EBITDA(ML).ipynb

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  "metadata": {
    "colab": {
      "name": "EBITDA(ML).ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "rDQZmmU4cdxY"
      },
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pylab as plt\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "import io\n",
        "from google.colab import files\n",
        "sns.set_style(\"whitegrid\")\n",
        "%matplotlib inline\n",
        "import plotly.express as px\n",
        "import plotly.graph_objects as go \n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn import preprocessing\n",
        "from scipy import stats\n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.model_selection import cross_val_predict"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "Va026jwfdKAD",
        "outputId": "2fd8ea18-6838-4e9d-bb02-322364a965c8"
      },
      "source": [
        "uploaded = files.upload()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-9d571a76-5927-400d-b30b-fd36e90386af\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-9d571a76-5927-400d-b30b-fd36e90386af\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving yhat2.csv to yhat2.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "id": "Gs7JDfLA7WtY",
        "outputId": "ad0c8a65-4875-4433-da7e-39ff628f86ea"
      },
      "source": [
        "df1 = pd.read_csv(io.BytesIO(uploaded['yhat2.csv']))\n",
        "df1.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Dates_</th>\n",
              "      <th>Hotel</th>\n",
              "      <th>Food</th>\n",
              "      <th>Beverage</th>\n",
              "      <th>F&amp;B</th>\n",
              "      <th>Spa</th>\n",
              "      <th>REVENUE</th>\n",
              "      <th>COS  (gross)</th>\n",
              "      <th>OpExp</th>\n",
              "      <th>FixExp</th>\n",
              "      <th>Op+Fix_Exp</th>\n",
              "      <th>CorpExp</th>\n",
              "      <th>EBITDA</th>\n",
              "      <th>Date</th>\n",
              "      <th>y_hat</th>\n",
              "      <th>yhat1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>92261.180204</td>\n",
              "      <td>75081.284922</td>\n",
              "      <td>60255.705116</td>\n",
              "      <td>135336.99000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>227598.1702</td>\n",
              "      <td>35498.871005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>90952.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>101147.511981</td>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>90605.816266</td>\n",
              "      <td>88632.370626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2016-02-01</td>\n",
              "      <td>71652.459665</td>\n",
              "      <td>67013.831684</td>\n",
              "      <td>51465.260916</td>\n",
              "      <td>118479.09260</td>\n",
              "      <td>0.0</td>\n",
              "      <td>190131.5523</td>\n",
              "      <td>32004.993231</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>92950.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>65176.852916</td>\n",
              "      <td>2016-02-01</td>\n",
              "      <td>66728.379852</td>\n",
              "      <td>63972.011076</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>82218.545266</td>\n",
              "      <td>68057.925466</td>\n",
              "      <td>54043.365802</td>\n",
              "      <td>122101.29130</td>\n",
              "      <td>0.0</td>\n",
              "      <td>204319.8365</td>\n",
              "      <td>33577.743298</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96491.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>74251.048211</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>73889.523120</td>\n",
              "      <td>71804.726212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2016-04-01</td>\n",
              "      <td>82267.407633</td>\n",
              "      <td>49679.356863</td>\n",
              "      <td>45048.526943</td>\n",
              "      <td>94727.88381</td>\n",
              "      <td>0.0</td>\n",
              "      <td>176995.2914</td>\n",
              "      <td>27772.245171</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96904.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52318.700007</td>\n",
              "      <td>2016-04-01</td>\n",
              "      <td>52994.450854</td>\n",
              "      <td>52189.748714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2016-05-01</td>\n",
              "      <td>64418.259843</td>\n",
              "      <td>46240.111203</td>\n",
              "      <td>39537.548435</td>\n",
              "      <td>85777.65964</td>\n",
              "      <td>0.0</td>\n",
              "      <td>150195.9195</td>\n",
              "      <td>27132.957779</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>95536.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27527.099200</td>\n",
              "      <td>2016-05-01</td>\n",
              "      <td>34886.526818</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Dates_         Hotel  ...         y_hat         yhat1\n",
              "0  2016-01-01  92261.180204  ...  90605.816266  88632.370626\n",
              "1  2016-02-01  71652.459665  ...  66728.379852  63972.011076\n",
              "2  2016-03-01  82218.545266  ...  73889.523120  71804.726212\n",
              "3  2016-04-01  82267.407633  ...  52994.450854  52189.748714\n",
              "4  2016-05-01  64418.259843  ...  34886.526818  33190.904229\n",
              "\n",
              "[5 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "id": "89CrIomK7jXB",
        "outputId": "6e93165d-25fa-4015-c169-674493dde06b"
      },
      "source": [
        "df1.set_index('Dates_', inplace=True)\n",
        "df1.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>Hotel</th>\n",
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              "      <th>Spa</th>\n",
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              "      <th>FixExp</th>\n",
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              "      <th>CorpExp</th>\n",
              "      <th>EBITDA</th>\n",
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              "    <tr>\n",
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              "      <td>82267.407633</td>\n",
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            ],
            "text/plain": [
              "                   Hotel          Food  ...         y_hat         yhat1\n",
              "Dates_                                  ...                            \n",
              "2016-01-01  92261.180204  75081.284922  ...  90605.816266  88632.370626\n",
              "2016-02-01  71652.459665  67013.831684  ...  66728.379852  63972.011076\n",
              "2016-03-01  82218.545266  68057.925466  ...  73889.523120  71804.726212\n",
              "2016-04-01  82267.407633  49679.356863  ...  52994.450854  52189.748714\n",
              "2016-05-01  64418.259843  46240.111203  ...  34886.526818  33190.904229\n",
              "\n",
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    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "id": "6WGHzRqYeUAv",
        "outputId": "b99f4a65-978b-403d-b463-aa50b2de479f"
      },
      "source": [
        "df1.index = pd.to_datetime(df1.index)\n",
        "df1.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Hotel</th>\n",
              "      <th>Food</th>\n",
              "      <th>Beverage</th>\n",
              "      <th>F&amp;B</th>\n",
              "      <th>Spa</th>\n",
              "      <th>REVENUE</th>\n",
              "      <th>COS  (gross)</th>\n",
              "      <th>OpExp</th>\n",
              "      <th>FixExp</th>\n",
              "      <th>Op+Fix_Exp</th>\n",
              "      <th>CorpExp</th>\n",
              "      <th>EBITDA</th>\n",
              "      <th>Date</th>\n",
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              "    <tr>\n",
              "      <th>Dates_</th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th>2016-01-01</th>\n",
              "      <td>92261.180204</td>\n",
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              "      <td>71652.459665</td>\n",
