Manila_South_Harbor_Sea_Level_Prediction_using_SARIMA_Model.ipynb

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        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import datetime"
      ]
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      "cell_type": "code",
      "source": [
        "df=pd.read_csv(\"SeaLevel.csv\")"
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              "   Year  Sea_ Level\n",
              "0  1902        6677\n",
              "1  1903        6655\n",
              "2  1904        6689\n",
              "3  1905        6678\n",
              "4  1906        6727"
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 120 entries, 0 to 119\n",
            "Data columns (total 2 columns):\n",
            " #   Column      Non-Null Count  Dtype\n",
            "---  ------      --------------  -----\n",
            " 0   Year        120 non-null    int64\n",
            " 1   Sea_ Level  120 non-null    int64\n",
            "dtypes: int64(2)\n",
            "memory usage: 2.0 KB\n"
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      "source": [
        "#converting year column into datetime\n",
        "df['Year'] = pd.to_datetime(df['Year'], format='%Y')"
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        "# setting the date column as our index\n",
        "df = df.set_index('Year')\n",
        "df.head()"
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              "            Sea_ Level\n",
              "Year                  \n",
              "1902-01-01        6677\n",
              "1903-01-01        6655\n",
              "1904-01-01        6689\n",
              "1905-01-01        6678\n",
              "1906-01-01        6727"
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              "      <td>6655</td>\n",
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              "      <td>6689</td>\n",
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      "source": [
        "# Checking if there are any negative values\n",
        "(df < 0).values.any()"
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      "execution_count": null,
      "outputs": [
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          "data": {
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              "True"
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      "cell_type": "code",
      "source": [
        "# Removing any negative values that may affect the plot\n",
        "df = df[df.select_dtypes(include=[np.number]).ge(0).all(1)]"
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      "metadata": {
        "id": "Qmg0EYVy8Ben"
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    {
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      "source": [
        "# **Plotting Time Series**"
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      "source": [
        "fig = plt.figure(figsize=(15,6))\n",
        "plt.plot(df.index, df['Sea_ Level'])"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "result = seasonal_decompose(df['Sea_ Level'], model='multiplicative', freq=30)\n",
        "fig = plt.figure()\n",
        "fig = result.plot()\n",
        "fig.set_size_inches(15,10)\n",
        "plt.suptitle('Manila South Harbor Sea Level Rise', y=1.01)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 775
        },
        "id": "XVUNpYEQ9CvW",
        "outputId": "5e78c660-4cb5-4c8c-ab31-bf26b3f9533e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-22-6308b7c0d233>:2: FutureWarning: the 'freq'' keyword is deprecated, use 'period' instead\n",
            "  result = seasonal_decompose(df['Sea_ Level'], model='multiplicative', freq=30)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.01, 'Manila South Harbor Sea Level Rise')"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "next_years = [pd.to_datetime('2023-01-01'),\n",
        "              pd.to_datetime('2024-01-01'),\n",
        "              pd.to_datetime('2025-01-01'),\n",
        "              pd.to_datetime('2026-01-01'),\n",
        "              pd.to_datetime('2027-01-01'),\n",
        "              pd.to_datetime('2028-01-01'),\n",
        "              pd.to_datetime('2029-01-01'),\n",
        "              pd.to_datetime('2030-01-01'),\n",
        "              pd.to_datetime('2031-01-01'),\n",
        "              pd.to_datetime('2032-01-01'),\n",
        "              pd.to_datetime('2033-01-01')]\n",
        "test2 = pd.Series(next_years)"
      ],
      "metadata": {
        "id": "H6HVukTC-st_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test2 = pd.DataFrame(test2, columns=['Year'])\n",
        "test2['Year'] = pd.to_datetime(test2['Year'], format='%Y')\n",
        "test2.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "8H921pWc_LsW",
        "outputId": "9548344e-434b-47ce-9337-5bb2b71e1c18"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Year\n",
              "0 2023-01-01\n",
              "1 2024-01-01\n",
              "2 2025-01-01\n",
              "3 2026-01-01\n",
              "4 2027-01-01"
            ],
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              "      <td>2023-01-01</td>\n",
