b59e31c46"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x720 with 1 Axes>"
            ],
            "image/png": 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          },
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "df_new['y'] = np.where(df_new['y']>2500, np.nan, df_new['y'])\n",
        "df_new"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 528
        },
        "id": "TNzPrfVg8zd3",
        "outputId": "b4e61b80-aa37-4441-a891-a67ae8683c48"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             ds       y\n",
              "0    2005-01-01   450.0\n",
              "1    2005-01-03   450.0\n",
              "2    2005-01-05   450.0\n",
              "3    2005-01-06   425.0\n",
              "4    2005-01-07   450.0\n",
              "...         ...     ...\n",
              "4316 2022-03-08  1300.0\n",
              "4317 2022-03-09  1250.0\n",
              "4318 2022-03-10  1250.0\n",
              "4319 2022-03-11  1200.0\n",
              "4320 2022-03-12  1200.0\n",
              "\n",
              "[4321 rows x 2 columns]"
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-24388e34-6f9e-4ebc-8134-dfe2ea45386e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-24388e34-6f9e-4ebc-8134-dfe2ea45386e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "plt.figure(figsize=(25,10))\n",
        "plt.scatter(df_new['ds'],df_new['y'])\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "id": "dLuos-IN9r5U",
        "outputId": "17290255-0579-4b40-cbd8-2505d4332559"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x720 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f0YxIY8F9uPI",
        "outputId": "646632f2-ac1d-443d-d667-fb638a4f05d2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ds     0\n",
              "y     28\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#FBPROPHET \n",
        "import fbprophet \n",
        "op = fbprophet.Prophet()"
      ],
      "metadata": {
        "id": "IzddteG5ic8l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "op.fit(df_new)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_U57PRAo-7Ah",
        "outputId": "68b758e1-adbf-4918-9363-bd441d3919dc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fbprophet.forecaster.Prophet at 0x7fa0104f0b90>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "forecast = op.make_future_dataframe(periods=500,freq = 'D')"
      ],
      "metadata": {
        "id": "XeiL_1to--0G"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "forecast = op.predict(forecast)"
      ],
      "metadata": {
        "id": "HOc3YO-c_Ojx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "op.plot(forecast,xlabel ='Date',ylabel = 'Potato price/q')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "LUBcVgE8_Rzd",
        "outputId": "02093647-e87f-42a0-f959-15c7961c0dd9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}