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              "      <td>66728.379852</td>\n",
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              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>82218.545266</td>\n",
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              "      <td>73889.523120</td>\n",
              "      <td>71804.726212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>82267.407633</td>\n",
              "      <td>49679.356863</td>\n",
              "      <td>45048.526943</td>\n",
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              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Hotel          Food  ...         y_hat         yhat1\n",
              "Dates_                                  ...                            \n",
              "2016-01-01  92261.180204  75081.284922  ...  90605.816266  88632.370626\n",
              "2016-02-01  71652.459665  67013.831684  ...  66728.379852  63972.011076\n",
              "2016-03-01  82218.545266  68057.925466  ...  73889.523120  71804.726212\n",
              "2016-04-01  82267.407633  49679.356863  ...  52994.450854  52189.748714\n",
              "2016-05-01  64418.259843  46240.111203  ...  34886.526818  33190.904229\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YtSzC_bsfrof",
        "outputId": "17f4004a-6a31-46ab-cce0-8b8e133e1730"
      },
      "source": [
        "df1.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Hotel', 'Food', 'Beverage', 'F&B', 'Spa', 'REVENUE', 'COS  (gross)',\n",
              "       'OpExp', 'FixExp', 'Op+Fix_Exp', 'CorpExp', 'EBITDA', 'Date', 'y_hat',\n",
              "       'yhat1'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DulToToK8dhi"
      },
      "source": [
        "Yhat = a + b_1 X_1 + b_2 X_2 + b_3 X_3\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "1NIlkzVDe677",
        "outputId": "76ea0d91-bc23-4a8f-db4e-033dcf28e466"
      },
      "source": [
        "plt.figure(figsize=(10,7))\n",
        "plt.title('Regression vs. EBITDA')\n",
        "\n",
        "plt.xlabel('Años')\n",
        "plt.ylabel('US DOLLAR')\n",
        "plt.plot(df1.EBITDA, 'y.-', label='EBITDA')\n",
        "plt.plot(df1.y_hat, 'b.-', label='Regression')\n",
        "plt.plot(df1.yhat1, 'r.-', label='Regression 1')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-6kuBMLUlMO9"
      },
      "source": [
        "y_data = df1['EBITDA']\n",
        "x_data = df1[['Hotel', 'F&B', 'COS  (gross)']]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KLqxoAckEvYD"
      },
      "source": [
        "**Train test split**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J2IG8BWmit3S",
        "outputId": "49718fcd-db12-464f-efab-fb9cb3e28bc7"
      },
      "source": [
        "x_train, x_test, y_train, y_test = train_test_split(x_data, y_data, test_size=0.33, random_state=3)\n",
        "print(\"number of test samples :\", x_test.shape[0])\n",
        "print(\"number of training samples:\",x_train.shape[0])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "number of test samples : 22\n",
            "number of training samples: 42\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "TUwb2LlBSFOA",
        "outputId": "8d977190-e570-4213-9c1b-75e76d66f6e3"
      },
      "source": [
        "x_train.head()"
      ],
      "execution_count": null,
      "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>Hotel</th>\n",
              "      <th>F&amp;B</th>\n",
              "      <th>COS  (gross)</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dates_</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-11-01</th>\n",
              "      <td>78676.000000</td>\n",
              "      <td>98379.0000</td>\n",
              "      <td>34463.323300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-05-01</th>\n",
              "      <td>86373.129000</td>\n",
              "      <td>113733.7741</td>\n",
              "      <td>35298.534500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-04-01</th>\n",
              "      <td>95544.448500</td>\n",
              "      <td>133662.0339</td>\n",
              "      <td>37748.046400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-01</th>\n",
              "      <td>104771.913800</td>\n",
              "      <td>169854.2417</td>\n",
              "      <td>47998.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-12-01</th>\n",
              "      <td>82124.540798</td>\n",
              "      <td>100940.7351</td>\n",
              "      <td>27571.157085</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    Hotel          F&B  COS  (gross)\n",
              "Dates_                                              \n",
              "2018-11-01   78676.000000   98379.0000  34463.323300\n",
              "2017-05-01   86373.129000  113733.7741  35298.534500\n",
              "2017-04-01   95544.448500  133662.0339  37748.046400\n",
              "2019-01-01  104771.913800  169854.2417  47998.000000\n",
              "2016-12-01   82124.540798  100940.7351  27571.157085"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "uCuryYGJSnd1",
        "outputId": "38f4d0ac-44bc-459c-e618-d00967f6ddec"
      },
      "source": [
        "x_test.head()"
      ],
      "execution_count": null,
      "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>Hotel</th>\n",
              "      <th>F&amp;B</th>\n",
              "      <th>COS  (gross)</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dates_</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-07-01</th>\n",
              "      <td>59663.130752</td>\n",
              "      <td>81608.35458</td>\n",
              "      <td>25026.665141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-08-01</th>\n",
              "      <td>38013.000000</td>\n",
              "      <td>77370.00000</td>\n",
              "      <td>32252.997900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-01</th>\n",
              "      <td>65495.000000</td>\n",
              "      <td>64686.00000</td>\n",
              "      <td>24598.846600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-01-01</th>\n",
              "      <td>110458.000000</td>\n",
              "      <td>198291.00000</td>\n",
              "      <td>61832.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-01-01</th>\n",
              "      <td>113395.000000</td>\n",
              "      <td>152661.00000</td>\n",
              "      <td>49573.682200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    Hotel           F&B  COS  (gross)\n",
              "Dates_                                               \n",
              "2016-07-01   59663.130752   81608.35458  25026.665141\n",
              "2020-08-01   38013.000000   77370.00000  32252.997900\n",
              "2020-03-01   65495.000000   64686.00000  24598.846600\n",
              "2021-01-01  110458.000000  198291.00000  61832.000000\n",
              "2020-01-01  113395.000000  152661.00000  49573.682200"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_BX-rCOME7lk"
      },
      "source": [
        "**Regresión Multilineal Metodo Train test split** "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UcZUreqTmOD7"
      },
      "source": [
        "lr=LinearRegression()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0G6XmEk_mklZ",
        "outputId": "8d9b2d70-06b0-4f1c-effb-e4ca2109aed4"
      },
      "source": [
        "lr.fit(x_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7uwukTcsnYUW",
        "outputId": "a9690427-43a2-4c7b-9f45-675b3f11e9ea"
      },
      "source": [
        "lr.intercept_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-54514.805940444385"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vIuwcc9KnfrR",
        "outputId": "83259d4d-7aa1-491e-ffc7-d1c551acc5e6"
      },
      "source": [
        "lr.coef_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.6039252 ,  1.02024285, -1.42675726])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mfFe7bTIURVZ"
      },
      "source": [
        "Yhat = a + b_1 X_1 + b_2 X_2 + b_3 X_3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aCcjQDmNnqV2",
        "outputId": "0b0e2298-7c22-49e1-c68f-8f9640b30f51"
      },
      "source": [