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              "    }\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",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d1468384-9213-4db4-872d-024ddfca4711 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-d1468384-9213-4db4-872d-024ddfca4711');\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": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts = df['Sea_ Level']"
      ],
      "metadata": {
        "id": "2F2LEsbH_Y1D"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.tsa.stattools import adfuller\n",
        "def test_stationarity(timeseries):\n",
        "\n",
        "    dftest = adfuller(timeseries, autolag='AIC')\n",
        "    dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])\n",
        "    for key,value in dftest[4].items():\n",
        "        dfoutput['Critical Value (%s)'%key] = value\n",
        "\n",
        "    critical_value = dftest[4]['5%']\n",
        "    test_statistic = dftest[0]\n",
        "    alpha = 1e-3\n",
        "    pvalue = dftest[1]\n",
        "    if pvalue < alpha and test_statistic < critical_value:  # null hypothesis: x is non stationary\n",
        "        print(\"X is stationary\")\n",
        "        return True\n",
        "    else:\n",
        "        print(\"X is not stationary\")\n",
        "        return False"
      ],
      "metadata": {
        "id": "vJ5Bgdpt_qnO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ts_diff = pd.Series(ts)\n",
        "d = 0\n",
        "while test_stationarity(ts_diff) is False:\n",
        "    ts_diff = ts_diff.diff().dropna()\n",
        "    d = d + 1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GgMkLtbM_0S6",
        "outputId": "ac95282f-770b-4d6d-b522-ae76f6036d13"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X is not stationary\n",
            "X is stationary\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
        "plot_acf(df['Sea_ Level'], lags =12)\n",
        "plt.show()\n",
        "print(\"\\n\")\n",
        "plot_pacf(df['Sea_ Level'], lags =12)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "PuWODuDM_3Q7",
        "outputId": "5b0926cd-81ea-42b1-f94a-1876a960a955"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
        "\n",
        "p = 8\n",
        "q = 1\n",
        "model = SARIMAX(ts, order=(p,d,q))\n",
        "model_fit = model.fit(disp=1,solver='powell')\n",
        "\n",
        "fcast = model_fit.get_prediction(start=1, end=len(ts)+10)\n",
        "ts_p = fcast.predicted_mean\n",
        "ts_ci = fcast.conf_int()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mc9XvbqbACCU",
        "outputId": "6b87c1c2-e927-4279-dd70-247c7ef3101f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/statsmodels/tsa/base/tsa_model.py:581: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.\n",
            "  warnings.warn('A date index has been provided, but it has no'\n",
            "/usr/local/lib/python3.8/dist-packages/statsmodels/base/model.py:566: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
            "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n",
            "/usr/local/lib/python3.8/dist-packages/statsmodels/tsa/base/tsa_model.py:376: ValueWarning: No supported index is available. Prediction results will be given with an integer index beginning at `start`.\n",
            "  warnings.warn('No supported index is available.'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts_p"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GnRniAKmALEX",
        "outputId": "341217ef-fcd0-46dc-a016-d83de54eecff"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1      6672.650138\n",
              "2      6660.602557\n",
              "3      6680.074916\n",
              "4      6680.180489\n",
              "5      6712.231601\n",
              "          ...     \n",
              "100    7680.110927\n",
              "101    7690.930777\n",
              "102    7699.057354\n",
              "103    7708.037269\n",
              "104    7718.018364\n",
              "Name: predicted_mean, Length: 104, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = pd.read_csv('SeaLevel.csv')\n",
        "df2['Year'] = pd.to_datetime(df2['Year'], format='%Y')\n",
        "#df.set_index('date', inplace=True)\n",
        "df2 = df2[df2.select_dtypes(include=[np.number]).ge(0).all(1)]\n",
        "df2.drop(columns=['Sea_ Level'], inplace=True)"
      ],
      "metadata": {
        "id": "P9nYF8TmAQpe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2.reset_index(inplace=True)"
      ],
      "metadata": {
        "id": "nWrlqUhTBoZS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2.drop(columns=['index'], inplace=True)"
      ],
      "metadata": {
        "id": "h5FIvdNYBr_H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "jf3vkF3zBvE-",
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        "test2.reset_index(inplace=True)\n",
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        "test2.rename(columns= {0: \"Year\"}, inplace=True)"
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      "outputs": []
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    {
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      "source": [
        "df2 = df2.append(test2, ignore_index=True)"
      ],
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        "id": "lt0_P-tuECmq"