        "lr.score(x_test, y_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9178560818111453"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qi3ch6LZ4a6A",
        "outputId": "e9151680-ccf0-401a-e273-196b5a6b3b1d"
      },
      "source": [
        "lr.predict(x_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 29070.62656052,   1361.19328716,  15938.12129383, 126279.28441165,\n",
              "        98988.97532939,  97496.01141222,  19856.53151319,  96551.52308104,\n",
              "       114608.92147984,  69415.82804106,  39445.49317842,  76786.30528709,\n",
              "        72493.5274502 ,  44725.43558266,  33190.90422893,  73679.72049429,\n",
              "        21543.67673961,  48477.39865339,  80990.52999951, -60571.5189146 ,\n",
              "       -57894.47861194,  95375.75697695])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2tmcIO1KsEcY",
        "outputId": "e63f712e-4b4a-4f62-8031-12bb295fd84d"
      },
      "source": [
        "yhat1 = lr.predict(x_data)\n",
        "yhat1[0:10]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([88632.37062621, 63972.0110764 , 71804.72621237, 52189.74871409,\n",
              "       33190.90422893,  9782.36318093, 29070.62656052,  9855.15133672,\n",
              "       -1668.60264928, 21543.67673961])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "id": "qK3N1txPAWMS",
        "outputId": "d4e8213f-170d-4d23-b37c-9966f6ec8b91"
      },
      "source": [
        "df1.head()"
      ],
      "execution_count": null,
      "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",
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              "    .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>Hotel</th>\n",
              "      <th>Food</th>\n",
              "      <th>Beverage</th>\n",
              "      <th>F&amp;B</th>\n",
              "      <th>Spa</th>\n",
              "      <th>REVENUE</th>\n",
              "      <th>COS  (gross)</th>\n",
              "      <th>OpExp</th>\n",
              "      <th>FixExp</th>\n",
              "      <th>Op+Fix_Exp</th>\n",
              "      <th>CorpExp</th>\n",
              "      <th>EBITDA</th>\n",
              "      <th>Date</th>\n",
              "      <th>y_hat</th>\n",
              "      <th>yhat1</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dates_</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>92261.180204</td>\n",
              "      <td>75081.284922</td>\n",
              "      <td>60255.705116</td>\n",
              "      <td>135336.99000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>227598.1702</td>\n",
              "      <td>35498.871005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>90952.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>101147.511981</td>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>90605.816266</td>\n",
              "      <td>88632.370626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>71652.459665</td>\n",
              "      <td>67013.831684</td>\n",
              "      <td>51465.260916</td>\n",
              "      <td>118479.09260</td>\n",
              "      <td>0.0</td>\n",
              "      <td>190131.5523</td>\n",
              "      <td>32004.993231</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>92950.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>65176.852916</td>\n",
              "      <td>2016-02-01</td>\n",
              "      <td>66728.379852</td>\n",
              "      <td>63972.011076</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>82218.545266</td>\n",
              "      <td>68057.925466</td>\n",
              "      <td>54043.365802</td>\n",
              "      <td>122101.29130</td>\n",
              "      <td>0.0</td>\n",
              "      <td>204319.8365</td>\n",
              "      <td>33577.743298</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96491.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>74251.048211</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>73889.523120</td>\n",
              "      <td>71804.726212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>82267.407633</td>\n",
              "      <td>49679.356863</td>\n",
              "      <td>45048.526943</td>\n",
              "      <td>94727.88381</td>\n",
              "      <td>0.0</td>\n",
              "      <td>176995.2914</td>\n",
              "      <td>27772.245171</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96904.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52318.700007</td>\n",
              "      <td>2016-04-01</td>\n",
              "      <td>52994.450854</td>\n",
              "      <td>52189.748714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>64418.259843</td>\n",
              "      <td>46240.111203</td>\n",
              "      <td>39537.548435</td>\n",
              "      <td>85777.65964</td>\n",
              "      <td>0.0</td>\n",
              "      <td>150195.9195</td>\n",
              "      <td>27132.957779</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>95536.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27527.099200</td>\n",
              "      <td>2016-05-01</td>\n",
              "      <td>34886.526818</td>\n",
              "      <td>33190.904229</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Hotel          Food  ...         y_hat         yhat1\n",
              "Dates_                                  ...                            \n",
              "2016-01-01  92261.180204  75081.284922  ...  90605.816266  88632.370626\n",
              "2016-02-01  71652.459665  67013.831684  ...  66728.379852  63972.011076\n",
              "2016-03-01  82218.545266  68057.925466  ...  73889.523120  71804.726212\n",
              "2016-04-01  82267.407633  49679.356863  ...  52994.450854  52189.748714\n",
              "2016-05-01  64418.259843  46240.111203  ...  34886.526818  33190.904229\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "95r1mE46-g0-"
      },
      "source": [
        "def DistributionPlot(RedFunction, BlueFunction, RedName, BlueName, Title):\n",
        "    width = 12\n",
        "    height = 10\n",
        "    plt.figure(figsize=(width, height))\n",
        "\n",
        "    ax1 = sns.distplot(RedFunction, hist=False, color=\"r\", label=RedName)\n",
        "    ax2 = sns.distplot(BlueFunction, hist=False, color=\"b\", label=BlueName, ax=ax1)\n",
        "\n",
        "    plt.title(Title)\n",
        "    plt.xlabel('Price (in dollars)')\n",
        "    plt.ylabel('EBITDA')\n",
        "\n",
        "    plt.legend()\n",
        "    plt.show()\n",
        "    plt.close()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 777
        },
        "id": "n1NmS-05_dWv",
        "outputId": "e2dcaf7e-ba8c-4796-a11a-b7b687dc4545"
      },
      "source": [
        "Title = 'Distribution  Plot of  Predicted Value Using Training Data vs Training Data Distribution'\n",
        "DistributionPlot(y_data, yhat1, \"Actual Values (Train)\", \"Predicted Values (Train)\", Title)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F_g_T5fOCq3e"
      },
      "source": [
        "box = df1[['EBITDA', 'yhat1']]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "VbVQivukGIxN",
        "outputId": "ebb09778-8419-450e-bf14-aff0eca55f62"
      },
      "source": [
        "box.describe()"
      ],
      "execution_count": null,
      "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>EBITDA</th>\n",
              "      <th>yhat1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>64.000000</td>\n",
              "      <td>64.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>46969.470445</td>\n",
              "      <td>45001.213862</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>48176.130970</td>\n",
              "      <td>46312.817509</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-63478.588200</td>\n",
              "      <td>-60571.518915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>13049.340906</td>\n",
              "      <td>11845.207100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>45199.101300</td>\n",
              "      <td>44462.361808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>91168.809725</td>\n",
              "      <td>77837.361465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>139931.000000</td>\n",
              "      <td>133469.609961</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              EBITDA          yhat1\n",
              "count      64.000000      64.000000\n",
              "mean    46969.470445   45001.213862\n",
              "std     48176.130970   46312.817509\n",
              "min    -63478.588200  -60571.518915\n",
              "25%     13049.340906   11845.207100\n",
              "50%     45199.101300   44462.361808\n",
              "75%     91168.809725   77837.361465\n",
              "max    139931.000000  133469.609961"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "e6LOJLwBGA11",
        "outputId": "e348e819-c5d3-4480-c65a-574a41481921"
      },
      "source": [
        "sns.boxplot(data=box).set(title= 'Cuartiles EBITDA vs. Predicción')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 777
        },
        "id": "37YsKB-nGXCc",
        "outputId": "894773a3-16ce-4045-9f4a-4afc0b23514b"
      },
      "source": [
        "Title = 'Distribution  Plot of  Predicted Value Using Training Data vs Training Data Distribution'\n",
        "DistributionPlot(y_train, y_test, \"Train Values\", \"Test Values\", Title)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "bts277xADuDh",
        "outputId": "390a887e-6465-4e47-db6c-ff5a3ac70458"
      },
      "source": [
        "corr_predict = df1[['EBITDA', 'y_hat', 'yhat1']]\n",
        "corr_predict.corr()"
      ],
      "execution_count": null,
      "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>EBITDA</th>\n",
              "      <th>y_hat</th>\n",
              "      <th>yhat1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>EBITDA</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.965706</td>\n",
              "      <td>0.965462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>y_hat</th>\n",
              "      <td>0.965706</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999747</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>yhat1</th>\n",
              "      <td>0.965462</td>\n",
              "      <td>0.999747</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          EBITDA     y_hat     yhat1\n",
              "EBITDA  1.000000  0.965706  0.965462\n",
              "y_hat   0.965706  1.000000  0.999747\n",
              "yhat1   0.965462  0.999747  1.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S-3p72UwJ-UB",
        "outputId": "f0005971-2b29-44d7-b837-a3e0bd1a6ad0"
      },
      "source": [
        "pearson_coef, p_value = stats.pearsonr(df1['EBITDA'], df1['yhat1'])\n",
        "print(\"The Pearson Correlation Coefficient is\", pearson_coef, \" with a P-value of P =\", p_value) "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The Pearson Correlation Coefficient is 0.9654615209218957  with a P-value of P = 6.361590210357176e-38\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HwG9VUJcKIgM",
        "outputId": "756e6ad2-b58d-4c90-9946-c5358fc2e1ed"
      },
      "source": [
        "pearson_coef, p_value = stats.pearsonr(df1['EBITDA'], df1['y_hat'])\n",
        "print(\"The Pearson Correlation Coefficient is\", pearson_coef, \" with a P-value of P =\", p_value) "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The Pearson Correlation Coefficient is 0.9657058167762496  with a P-value of P = 5.123510784551663e-38\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_I4btfAUENp1",
        "outputId": "d099f7ae-3cf7-4611-b860-d6d4c5c724f9"
      },
      "source": [
        "pearson_coef, p_value = stats.pearsonr(df1['EBITDA'], df1['COS  (gross)'])\n",
        "print(\"The Pearson Correlation Coefficient is\", pearson_coef, \" with a P-value of P =\", p_value) "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The Pearson Correlation Coefficient is 0.861965589788533  with a P-value of P = 5.955456811437811e-20\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mMf2hq_AH5Li",
        "outputId": "876f9a82-bd86-4ac0-c02c-b3460fe5a112"
      },
      "source": [
        "pearson_coef, p_value = stats.pearsonr(df1['EBITDA'], df1['OpExp'])\n",
        "print(\"The Pearson Correlation Coefficient is\", pearson_coef, \" with a P-value of P =\", p_value) "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The Pearson Correlation Coefficient is 0.2387527246525752  with a P-value of P = 0.0574392393300312\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Vo9TX6prFn_Z"
      },
      "source": [
        "<p>What is this P-value? The P-value is the probability value that the correlation between these two variables is statistically significant. Normally, we choose a significance level of 0.05, which means that we are 95% confident that the correlation between the variables is significant.</p>\n",
        "\n",
        "By convention, when the\n",
        "<ul>\n",
        "    <li>p-value is $<$ 0.001: we say there is strong evidence that the correlation is significant.</li>\n",
        "    <li>the p-value is $<$ 0.05: there is moderate evidence that the correlation is significant.</li>\n",
        "    <li>the p-value is $<$ 0.1: there is weak evidence that the correlation is significant.</li>\n",
        "    <li>the p-value is $>$ 0.1: there is no evidence that the correlation is significant.</li>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q9_5bE0XLG6O"
      },
      "source": [
        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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "AT9icPzf6zyG",
        "outputId": "972eebef-8e45-43ad-d0b7-ba3f710ecc66"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['EBITDA'], x=df1['COS  (gross)'], order=3).set(title= 'CosGross vs EBITDA')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "7G1_JDRE9OlC",
        "outputId": "ec752ca3-7375-4eed-eb6a-0787186c2e60"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['yhat1'], x=df1['COS  (gross)'], order=1).set(title= 'Prediccion vs EBITDA')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "4oLP_2cO8eM2",
        "outputId": "e5143030-ee43-461b-97c2-9ea5a95435ac"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['EBITDA'], x=df1['F&B'], order=1).set(title= 'F&B vs EBITDA')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "mz3_rgJ59ZEA",
        "outputId": "b96c7b1e-93b2-4eca-8024-06a6e9cf05cd"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['yhat1'], x=df1['F&B'], order=1).set(title= 'Regresión vs F&B')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "LE695Pt581N5",
        "outputId": "8f3e7d04-b796-4b3d-8606-c126ea0dd93e"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['EBITDA'], x=df1['Hotel'], order=1).set(title= 'Hotel vs EBITDA')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JPKOUKlNKLbePfVRr3QuglHoUuE4p9SRQorV+xm7/IXAL8PAE1xBCXOAyDVv9w89emtZcjdtpEIxak++GAaZp/XIY5GRxQSgSpz8Y5fRQiIIlGfcFA2AwGOWnz3Xy44OdDIZiqfZir4uKQjcel7XqbKocBhR63RR7Xfg8GbeMmdBczcks1VonSxCcApbaX9cA7WnHddhtE7V3ZGif6BoTSiQStLS0TPIxFrZQKCTPugjJs05PhdekbySAL23yOxRLUO53TXiNmmInhhlnJGISTZi4HQaGAW4HhEKjcyCGadLaHZ7U/RqGQcJwMBROMByKkkgkCEciHDt27Lxj+4JxHjs2xG9PjBCOWb0WA/C7Dcp8TtxOAxIxhgIJSn3OjOfIdH2Py0mRz43fBSEzwdnJZHNmMOcT//b8yfTuPg/XcDgcrF+/Pp+3M2+0tLTIsy5C8qzT8zdGJZ/Z+zIJh5GaqzGcJn9z3WWsn6D3kXxfaeHo+zr6gpQXuvH5RpMYA5EYq6t9We83FI0zFLRKwPhMqLLbjx07xpo1a1LHdfQF2NPczqOvnE4NiRV6nNx81QpWVRZy3x9P4HQYeNwOQtEEhtPkz9+4ljUZljQnGYDX5aS4wEWh24VjCgsCDhw4kLF9roLMaaXUcq11lz0clhyo7ATq0o6rtds6GR36SrY/abfXZjh+omsIIcR5prvEONP7br5yBQ8d7JxSTkx6cJmo0/Dq6SF2NbXz1JEzqXmZ8gI3791Uy01XraDIa32sF/vc7Glu59RgcMKcGbCHxDxWpYDpDIlNZK6CzF7gTuCL9u8/S2v/mFJqD9Yk/4AdJH4N/FPaZP87gE9rrXuVUoNKqauBZ4H3A9/Icg0hhMhoukuMM71vQ23ZpAJWOBZnMBhjODx+cDFNE302zLefe4HmE6OLZJeV+LijoZbrLluG131ucMi0H8xYLodBkc9Fsc+NexKT+NMxG0uYd2P1QpYopTqwVol9EXhAKfVB4DXgdvvwfVjLl49iLWH+cwA7mHwOaLaPuzu5CAD4KKNLmB+2fzHBNYQQC1wyn6W1e4DV1QNTWh48W3XLsgWsyQSXhGnyTGsPu55t55WuwVT7qiWF7Gis482qeso5LgbgcTko8bkp9E5tSGw6DHOakzmL1aFDh8yNGzfO9W3MChm7X5wW+7OmZ9gb8Qim00M0bnL3TZdlDRbp700fxprMe3NlMsElFk/wG32G3U1tnOgZXd126fISdm6t4+rVlTgmWIKcTMTsGgyy3B4q27qmwkqc9Loo8Oa+f3HgwIEDmzdv3jK2fc4n/oUQYirSa4+FQlH8U1gePJm6Zfnq6URiCQaC0XGDS1NrL7ua2jjeM0I4miASH81tbFhZzptqXVzfuD5rfktTay/3PPEqLoeVVBqNx/nxoU5WlPm4Vs3+VgcSZIQQC8pMao9le28+KjRH4wkGAlGGJui5PKXP8JVHjzASiZFIO2ZDTSl/+eY1rF1azLFjxyaVQLmnuZ0Ct5PqEh9+j4NwNMHZ4TD3/rZVgowQQmQzk5L52d6bywrNsXiy5xJLldEfq3ckwo8OdnB/c3squBhAic+F3+PEYRisXVo86WsaBphGgrqKAkKxOGeHIpiA2+nI2b41UyVBRgixoKTXHjNMk0AkNumS+dnK7eeiQnM8YTIYjDAYGj+