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      "outputs": []
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              "          const element = document.querySelector('#df-27cc9cfb-415f-4b42-bba1-384572f33d30');\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",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          },
          "metadata": {},
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    },
    {
      "cell_type": "code",
      "source": [
        "df2['Sea_ level'] = ts_pred['predicted_mean']"
      ],
      "metadata": {
        "id": "8hvfcfDqElad"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2.set_index('Year', inplace=True)"
      ],
      "metadata": {
        "id": "5RcxxIeyE1jy"
      },
      "execution_count": null,
      "outputs": []
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    {
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        "df2.dropna(inplace=True)\n",
        "df2"
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          "height": 455
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              "             Sea_ level\n",
              "Year                   \n",
              "1902-01-01  6672.650138\n",
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              "1904-01-01  6680.074916\n",
              "1905-01-01  6680.180489\n",
              "1906-01-01  6712.231601\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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        "ts_ci.reset_index(inplace=True)\n",
        "ts_ci.drop(columns=['index'], inplace=True)"
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        "id": "wpaSyQ_TFG3a"
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      "outputs": []
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    {
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      "source": [
        "df3 = pd.read_csv('SeaLevel.csv')\n",
        "df3['Year'] = pd.to_datetime(df3['Year'], format='%Y')\n",
        "#df.set_index('date', inplace=True)\n",
        "df3 = df3[df3.select_dtypes(include=[np.number]).ge(0).all(1)]\n",
        "df3.drop(columns=['Sea_ Level'], inplace=True)"
      ],
      "metadata": {
        "id": "8A9uGvkFFLju"
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      "outputs": []
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      "outputs": []
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    {
      "cell_type": "code",
      "source": [
        "df3 = df3.append(test2, ignore_index=True)"
      ],
      "metadata": {
        "id": "bMaGMLdYJocY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3['lower Sea_ Level'] = ts_ci['lower Sea_ Level']\n",
        "df3['upper Sea_ Level'] = ts_ci['upper Sea_ Level']"
      ],
      "metadata": {
        "id": "jrSjA5amJq5X"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3.set_index('Year', inplace=True)"
      ],
      "metadata": {
        "id": "2aIpy5bsJyVM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3.dropna(inplace=True)\n",
        "df3"
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          "base_uri": "https://localhost:8080/",
          "height": 455
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        "id": "LXb-itwQJ_Z8",
        "outputId": "c8eabcd9-9e27-4dc5-e45a-e67ff0290608"
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      "execution_count": null,
      "outputs": [
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          "data": {
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              "            lower Sea_ Level  upper Sea_ Level\n",
              "Year                                          \n",
              "1902-01-01       6582.299193       6763.001082\n",
              "1903-01-01       6574.611340       6746.593773\n",
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              "...                      ...               ...\n",
              "2028-01-01       7521.816164       7838.405690\n",
              "2029-01-01       7517.877475       7863.984078\n",
              "2030-01-01       7513.351821       7884.762887\n",
              "2031-01-01       7508.925068       7907.149471\n",
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              "\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",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c2692d2f-91e6-49b1-9ea6-a363c2c4a64e 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-c2692d2f-91e6-49b1-9ea6-a363c2c4a64e');\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": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plt.show()\n",
        "plt.plot(df2,label='prediction')\n",
        "plt.plot(df['Sea_ Level'],color='red',label='actual')\n",
        "plt.fill_between(df3.index[1:],\n",
        "                df3.iloc[1:, 0],\n",
        "                df3.iloc[1:, 1], color='k', alpha=.2)\n",
        "\n",
        "plt.ylabel('Sea Level Mean')\n",
        "plt.legend()\n",
        "plt.tight_layout()\n",
        "plt.grid()\n",
        "#plt.savefig('plots/IT_trend_prediction.png')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 314
        },
        "id": "NaG61_74KFjg",
        "outputId": "4d7fe4a4-686c-4758-cb38-5a985ccb8350"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}