4dA0Eub+5g4df6krluBgGlPnclBVYK71MTE4NBjO+fyynw6DQ66LY56Lc76W9L5C3fWumSoKMEGJBSc9Lae0Os7raN+l5k2y5MDPpJSUSJkOhKAPBKLFxgsvxsyPsbmrjicPdqZ5Lic9FgceFwyCV4wIQiiZYVuIf93oGVg+lxO+i0OtOrTL7wOtX5m3fmumQICOEWHCSy4Ons5JuoqXF09lYzDRNhkMx+oORVK9krJc6B9jV1MYzrb2ptqoiL7dtqeVPNiznxfYB7nniVYLROD47Qz+WMNneUHfeuQwDCtxWef0Cj/O8eZp87FszExJkhBDCNtUPaGtPlxjh2PmFK03TpPlEH7ua2nihYyDVXl9RwPaGOt66vjqVANm4uoJPsHbCDH23y0WJ3yqv73NPnJWfy31rZkqCjBBCpJnMB3QwEqM/ECUUPb/kfjxh8tSRM+xuaufomeFUu1pazI6tdVxz8ZKMOS7jZei7nQYlPjeRYhdLirzTeqa5JEFGCCEmKRSNMxiMMhKOnRdcIrEEj7xymvub2+nsH52w31hfxs7GejbVl016DxcD8HtcFPmcFNr725xMZN4Bc76TICOEEFmEY3EGA5mLVwYiMX7+fBcPHeigZ8TagdIArlm7hO0NdaxfXjLp66RvZ5xtSGyhkCAjhBDjmKgETH8gwk8OdfLT504yZG8S5nQYvG19Ndsb6riosnDS1xlnO+NFQYKMEEKMEYrGGQplDi6nB0M8uL+DX77YRThmDWF5XQ7edcVybt9Sy9ISX4Yzni+5nXGR30WRPSS2GEmQEUII20R7urT1BNjd3MZjLd2pJMsir4tbNq7gPRtrKCvwTOoaM93OeKGRICOEuOBNFFwOnxpkd1M7v3/1bGqyv7LQw62ba7nxyuXnJG5OxOUwKPa5KMrj3i3zkQQZIcSiMpUqyuPNuZimyaG2fnY1tXGwrT/VvqLMx/aGOt5x6TI8ruyBIrWdsd9FoSf/e7fMRxJkhBDTMlubf031niZTRXm84JIwTX5/9Cy7m9rRp4ZS7WuqCtnZWM+1l1RNapOwfG5nvNBIkBFCTFk+SuLnQrYqyuNN6EfjCR5r6eb+5nbaekeLYV5RU8rOrXU0rqyY1MT8hTokNhEJMkKIKctlSfxcylRFuczvJhyNcWYwfN6cSzAaZ9+LXTy4v4PuoXCq/erVFexsrOfymtKs15QhsYlJkBFCTFkuSuLnQ5HHydEzw8QTJiU+F6sqC3E6DAzDyVA4mjpuMBjlZ8+d5EcHOxi0c1wcBrxlnZXjsrqqKOu1kkNiRT4n/klO/l+I5E9GCDFlMymJny9PHu6mZySCy2FQVeTBaRgcOT2E0+ngk+9cB8DZ4TAP7u/gFy90EYxaRS3dToPrLl/GHVvqWFE2fmn9JJfDoMjnosjrntTk/4VOgowQYsqmUxI/3+77w3FWVRWSSJgcPzvCQDCKwzCoLfZRU+7nK48c4ZFXTqXK8Rd4nNx05Qpu3VxLReHEOS4G4HE5KfG5KPTKkNhUSJARQkzZfNuzJBJL2NscJwhGElQWeqks9BKKxjjZH+TO/2hKbRJWXuDmvZtquenKFRT5Jv4ITO7dUuxzUeCVj8vpkD81IcS0TFQSf7aWNxsOJz3DYYZCURIJ6B2J4nM5CEYT9AYiBCKj+7wsLfFyx5Y6rr98Gd4sxSfTtzP2ui7sJcgzJUFGCJFTs7G8ORpPMBiMcmooiidoTejfsaWWLz+iOT0YJxIfLYu/tNjLX1yzijerqqzFJ5N7txQuwkKVc0WCjBAip/K5vDkSSzAYijIcipIwIRqLEU+Y/EZ3s6epnb7A6AqyAo+TWzfV8v7XX5Rxk7CkZKHK5BLkyRaqnI/JqPORBBkhRE7lY3lzpiTKcDTOk8eHeeI3TXQNhFLHbrmonJ1b67mytnTCgJEqVDmNvVvmazLqfCRBRgiRU9Nd3jy2Z/DRbWtoWFnBYCjKSCSWCi7D4Rh77RyXZM/FAK69pIodjXVcsrR4wuvkIit/viajzkcSZIQQOTWd5c3pPYOaUh9g8pVHNH+69SI2rywHoHckwo8OdrD3uZOM2BP6TgPeedky7mioo65i/CCW66z8+ZqMOh9JkBFC5NR0ljd/+6lWygtcVBb5CEbiDAYjDIZi/PezbdSU+7m/uZ2HXz5FxN4kzOd2cOOGFTQsibPl8kvGPa9hQFEesvLnYzLqfCVBRgiRcxMtbx7LNE2i8QQ+l5NT/UFidkKLYcDh04P82feeTeW4lPhcvHtjDbdsrKHU7+bYsWMZz5nvrPz5mIw6X0mQEULMiUTCZCQcoz8YIWHCqcFQ6gO7dySSGhIDWFLk4fYtdfzJhuX4x5mkt7LyHaklyJMdEptoldh4r21bV82tHf189/fHGYnEKfQ4+dA1q2Q+JgMJMkKIWRVPmAyFogwGo6ley62bavjnRzTdQ2HCsdEcl6oiLx94w0retr563En6gyf6eKTlFD0jEcr8Ht539UWT/rCfaJUYMOFrDx3spKrYS70dGB862MmG2jIJNGNIkBFCzIpY3MpxGQpZuS1gBZzfvXqGXU3t9KbluPjdTt6zsYYPvGHluJuEOQw4FTD56eE2QrEEBnAiMDKlpcQTrRIDpvWaBJlzSZARQuRVpuASiSV49JXT3L+/nY6+YOrYjfVl7GysZ1N92Tk5Lk2tvexpbqd7KMSa6iLuvPoi3rSump++3Ed/5NwP+7PDIT6+5xAlfnfWJMmJVomZMK3XxLkkyAgh8iIaTzA0JrgEI3F+/sJJHjzQQc9wJHXsGy6uZGdjPeuXl5x3nqbWXv7tyaNUFLpRy4oZCEb4wsOHcTkddAxEqCoZXdE1FIpydiiCCdRXFGRNksy2Smy6r4lRcxpklFIngCEgDsS01luUUhXA/cBK4ARwu9a6TyllAPcA7wICwAe01gft89wJ/IN92s9rrX9gt28Gvg/4gX3AJ7TWafviCSFyLVn6ZSQ8GlwGAlF+cqiTnzzXyZC9SZjTYfDWddVsb6xjZWVhxnMZwCOvnKauwo9pWrkyCdMaKvvWU60sLXIxEo2nPuzPDIXBAK/TgWEYWYexsq0Sm+5rYtR86Mm8WWt9Nu37TwGPa62/qJT6lP39J4HrgbX2r63AvcBWOyj9I7AFMIEDSqm9Wus++5gPA89iBZnrgIdn57GEuLBkKv3SPRjigQMd7Huhi5A9oe91OXjXFcu5bUsty0p8Gc9lAF63kxK/i66BIC6HYa1ptiWHpj68qZTvHhpKfdiHYnEchsGSIu95x2aSLadnuq+JUfMhyIx1M7DN/voHwJNYQeZm4Id2T+QZpVSZUmq5feyjWuteAKXUo8B1SqkngRKt9TN2+w+BW5AgI0ROhSLx80q/tPUE2N3cxmMt3aneTKHXyS1X1fCeTTWUF2TeJMwwoNBjldhPJk+WFXjGHZpqqC2kvq4+9WFf6HFR4HFSkjZfkm0Ya2xOz5OHu9nx7WeyFr6cSi7QhWyug4wJPKKUMoFvaa2/DSzVWnfZr58Cltpf1wDtae/tsNsmau/I0D6hRCJBS0vLNB5l4QmFQvKsi9BsPKthGERxMByKE4jESCSsXsqJvggPHxniUFeQ5Lh0qdfB2y8u5tqVhfjdCXq72ukdcz63y0WRz0mBy0GYBD3m6Kj29atcfPPZMJFIGK/TIBw3icbh+g1FhEIhlvp6+MwbS4FSmjtG+OazPfQPj5x37GT+TJLvdzvB5zTo6BngUw8d4qNbK2mozTykN1sW6s/wXAeZa7TWnUqpauBRpdTh9Be11qYdgGaNw+Fg/fr1s3nJOdPS0iLPugjl81lN02Q4HGMwGCUSS1Botx1q62dXUxsH2/pTx64o87G9oY53XLps3Kx7t9Og2OemaIL9W9avh/q67tGhqcrR3sXYZ53o2Mm4+3fPUOj3pnpNfiAQifHw8Rjvf/vc/vzM95/hAwcOZGyf0yCjte60f+9WSv0EaAROK6WWa6277OGwbvvwTqAu7e21dlsno8NryfYn7fbaDMcLIaYonjAZDkUZDEWJxq3/9yVMkz8c7WF3UxuHTw2ljl1TVciOxnredEnVuDkuHqeDUv/kM/OnMjQ1k2EsKXyZe3MWZJRShYBDaz1kf/0OrLm0vcCdwBft339mv2Uv8DGl1B6sif8BOxD9GvgnpVS5fdw7gE9rrXuVUoNKqauxJv7fD3xjtp5PiMUg00qxWDzBYy3d7Glup6139MP3ipoSdjTWs3VVRcZ9XJKVkEsKprY52GySwpe5N+0go5Rq0Fo3z+DaS4GfKKWS97FLa/0rpVQz8IBS6oPAa8Dt9vH7sJYvH8VawvznAHYw+RyQvJe7k4sAgI8yuoT5YWTSX4isntJWADk1GMLncnLTlStoXF1BKBpn34tdPLC/g+6hcOr4q1dXsKOhnitqSzOezwD8HhclPhcF3rkeoZ+YFL7MvaMiyBAAACAASURBVCn9jSulLgV22L/6sZYNT4vWuhW4MkN7D/DWDO0m8JfjnOs+4L4M7fuBy6d7j0JcaH6ru7nniVcZCcVImCZnomG+9vgRNhwuo+lELwNBq/SLw4BtqpodjXWsqSrKeC4DKwO/1O/G55nazpNzZTrbFIiJZQ0ySqmVjAaWKHARsEVrfSKvdyaEmBWmaRKIWDku3/zNMc4MhvG7ncTj1iR/fyDKo4OnAWui/rrLl3HHljpWlPkzns8AfG4nZQXunO7hMltkaXJuTfgToJR6GigB9gDv1Vq/qpQ6LgFGiIVv7EoxEzjRO4LP5eD0YIjBUCy1DNkA7mio472baqhMS3RMlwwupX73vB8WE7Mn20/CaazckqVAFfAqIGVZhFjA4gmTkXCUgeDoSjGAY93DhKMJTg+Ozrc4DYMir5Myv5vDXUN8bPchlpf42d5QR+PqCkCCi5jYhD8RWutblFKlwHuAzyql1gJlSqlGrXXTrNyhECInkgUrh0Ox1D4uAC909LOrqZ2m46Mpkk6HQUWBtatkIBJnMBwjgbUzZc9ImHueeJW/NtbyxkuqJLiICWX9ydBaDwD/AfyHnTR5B/A1pVS91rpu4ncLIeZaKBpn2K4plowtpmnyTGsvu5vaeOnkYOrYiyoL2LqyAn1qiNNDIaqKfHZuTCK1I2WJz4XX7eCpV89ye2P9XDySWEAm/d8PpVQVYGqtvwF8Qyl1Uf5uSwgxU8FIjMFgjEB0tKZYPGHyG93N7qZ2jp8dSR27fnkxOxvred2aShxj8ld2fOcZSnwuPC4rgdLjcjASjvF8Rz9CZJNt4t/AqnD8McBpt8WAb2it757ovUKI2WeaJlGcnOwPEo7GUxOokViCh186xQP72+kaCKWO33JROTsa67iqrmzc5MiVFYXEzQTFPrc1dDYcIRCJSYKimJRsPZm/Bt4ANGitjwMopVYD9yql/lpr/bV836AQIrtEwmQkHGMgGKV7METRkjgAI+EYe58/yUMHOuiztzc2gDdesoSdjfVcsrR43HMaQKHXxUffvIZ/evgwfYGoJCiKKcsWZN4HvD19vxetdatS6s+ARwAJMkLMoXjCtHefHF0pZpomfYEIPzrQwc+eP8lI2Ao4LofBOy5dyh0NddRVjN8LSQaXEr8bn9tJdYkP05QERTE92YKMe8yGYgBorc8opdyZ3iCEyL9MWxsDnBoIsev5Pv7wi5NE7E3CfG4HN2xYzm2b66gqzpzjAqN7uZT4zs/QlwRFMV3Zgkxkmq8JIfIgHIszFDx3pRjA8bMj7Glu5/GW06n2Ep+Ld2+s4ZaNNZSOqSzc1Npr1ycLsqa6iDuvvgif28l9fzjB0TPDE27WJcRUZAsyVyqlBjO0G0DmfVOFEDmXafdJgFdODrKrqY0/HutJtZX5nOy4eiU3XLEcf4aaYU2tvXzjN69S5ndTX1HAa2dH+F97niNhmiwp8lBZ6KV7KMRn9r7M3bBoA82Th619Z7LtgClmJluQ8Wmto7NyJ0KIc5imyUgkxlAwRihtpZhpmux/rY/dTW081z6QOr623MrEX+0dYd0ltZlPCux7qYuLKgsIhGO8fHKQWMJMlZXpGY7idTntlWQxvvVU66L84H3ycDef2fsybqdBmd99QQTVuZItyDwLbJqNGxFCWBIJk+FwlMFgjEg8kWqPJ0x+9+pZdje18Wr3cKp9bXURjSsreKlzgP985jXKPCZ/7qpIlX1JcjsNSv1uekbCOA2DY2dGiCVMHIYxWqPMgDNDYYp97kW9Wde3nmrF7TRS+8YUeFyLOqjOpWxBZv7tKiTEJIwdCrl+lYt5vHMtYG0GlixYmV72JRJL8Ogrp7l/fzsdfcFU+1V1ZexorCMRN/n6b47ichiU+FwMBELc88SrfIK1NK6uSAWXIq8bh8OgxOeheyhEJJ5I7VyZ/IduGKQC22LerEt2wJw92YJMlVLqb8Z7UWv91RzfjxAzlmko5JvPhqmv656X/0sNx6wy++m7TwIEI3F+8cJJHjzQwdnh0XU2b1hTyZW1ZfzxWA9fffQIw6EYfreD4kJr5ZjX5cBwONj3UhdVxR72NLejTw9RU2bNOyQ35nIaBomEiYEVXAzDIJ4wcTsMApHYos6FkR0wZ48jy+tOoAgoHueXEPNO+lCIYVi/u51W+3wSjMToHgxxsj/IYDCaCjADwSjf/8MJtn/nGe79bStnhyM47RyX+z6whRs3rOAnz3XSMxKmxOciGI3TH4wyHI7hchiUF3hYVVXIyb4An//lYVrPjlDiG513ALj7pstYtaSQuAmGA+rK/VQVeXAYBgVeF9XFPu6+6bJ5GZRz4a5rVxONmwQiMXs/ncUdVOdStp5Ml5SPEQtNpqEQr9OY1FBIvlccJfdwGQrGCMfi5+yb0T0Y4oEDHex7oYuQnePidTl41xXLuW1LLctKrAWdX3/MGhpLFqz0uhyAicthsKzMT//gMB19AbqHI1QVezPOO+z+yNVsW1edet6OvgCrlhTxxQtkhZXsgDl7ZE5GLDqZhkLCcZPayomHQvK54ihTZn5SW2+A+5vbefSV06m5mEKvk1uuquE9m2ooL/Ccc3zXYJASn/VsLofB2uoihkMx+oNRzgyG6B+JYDg9eFyOVCBKGjvvcCEnWV7Izz6bsgWZdyilKsZ7UWvdO95rQsyV5JxDIBJLq7VF1qGQfKw4isQSDIfPz8wHOHJ6iF3PtvG7V8+mejQVhR5u3VTDjVeuoHCcPVqWl/jpD0SoLvVQ5HUTCMfo6AswEIozcGoIn8vgrmtreLq1d07nHSQPRUD2INOEtRNmph6NCcgAppgXxn6g3brJ+pBNDoVcv6Eo6wdcLlcchSLWZP5wJHpO8qRpmjzXbm0SduC1vlT78lIfdzTUcd1ly/C4Jp4q/cDrL2JXUzuRWJyzkRDdQ2EGQnGqi61EyoGRAA8d7OTWTTU8dLBzTLCdnXkHyUMRSdl2xlw1WzcixHRl+kB76GDnORPXLS0tWc8z0xVH4yVPAiRMkz8e7WFXUxuHTw2l2ldXFbKjoZ5tqiq1nHg8TnuJ8o1XWUNo/27PJwQiVoBZUmTN2fhcDhIOg6dbe7n7psvmZN5B8lBEUtZNy5RSLiCutTaVUnXAVuCo1vq5vN+dEJOQqw+0zMNs2f/nn15mPz15EqzclycOd7O7uZ3XekZ7RFfUlLCjsZ6tqyrG3cclyTCg2OumtMCN22n1ct60rpo32c92zZeeOKcHNhyOMxiJc8K+3tjAMhvDWJKHIpKybVr2YeBLwLBS6nPA3wIHgY1Kqfu01l+ahXsUYkK5+kCb6oqjZCXk4VDsnORJsLY83veitUlY91A41X716gp2NNRzRW1p1vtJltwvLXDjdZ1fgywpvQc2GIxyJhDHMAy8TuO8YarZGsaSPBSRlK0n81fAGqycmBbgIq31WaVUAdCMFYCEmFO5/ECbzIqjUDSZPHluJWSAoVCUnz13kh8f7KQ/aJX9cxiwTVWzo7GONVVFWe/BAHxuJ+UFnvNK7meS3gM7OxzGBBwYVJf4zuvVzdYw1nR7hWLxyVrqX2vdB/QppY4m95bRWgeUUlLqX8wLs/WBNhKOMRSKEYzEGBNb6BkO89CBDn7+QheBiLVJmNtpcN1ly7i9oY6aMv+kruFzOSktcI+7siyT9B7YiZ4AbgOWlfko9lm9u/Re3WwNY0keikjK9pPsV0ptxKoM4LG/NpBS/2IeyecHWnK+ZTAUTVUqTtfZH+SB5nZ+9fKpVP5LgcfJTVeu4L2baqgsGn+TsHQep4PSQjdFdpWCqUr2wHZ8+xk6egZSAQbO7dXN5jCW5KEIyB5kTgFfzfB18nsh5oVcf6CNV6wy6Vj3MLua2vjtkTOpIbNSv5v3bqrhlqtqeOXkIF/45WG6BoMsL7FK8I+tigzYcyMeinzTCy5j3XXtaj710KFxe3UyjCVmW7YlzNtm6T6EmJR8r4war1hl0gsd/exuaufZ46N5yNXFXm7fUse7rliGz+2kqbWXe554NVUVuWckfE5VZLAy9Uv9bop9VmXkXNm2rpq3rSlkrx5hJBKn0OPkQ9esSv0ZyTCWmG3ZVpf9H631l+2vb9NaP5j22j9prf8u3zcoRFI+V0aNlzwJVv7Ls8d72fVsGy+dHN0o9qKKAnY01vGWddW4nKMJlHua28+pLZbsMexpbufqNRUU+9yU+t3nvCdXnjzczWPHRqgq9lJvX/ehg51sqC07J9BIUBGzJdtw2Xbgy/bXnwYeTHvtOkCCjJg1uV4ZZVXfjY87mR9PmDypz7C7uY3WMyOp9nXLitnZWM/rL67EkWGIK722WFJFoRunA1aUFeBxOfLWI7P+jJAkSDFvTKVA5th/TVI8U8yqXK2MiidMRuydJ6Px8yfzI7EEv3r5FPc3t9M1EEq1b64vY8fWejbWlU04f7K8xE/PSBi/24nP7aC80EMwGsfncqYCTL56ZO19AXzOc+9NkiDFXMoWZMxxvs70vRB5NZOVUYZhTFisEqwlyj9//iQPHeykd8RaoW8Ab7xkCTsa6lHLJreF0vaGOv79qWOU+F0UeVycGQozFI5z902X8eThbj6+5xAjkRg+l5OqYi/FPnfOeht15QV09AyQvmBakiDFXMoWZK5USg1i/Vvz21+DLGEWc2C6K6NC0TiDEejsD5w33wLQF4jw44Od/PS5TkbCVo6Ly2Hw9kuXckdDHfUVk/+ANoA3qSqWl/r4/tMnONo9TG15AX/7TuserfuP43IYxBImJ/tDrCiDIq8rJ72NbKvLhJht2VaXZU83nueUUtcB92Dt8vldrfUX5/iWxDRNdWVUevLkQCDMkjEB5tRAiAf2t7PvpVNE7E3CfC4HN1y5nNs211FVPLkclySvy0FpgZsir5vlZf5UbbGkHd9+BrfTwOtyEIubOBwGCUzODIVxOoyc9Da2ravmo1srefh4TFaPiXlh8mnFC5BSygn8G/B2oANoVkrt1Vq/Mrd3JqYr28qo9GKVmeZbAI6fHWFPczuPt5xO5bgU+1y8e2MN795YQ+mYeZ+xmlp72dPcTtdgkNqyAt5/dT1vWb80a65Lck5pSZGXkwNBSACGSSiWyGlvo6G2kPe/fX1OziXETC3qIAM0YlWMbgVQSu0BbgYkyCwy4VicYTu/JVPyJMArJwfZ1dTGH4/1pNoqizzcvrmWGzaswD+JOmHJHBiv00F9eQFul8F3fn+c0gJP1t5Cck6pxA5iZ4fDhGMmhR7XOdsSTEWmVWpLp3wWIfJnsQeZGqA97fsOrK0KxCKQXII8HIoRiMYyzreYpsn+1/q47/dn0Gc7Uu215VYW/tvWL826SVi6B/a3s6TIQ1WRl1AswUg4RjAan9SkffqcUrHPhctpEI2bMwowmVapfWhjMeulIyPmicUeZKYskUhMaoOrxSAUCi24ZzUMAxODSMJgKBwjHImRyBBdEqbJwZNBHj4yRNtANNVeX+rm+kuK2bTCj8MI0P7a8Ulf2+N2kTBjeEjQ2RNOXdcwTVq7w1n/LJcCH9pYzEMvD3B6MMzSIhe3bihlqdlDS0vPhO/N5Ku/PokZj+EwHITDURyAGU/wwIt9NNQurL/X6VqIP8PTtVCfdbEHmU6gLu37WrttXA6Hg/UXyH8DW1paFtSzppd88SZMMi0ojsYTPPrKafY0t9PRF0y1qyVe/uJNl7DlovIp1whzGKSy9L9zsJmuwSAF3tHFlYFIjNXVvkn9Wa5fD+9/+5QuP67evV2UFRac8zxe0+TMYGBB/b3OxEL7GZ6J+f6sBw4cyNi+2INMM7BWKbUKK7hsB3bO7S2JqQpGrFViI5HMQ2LWMXF+8cJJHjzQwdnh0V0oXr+mkp2N9XiDZ1iz8vwClRMxDDhyaoifHDqJPj3IshI/r1tdwUMHA+csER4IRvE4HVzzpSfyttNkJuPlDS0tWuz/rMVCsqh/GrXWMaXUx4BfYy1hvk9r/fIc35aYhGRW/lAolrHEftJAMMpPDnXy00OdDIZigNXzeOv6pWxvqGPVkkIAjh07M+lrG1jlWPSpQf75kSOYpjU53z0U4qGDndy6qYanW3vp6AtQ6HFiAJF4Iq87TWYyXt7QrRuy77opxGxZ1EEGQGu9D9g31/chJie5Smx4nCrISWeGwjx4oJ1fvNBFKGrluHhcDq6/fBl3bKljWenUc4WTO1KWFbjxe1z81f3PYZrmeXXAnm7tZfdHrgas3Jdo4vxjZqNW2Hh5Q0vNqc/vCJEviz7IiIUhELYCy0RDYgDtvQHub27nkVdOp5YqF3qc3HzVCt6zqZaKQs+0rp+eSJm6lp3XMhSKcmYoTCSewO0wGAhGzzsm3WzWCsuUNzSdRQRC5IsEGTFnRnedjBGJxScshnfk9BC7mtr43ZGzqePKC9zcurmWG69cQdEUtitON9GmYXXlBZzoGaZnOIphgNNhEE2YDIViPHm4m23rqmd1p0khFiIJMmLWJQtVDofGT5wEK8fl+Y4Bdj3bxv7X+lLty0t93L6ljusuW4rXPb3KR05707CSCTYNu+va1dz1XwcwMXFgYFqjcpQXuFPDYQthp8l8b/QmxEQkyIhZM5lVYmDluPzxaA+7m9to6RpKta9eUsiOxjq2qWqc09xNMn05crZNw7atq6bI6yQUTRCJJ/A4HSwp8lHsGy1mOd93mszntgJCTIYEGZFXiYTJSCTGYDD7kFgsnuCJw93sbm7ntZ7ROY3LVpTwp1vr2bqqYso5LklOhyMVXKaS4X/J0pLzhsMCkdg5w2FzsdPkZHsnud7oTYipkiAj8iIaTzAcspYgTzQkBlYp/odfOsUD+9s5PRhOtW9dVcGOxjo21JZN+z4MwO9xsbTEO+WqyjD97QXyaSq9k7lemCCEBBmRU6FInKFwjJFwlCyxheFQjJ8+18mPD3bSb6/Ychjwpkuq2NlYz5rqohndi9dlLUcu9LroOxmf1jnm43DYVHonsjBBzDUJMmLGkkNiQ8EY4SxDYgA9w2F+dLCTvc+fJBCxPvzdToN3XmbluNSU+7OcYWIuh0FZgZtin3vaw2vp5mI4bCJT6Z3Mx56YuLBIkBHTFosnGJrkkBjAyf4g9+9v51cvnSIat473u53ceOVybt1cy5KiqQ9npUtO6pcVeKa9MGAhmErvZD72xMSFRYKMmLJQNJmVn31IDODYmWF2N7XzpO5OHV/qd/OeTTXcctUKin0TbxKWjWFAkcdNacHUJvUXqqn2TuZbT0xcWCTIiEkL2NsZj7d3y1gvdgywu7mNZ1p7U23VxV5u31LHu65Yhm+aOS5JyUn9sgL3jM+1kEjvRCwkEmTEhJKFKgeDsXG3M05nmibPHu9ld1MbL3YOptovqihge2Mdb11XnTU/ZTI8TgflhR4Kp5npv9BJ70QsFBfmv1CRVSgat2qJZSlUmRRPmDypz7C7uY3WMyOpdrWsmJ2N9bzh4kocOZiEz/WkvhAivyTIiJREwmQkGmM4GCMUzb5KDKwSMb9++RR7mtvpGgil2jfXl7Fjaz0b68pyEgycDoMSn4sS/+Ke1BdisZEgIyZdSyzdSDjGz1/o4kcHOugZsTYJM4A3rl3CjsZ61LJM+1ZOnZFWBsadg2E2IcTskiBzAYvjpHswlLWWWLr+QIQfHezkZ8+dZDhsbRLmdBi83d4krL4yN0l+BlDkdVNS4MLrunAm9YVYbCTIXGDSJ/JPD4YoWBKb1PtODYZ4cH8H+17sIhyzyhH7XA7+ZMNybttcS3XJ1DcJyyS1YszvxueR4CLEQidB5gKRaSI/MYnuy4meEfY0tfP44e7U+4p9Lt59VQ3v3lhDacHMclzS+VxOSu0yMEKIxUH+NY/x6tkwd37213zomlV8/G2XzPXtzMg5E/mx+KSHxABaugbZ1dTGH46O7rJYWejhti213LBh+TnZ5jPlcSZ3pTx/4zAhxMImQWYMw7BKdNzzxFGABRlowjErI38kPPmJfLByXA681seupnaea+9PtdeW+7ljSx1vv3RpTjPqZTmyEIufBJkMXA4HsUSC7/7++IIJMqZpFakcDsUJTjIjPymeMPnD0bPsamrjyOnhVPvF1UXsbKzjjWurcrpsOLkrZbHPLcuRhVjkJMiMw2HASGR65eFnUyyeYDgcYygUTRWdnPR7EyYPv9jFnuZ22vuCqfYra0vZubWeLReV57SH4XQYFPtclPiy70ophFgcJMiMI2FC4Txe3ZQsUjkSmVxGfrpgNM4vX+hi97On6AuOBtLXr6lkR2Mdl60ozem9Goa1HHmqu1IKIRY+CTIZxBIJEiZ86JpVc30r50gOiQ1NISM/3WAwmtokbDBkLV12GPBWO8dl1ZLCnN7vhVrAUggxSoLMGKZp7XEyn1aXzWRIDODMUJiHDnTw8xdOEopaOS4el4M31Pn58FsvZ1lpbnJc0nldDsoKLtwClkIIi3wCjLF2iZcXPvvOub4NYGZDYgDtvQHub27nkVdOp1aZFXqc3HzVCt6zqZa+U+05DzAuh0F5gYcinyxHFkJIkJl3ZjokBnDk9BC7m9p56siZ1PvLC9y8d1MtN121giK7d9GXs7sendQvlQKWQog0EmTmiZkOiZmmyfMdA+x6to39r42Gj+WlPm7fUsd1ly3Fm4d5EZnUF0JMRILMHJvpkFjCNHn6WA+7m9p4pWso1b56SSHbG+t4s6rOS89CJvWFEJMhQWYOmKbJcGRq+7aMFYsneEKfYU9TGyd6Aqn2y1aUsLOxnqtXV+RtTsTrclImNcaEEJMgnxKzaKZDYgDhaJyHXzrF/fvbOT0YTrU3rixnx9Z6NtSU5i24uJ0GZX6Z1BdCTJ4EmVkQisYZCsUYCUeZxogYAMOhGHufP8mPDnbQF4gCVo7Lmy6pYntDHWuX5maTsExkV0ohxHRJkMmTXAyJAfSORKwcl+dPpsrcuJ0G77h0Gdsb6qgp9+fupscwDCj2uiktkF0phRDTI0Emx6LxBCMzHBIDONkf5P797fzqpVOp8/jdTm68cjm3bq5lSZE3V7d8HpnUF0LkigSZMY73hfnyt5/hrmtXs21d9aTfF7QrII9Epj8kBtB6ZpjdTe38RnenzlPqd/OeTTXcctUKin252yQsE5nUF0Lk0px8kiilPgt8GDhjN/2d1nqf/dqngQ8CceDjWutf2+3XAfcATuC7Wusv2u2rgD1AJXAAeJ/WOqKU8gI/BDYDPcAdWusT2e7NaRh0DwX5zN6XuRsmDDTJrYyHQjEiscS0h8QAXuocYFdTG8+09qbaqou93L6lluuvWI4/zz0KmdQXQuTDXP539Wta6/+X3qCUuhTYDlwGrAAeU0olC4j9G/B2oANoVkrt1Vq/AnzJPtcepdS/YwWoe+3f+7TWFyulttvH3TGZGyvwuAhEYnzrqdaMQSa5KdhweHq5LUmmafLs8V52N7XxYudgqr2+ooDtDXW8dX113udCZFJfCJFP821M5GZgj9Y6DBxXSh0FGu3XjmqtWwGUUnuAm5VSLcBbgJ32MT8APosVZG62vwZ4CPhXpZShtZ5UVPC7nXT0Bc5pC4StwDISmdqmYGPFEya/PXKG3U1tHDszkmpXy4rZ2VjPGy6uxJHn3oRhQHmhlxVlfpnUF0LkzVwGmY8ppd4P7Af+t9a6D6gBnkk7psNuA2gf074Va4isX2sdy3B8TfI9WuuYUmrAPv5sthsLhYKEYgmqity0HNZEEgZD4RjhSIzEDKJLNG7ydPsIv3p1iDMjo/u4rK/ycv0lxaxb4sUwBjjeOjDta2TjcBgU+TwUex244iGOHtF5u9Z8EgqFaGlpmevbmBXyrIvTQn3WvAUZpdRjwLIML/09Vk/jc4Bp//4V4C/ydS9T5fX6KCl0cNe1ayioKsabMJlJFkogEuPnz3fx0IEOekYigLWC65q1S9jRWMe6ZSU5ue9svC4n5QVuCuxJ/ZaWFtavXz8r155r8qyLkzzr/HHgwIGM7XkLMlrrt03mOKXUd4Bf2N92AnVpL9fabYzT3gOUKaVcdm8m/fjkuTqUUi6g1D5+Qg6HwfJSH++8dBkXLy2a0ZxLfyDCjw918tNDJxkOW50tp8Pgbeur2dFQT31lwbTPPRUyqS+EmCtztbpsuda6y/723cBL9td7gV1Kqa9iTfyvBZqw/uO/1l5J1om1OGCn1tpUSv0GuBVrhdmdwM/SznUn8LT9+hOTmY9ZUezm0+9aO6PnOz0Y4sH9HfzyxS7CMWuTMK/LwZ9sWM7tm2upLsn9JmGZJCf1S/0eHDKpL4SYA3M1J/NlpdRVWMNlJ4C7ALTWLyulHgBeAWLAX2qt4wBKqY8Bv8Zawnyf1vpl+1yfBPYopT4PHAK+Z7d/D/hPe/FAL1ZgyqvXekbY09zOYy3dqR5QkdfFezbW8O6NNZQW5DfHJUky9YUQ88WcBBmt9fsmeO0LwBcytO8D9mVob2V0BVp6ewi4bWZ3OjktXYPsbmrnD0fPpnJlKgs93Lq5lhuvXE6BZ3b+mA2s5delkqkvhJgn5tsS5gXDNE0OtvWzq6mNQ239qfYVZT62N9TxjkuXzeomXj47U79AMvWFEPOIfCJNUcI0+f3Rs+x+th19enSTsIuritjRWMe1l1TNalKjx+mgtNBNsXd2huKEEGIqJMhMUjSe4LGWbvY0tdHeF0y1b6gtZWdjPQ0ry2d15ZbLYVBW4KbY55YVY0KIeUuCzBgnh6J87v7n2d5QR+PqCoLROPte7OKB5g7ODI9uEva61ZXsaKzj8prSWb0/hwHFPjdlBVIGRggx/0mQGcNhQM9ImK89doQraktpOt7LYCiWeu0t66rZ3lDH6qqiWb0vAyiyV4zN5lyPEELMhASZMUzT2oWyPxjlsZZuwEpmfNfly7m9oZblpfnbJCwTA/C5nZQXePB5ZMWYEGJhkSAzRiCSoC9obW9sANsb63jvploqCj2zfi8yqS+Esum6YAAAB/BJREFUWOgkyIxhYu0pU+RzUl9eyIffuHrW78HlMCj1W5P6kqkvhFjIJMiM4XMZLCv1kjDhT7fWz+q1DQNKfG5K/W5ckqkvhFgEJMiM4XAYVBX5UqvLZoMBFHqtTH2vS+ZdhBCLhwSZMVYUu/nqHZfO2vV8LiflhW78s1R6RgghZpN8ss0Rt9NBmUzqCyEWOQkys8xpT+qXyKS+EOICIEFmlhjJTH2Z1BdCXEAkyOSZTOoLIS5kEmTySCb1hRAXOvn0ywOZ1BdCCIsEmRxyOgzKJFNfCCFSJMjkgEzqCyFEZhJkZkAm9YUQYmISZKbJ73ZSViCT+kIIMRH5hJwiKb8vhBCTJ0FmkqT8vhBCTJ0EmSyk/L4QQkyfBJlxyKS+EELMnASZDGRSXwghckM+RcdwGLC8zD/XtyGEEIuCTDIIIYTIGwkyQggh8kaCjBBCiLyRICOEECJvJMgIIYTIGwkyQggh8kaCjBBCiLyRICOEECJvJMgIIYTIG8M0zbm+h3nlwIEDZ4DX5vo+hBBigblo8+bNVWMbJcgIIYTIGxkuE0IIkTcSZIQQQuSNBBkhhBB5I0FGCCFE3kiQEUIIkTcSZIQQQuSN7IxpU0pdB9wDOIHvaq2/OMe3NClKqTrgh8BSwAS+rbW+RylVAdwPrAROALdrrfuUUgbWc74LCAAf0FoftM91J/AP9qk/r7X+gd2+Gfg+4Af2AZ/QWs/Z2nellBPYD3RqrW9QSq0C9gCVwAHgfVrriFLKi/VnsxnoAe7QWp+wz/Fp4INAHPi41vrXdvu8+TlQSpUB3wUux/q7/QtAswj/XpVSfw18COs5XwT+HFjOIvl7VUrdB9wAdGutL7fb8v5vdLxr5PlxzyE9GVIfWv8GXA9cCuxQSl06t3c1aTHgf2utLwWuBv7SvvdPAY9rrdcCj9vfg/WMa+1fHwHuhf+/vbsNsaKK4zj+TS1RK7WMKDdQSn5BL9QQtYQKDRMClbIQJB8SISqzFz1QBEb1oiKyR4VIaxVJbBOSnkQqKAgtyh4w+9OikStago9FZJa9OGf1tnnXNZm5d2+/Dyz3zpm5O+fMf3b+c8/Mnjm6wy8ExgCjgYWSBubPLAHmVXxuUgnt6swCYEvF9BPAooi4BNhLOsiQX/fm8kV5OfL2mQ5cRmrLYkk963A/eBZ4LyIuBYaT2txwcZU0GLgLGJUPwD1J8WmkuL7Kv7dvGbGsto7SOMkko4HWiNgaEYdIZ09TalynLomIne1nORFxkHQgGkyqf3NerBmYmt9PAZZHxJGI2AAMkHQBcB2wPiL25DOd9cCkPO/siNiQz3KXV/yu0klqAq4nneGTz/rGAy15kY5tbd8GLcCEvPwUYFVE/B4R24BW0j5QN/uBpP7AVcBSgIg4FBH7aNC4knpV+kjqBfQFdtJAcY2Ij4A9HYrLiGW1dZTGSSYZDGyvmG7LZd2KpCHASGAjcH5E7MyzdpG606B6WzsrbztOea08A9wH/JWnzwX2RcThPF1Zv6NtyvP35+VPdhvUwlBgN/CKpE2SXpbUjwaMa0TsAJ4CfiQll/2k7rFGjGulMmJZbR2lcZJpEJLOBN4A7o6IA5Xz8tlNtx8/SFJ7n/bnta5LCXoBlwNLImIk8CsdujoaKK4DSWfcQ4ELgX7Uvku2VGXEslb7i5NMsgO4qGK6KZd1C5JOJyWYlRGxJhf/lL9Gk19/zuXV2tpZedNxymthHDBZ0g+kLo/xpOsWA3I3C/yzfkfblOf3J10oPtltUAttQFtEbMzTLaSk04hxvRbYFhG7I+IPYA0p1o0Y10plxLLaOkrjJJN8BgyTNFTSGaSLh2trXKcuyX3RS4EtEfF0xay1wKz8fhbwZkX5TEmnSRoL7M9fp9cBEyUNzGeWE4F1ed4BSWPzumZW/K5SRcQDEdEUEUNIMfogImYAHwLT8mId29q+Dabl5Y/k8umSeuc704YBn1JH+0FE7AK2S1IumgB8SwPGldRNNlZS31yX9rY2XFw7KCOW1dZRGt/CTOrXlXQnKYg9gWURsbnG1eqqccAtwDeSvsxlDwKPA6slzSU9uuDmPO8d0q2RraTbI+cARMQeSY+S/iABHomI9guVt3Ps9sh38089uR9YJekxYBP5Ynl+XSGplXTRdTpARGyWtJp0IDsM3BERfwLU2X4wH1iZD4xbSbHqQYPFNSI2SmoBviDFYxPwEvA2DRJXSa8B1wCDJLWR7hIr42+02jpK46H+zcysMO4uMzOzwjjJmJlZYZxkzMysME4yZmZWGCcZMzMrjJOMWY1I+qXD9GxJL5zgM1O7MrijpIcl3XOqdTQ7VU4yZt3LVNJIwmbdgv8Z06wO5cFOlwGDSANlziENFzIZuFrSQ8CNefEXgfNI/7g3LyK+K73CZlU4yZjVTp+KURoAzuHYcCfPA80R0SzpVuC5iJgqaS3wVkS0AEh6H7gtIr6XNAZYTBrTzawuOMmY1c5vETGifULSbGBUnrwCuCG/XwE82fHDeeTtK4HXjw1xRu+iKmv2XzjJmHVfPUjPXBlxwiXNasQX/s3q0yfkgR+BGcDH+f1B4CyA/NygbZJugjQit6ThZVfUrDNOMmb1aT4wR9LXpFG2F+TyVcC9+WmZF5MS0FxJXwGb6SaPDbf/D4/CbGZmhfE3GTMzK4yTjJmZFcZJxszMCuMkY2ZmhXGSMTOzwjjJmJlZYZxkzMysMH8DcHN/Umnnkf0AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "rQ_C2QRa9E9q",
        "outputId": "e4b5fbad-3508-429d-8eb6-ef798cd032bc"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['yhat1'], x=df1['Hotel'], order=1).set(title= 'Hotel vs Regreción')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "7cX1TRAVSyIC",
        "outputId": "8946248d-52c6-4a26-d075-e8d545ed7c82"
      },
      "source": [
        "sns.regplot(data= df1, y=df1['EBITDA'], x=df1['yhat1'], order=1).set(title= 'Hotel vs Regreción')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WahJ5uXpAB-K",
        "outputId": "1e6dd063-19c0-4577-f69f-24b58061ce3c"
      },
      "source": [
        "x = (df1['EBITDA'] - df1['yhat1'])\n",
        "x.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dates_\n",
              "2016-01-01    12515.141355\n",
              "2016-02-01     1204.841839\n",
              "2016-03-01     2446.321999\n",
              "2016-04-01      128.951293\n",
              "2016-05-01    -5663.805029\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VpM_sxsGAm-G"
      },
      "source": [
        "z = x / df1['EBITDA']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kwRJuI8oBlxz",
        "outputId": "f1fa720a-2013-4033-b117-713a9e5d82c1"
      },
      "source": [
        "z.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dates_\n",
              "2016-01-01    0.123732\n",
              "2016-02-01    0.018486\n",
              "2016-03-01    0.032947\n",
              "2016-04-01    0.002465\n",
              "2016-05-01   -0.205754\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 116
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6LeGom3mCrxY",
        "outputId": "443d0603-1568-4de5-a795-ee209696ec55"
      },
      "source": [
        "dif_por = abs(z)\n",
        "dif_por"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dates_\n",
              "2016-01-01    0.123732\n",
              "2016-02-01    0.018486\n",
              "2016-03-01    0.032947\n",
              "2016-04-01    0.002465\n",
              "2016-05-01    0.205754\n",
              "                ...   \n",
              "2020-12-01    0.004448\n",
              "2021-01-01    0.097560\n",
              "2021-02-01    0.194469\n",
              "2021-03-01    0.169670\n",
              "2021-04-01    0.176712\n",
              "Length: 64, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "uPO7IwDhDJSu",
        "outputId": "efddecf7-e6bf-4ab7-b253-dcc0faf9d0b2"
      },
      "source": [
        "plt.figure(figsize=(10,7))\n",
        "plt.title('Regression vs. EBITDA')\n",
        "\n",
        "plt.xlabel('Años')\n",
        "plt.ylabel('Porcentaje%')\n",
        "plt.plot(dif_por, 'b.-', label='Diferencia Porcentual')\n",
        "\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B6RXl6WIHTCW",
        "outputId": "cee7eaba-b5a6-4728-f1d6-f607ef05c456"
      },
      "source": [
        "x2 = (df1['EBITDA'] - df1['y_hat'])\n",
        "x2.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dates_\n",
              "2016-01-01    10541.695714\n",
              "2016-02-01    -1551.526936\n",
              "2016-03-01      361.525091\n",
              "2016-04-01     -675.750847\n",
              "2016-05-01    -7359.427618\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "id": "HigE87A-GxRV",
        "outputId": "f639fcb1-ba20-469d-de2f-864a4a618620"
      },
      "source": [
        "df1.head()"
      ],
      "execution_count": null,
      "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>Hotel</th>\n",
              "      <th>Food</th>\n",
              "      <th>Beverage</th>\n",
              "      <th>F&amp;B</th>\n",
              "      <th>Spa</th>\n",
              "      <th>REVENUE</th>\n",
              "      <th>COS  (gross)</th>\n",
              "      <th>OpExp</th>\n",
              "      <th>FixExp</th>\n",
              "      <th>Op+Fix_Exp</th>\n",
              "      <th>CorpExp</th>\n",
              "      <th>EBITDA</th>\n",
              "      <th>Date</th>\n",
              "      <th>y_hat</th>\n",
              "      <th>yhat1</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dates_</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>92261.180204</td>\n",
              "      <td>75081.284922</td>\n",
              "      <td>60255.705116</td>\n",
              "      <td>135336.99000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>227598.1702</td>\n",
              "      <td>35498.871005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>90952.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>101147.511981</td>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>90605.816266</td>\n",
              "      <td>88632.370626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>71652.459665</td>\n",
              "      <td>67013.831684</td>\n",
              "      <td>51465.260916</td>\n",
              "      <td>118479.09260</td>\n",
              "      <td>0.0</td>\n",
              "      <td>190131.5523</td>\n",
              "      <td>32004.993231</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>92950.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>65176.852916</td>\n",
              "      <td>2016-02-01</td>\n",
              "      <td>66728.379852</td>\n",
              "      <td>63972.011076</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-03-01</th>\n",
              "      <td>82218.545266</td>\n",
              "      <td>68057.925466</td>\n",
              "      <td>54043.365802</td>\n",
              "      <td>122101.29130</td>\n",
              "      <td>0.0</td>\n",
              "      <td>204319.8365</td>\n",
              "      <td>33577.743298</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96491.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>74251.048211</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>73889.523120</td>\n",
              "      <td>71804.726212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-01</th>\n",
              "      <td>82267.407633</td>\n",
              "      <td>49679.356863</td>\n",
              "      <td>45048.526943</td>\n",
              "      <td>94727.88381</td>\n",
              "      <td>0.0</td>\n",
              "      <td>176995.2914</td>\n",
              "      <td>27772.245171</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96904.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52318.700007</td>\n",
              "      <td>2016-04-01</td>\n",
              "      <td>52994.450854</td>\n",
              "      <td>52189.748714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-05-01</th>\n",
              "      <td>64418.259843</td>\n",
              "      <td>46240.111203</td>\n",
              "      <td>39537.548435</td>\n",
              "      <td>85777.65964</td>\n",
              "      <td>0.0</td>\n",
              "      <td>150195.9195</td>\n",
              "      <td>27132.957779</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>95536.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27527.099200</td>\n",
              "      <td>2016-05-01</td>\n",
              "      <td>34886.526818</td>\n",
              "      <td>33190.904229</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Hotel          Food  ...         y_hat         yhat1\n",
              "Dates_                                  ...                            \n",
              "2016-01-01  92261.180204  75081.284922  ...  90605.816266  88632.370626\n",
              "2016-02-01  71652.459665  67013.831684  ...  66728.379852  63972.011076\n",
              "2016-03-01  82218.545266  68057.925466  ...  73889.523120  71804.726212\n",
              "2016-04-01  82267.407633  49679.356863  ...  52994.450854  52189.748714\n",
              "2016-05-01  64418.259843  46240.111203  ...  34886.526818  33190.904229\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3QtNyXxZHfCn",
        "outputId": "a6f0f4a6-9f02-4a09-d7c1-3ef65d324705"
      },
      "source": [
        "z2 = x2 / df1['EBITDA']\n",
        "z2.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dates_\n",
              "2016-01-01    0.104221\n",
              "2016-02-01   -0.023805\n",
              "2016-03-01    0.004869\n",
              "2016-04-01   -0.012916\n",
              "2016-05-01   -0.267352\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2MmiduPhILXU",
        "outputId": "ab75efa8-8ea8-4222-b103-e4b0e1efb18a"
      },
      "source": [
        "dif_por2_m = abs(z2).mean()\n",
        "dif_por2_m"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.4874733994342581"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D9biqi2aIgl-",
        "outputId": "b73d5994-78da-47ef-d98e-38b77880456d"
      },
      "source": [
        "dif_por2 = abs(z2)\n",
        "dif_por2.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dates_\n",
              "2016-01-01    0.104221\n",
              "2016-02-01    0.023805\n",
              "2016-03-01    0.004869\n",
              "2016-04-01    0.012916\n",
              "2016-05-01    0.267352\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "p9yLXKDmIXZ4",
        "outputId": "17b0731b-f4c9-4584-9183-6bdac2fc85e7"
      },
      "source": [
        "plt.figure(figsize=(10,7))\n",
        "plt.title('Regression vs. EBITDA')\n",
        "\n",
        "plt.xlabel('Años')\n",
        "plt.ylabel('Porcentaje%')\n",
        "plt.plot(dif_por2, 'b.-', label='Diferencia Porcentual')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "2oQg1u0TD3Sq",
        "outputId": "eb29cd1d-3c11-4829-bb61-e2e76b1b79a1"
      },
      "source": [
        "sns.boxplot(data=dif_por).set(title= 'Distribucion de la diferencia')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "4jTQOtW1E5kE",
        "outputId": "5b56fc10-79cb-4b6c-f8de-3caf7d102355"
      },
      "source": [
        "sns.residplot(data=df1, x=df1['yhat1'], y=df1['EBITDA']).set(title='Grafica de Residuos')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wi7C7b7XEgwE"
      },
      "source": [
        "df1.to_csv('yhat2.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "GgMXBuY-f99i",
        "outputId": "b602ca02-d7dd-47bf-d3f4-ca75b3045b0a"
      },
      "source": [
        "df2 = pd.DataFrame({'Hotel':[85294,76389,55188,65221,94307,110816],'f&b':[77363,64721,68724,90414,124203,182225],'CossGross':[33878,29774,29349,35200,45981,62472]})\n",
        "df2"
      ],
      "execution_count": null,
      "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>Hotel</th>\n",
              "      <th>f&amp;b</th>\n",
              "      <th>CossGross</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>85294</td>\n",
              "      <td>77363</td>\n",
              "      <td>33878</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>76389</td>\n",
              "      <td>64721</td>\n",
              "      <td>29774</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>55188</td>\n",
              "      <td>68724</td>\n",
              "      <td>29349</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>65221</td>\n",
              "      <td>90414</td>\n",
              "      <td>35200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>94307</td>\n",
              "      <td>124203</td>\n",
              "      <td>45981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>110816</td>\n",
              "      <td>182225</td>\n",
              "      <td>62472</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Hotel     f&b  CossGross\n",
              "0   85294   77363      33878\n",
              "1   76389   64721      29774\n",
              "2   55188   68724      29349\n",
              "3   65221   90414      35200\n",
              "4   94307  124203      45981\n",
              "5  110816  182225      62472"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FRp86bWtoA9K",
        "outputId": "86f58094-ee0f-4f6c-fc32-aeda99618602"
      },
      "source": [
        "df2.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(6, 3)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JtmY0j_5hypu",
        "outputId": "276531f9-8c06-4e4c-9006-424094bb4234"
      },
      "source": [
        "oct = df2.loc[0,['Hotel','f&b','CossGross']]\n",
        "oct = np.asarray(oct)\n",
        "oct"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([85294, 77363, 33878])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GEX3p5LCjaXi",
        "outputId": "82d0c6e3-415b-43e1-8f26-96c4200c420d"
      },
      "source": [
        "oct.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PPWmKOPQj577",
        "outputId": "5d829cb4-11c8-4859-cde8-8bfb59333a44"
      },
      "source": [
        "oct = oct.reshape(1,3)\n",
        "oct"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[85294, 77363, 33878]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dpTHYUjTl5lG",
        "outputId": "f7f4a9dc-c9d1-4e0e-f966-a0a91822ca6f"
      },
      "source": [
        "lr.predict(oct)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([27589.75552187])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5zOcWxEaknRW",
        "outputId": "10016b9c-b408-43dc-82df-6146bc05c3dd"
      },
      "source": [
        "nov = df2.loc[1,['Hotel','f&b','CossGross']]\n",
        "nov = np.asarray(nov)\n",
        "nov"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([76389, 64721, 29774])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OH1Z-5TVk4EW",
        "outputId": "929dbfe1-c17c-401f-86b8-e4814f1d107e"
      },
      "source": [
        "nov = nov.reshape(1,3)\n",
        "nov"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[76389, 64721, 29774]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5Hh-aN6UhpBC",
        "outputId": "8bd3f441-5635-4ce6-c40b-5f86d9fbf428"
      },
      "source": [
        "lr.predict(nov)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([15169.3032628])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7a_tPS9nlRvr",
        "outputId": "c147448f-9910-4616-8cbf-ea45b821a838"
      },
      "source": [
        "dic = df2.loc[2,['Hotel','f&b','CossGross']]\n",
        "dic = np.asarray(dic)\n",
        "dic"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([55188, 68724, 29349])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hboDjeTtlhB2",
        "outputId": "1f72ff81-5b52-4052-d625-bc31e1879248"
      },
      "source": [
        "dic = dic.reshape(1,3)\n",
        "dic"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[55188, 68724, 29349]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aqOk7winlna8",
        "outputId": "a3aebc3e-f49d-4bd1-a108-be6b515f99c6"
      },
      "source": [
        "pred_df2 = lr.predict(df2)\n",
        "pred_df2"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 27589.75552187,  15169.3032628 ,   7055.88902388,  26896.1812982 ,\n",
              "        63553.06541728, 109191.14333739])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "z0pcJmwUosdK",
        "outputId": "22f624b8-151d-4c3e-9dfe-b5e86f31a88b"
      },
      "source": [
        "plt.figure(figsize=(10,7))\n",
        "plt.title('Predicciónes')\n",
        "\n",
        "plt.xlabel('Meses')\n",
        "plt.ylabel('US Dollar')\n",
        "plt.plot(pred_df2, 'b.-', label='Predicción')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}