From f56e953b394c3d0d36a25dcd1fd0f7bf5d645b78 Mon Sep 17 00:00:00 2001
From: Samuel Vasco Gonzalez <65866495+samuVG@users.noreply.github.com>
Date: Mon, 13 Jun 2022 22:36:58 -0500
Subject: [PATCH] Homework 1

---
 .../1152223665/homework_01/Homework1.ipynb    | 712 ++++++++++++++++++
 1 file changed, 712 insertions(+)
 create mode 100644 EXTRAS/homeworks_to_submit/1152223665/homework_01/Homework1.ipynb

diff --git a/EXTRAS/homeworks_to_submit/1152223665/homework_01/Homework1.ipynb b/EXTRAS/homeworks_to_submit/1152223665/homework_01/Homework1.ipynb
new file mode 100644
index 0000000..a2ec34b
--- /dev/null
+++ b/EXTRAS/homeworks_to_submit/1152223665/homework_01/Homework1.ipynb
@@ -0,0 +1,712 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Homework1.ipynb",
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# **Samuel Vasco Vasco González**  Cc. 1152223665"
+      ],
+      "metadata": {
+        "id": "tLr2S-IBR7xg"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd"
+      ],
+      "metadata": {
+        "id": "7MMk8hm4cZDH"
+      },
+      "execution_count": 1,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### Descarga del libro Adventures of Huckleberry Finn, by Mark Twain (en formato TXT)"
+      ],
+      "metadata": {
+        "id": "1k91-0GyH7t5"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "CEqc89mtKY5p"
+      },
+      "outputs": [],
+      "source": [
+        "from urllib.request import urlopen\n",
+        "contents = urlopen(\"https://www.gutenberg.org/files/76/76-0.txt\").read().decode('utf-8')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### **a)** Analisis del libro contando la aparición de tres nombres de personajes principales: Jim, Tom, Huck a través de los capítulos del libro."
+      ],
+      "metadata": {
+        "id": "hRGDQWcPJHzX"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "chapter = [\"CHAPTER I.\",\"CHAPTER II.\",\"CHAPTER III.\",\"CHAPTER IV.\",\"CHAPTER V.\",\"CHAPTER VI.\",\"CHAPTER VII.\",\"CHAPTER VIII.\",\n",
+        "             \"CHAPTER IX.\",\"CHAPTER X.\",\"CHAPTER XI.\",\"CHAPTER XII.\",\"CHAPTER XIII.\",\"CHAPTER XIV.\",\"CHAPTER XV.\",\"CHAPTER XVI.\",\n",
+        "             \"CHAPTER XVII.\",\"CHAPTER XVIII.\",\"CHAPTER XIX.\",\"CHAPTER XX.\",\"CHAPTER XXI.\",\"CHAPTER XXII.\",\"CHAPTER XXIII.\",\n",
+        "             \"CHAPTER XXIV.\",\"CHAPTER XXV.\",\"CHAPTER XXVI.\",\"CHAPTER XXVII.\",\"CHAPTER XXVIII.\",\"CHAPTER XXIX.\",\"CHAPTER XXX.\",\n",
+        "             \"CHAPTER XXXI.\",\"CHAPTER XXXII.\",\"CHAPTER XXXIII.\",\"CHAPTER XXXIV.\",\"CHAPTER XXXV.\",\"CHAPTER XXXVI.\",\n",
+        "             \"CHAPTER XXXVII.\",\"CHAPTER XXXVIII.\",\"CHAPTER XXXIX.\",\"CHAPTER XL.\",\"CHAPTER XLI.\",\"CHAPTER XLII.\",\"CHAPTER THE LAST\",\n",
+        "           \"THE END. YOURS TRULY, _HUCK FINN_.\"]\n",
+        "\n",
+        "Chapters=[]\n",
+        "Characters=[\"Tom\",\"Jim\",\"Huck\"]\n",
+        "\n",
+        "for i in range(len(chapter)-1):\n",
+        "  Chapters.append(contents[contents.find(chapter[i])+1+contents[contents.find(chapter[i])+1:].find(chapter[i]) : \n",
+        "                           contents.find(chapter[i+1])+1+contents[contents.find(chapter[i+1])+1:].find(chapter[i+1])])"
+      ],
+      "metadata": {
+        "id": "5mQS9B4uK7G3"
+      },
+      "execution_count": 3,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### **b)** Resultados en formato Pandas DataFrame"
+      ],
+      "metadata": {
+        "id": "MLlPwz2vyrTF"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "Matrix = np.zeros((3,len(chapter)-1))\n",
+        "\n",
+        "for i in range(Matrix.shape[0]):\n",
+        "  for j in range(Matrix.shape[1]):\n",
+        "    Matrix[i,j] = Chapters[j].count(Characters[i])\n",
+        "\n",
+        "df = pd. DataFrame (data = Matrix, index = [\"Tom\", \"Jim\",\"Huck\"], columns = chapter[:-1])\n",
+        "df"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 271
+        },
+        "id": "EqWljhwZwMRm",
+        "outputId": "ba9a0ef2-83c2-4d26-e6e7-a6171f901b78"
+      },
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "      CHAPTER I.  CHAPTER II.  CHAPTER III.  CHAPTER IV.  CHAPTER V.  \\\n",
+              "Tom          6.0         24.0           5.0          0.0         0.0   \n",
+              "Jim          0.0         16.0           0.0          8.0         0.0   \n",
+              "Huck         3.0          2.0           2.0          1.0         0.0   \n",
+              "\n",
+              "      CHAPTER VI.  CHAPTER VII.  CHAPTER VIII.  CHAPTER IX.  CHAPTER X.  ...  \\\n",
+              "Tom           0.0           2.0            2.0          0.0         0.0  ...   \n",
+              "Jim           0.0           0.0           22.0         11.0        19.0  ...   \n",
+              "Huck          2.0           0.0            5.0          1.0         0.0  ...   \n",
+              "\n",
+              "      CHAPTER XXXIV.  CHAPTER XXXV.  CHAPTER XXXVI.  CHAPTER XXXVII.  \\\n",
+              "Tom             15.0           14.0            18.0              9.0   \n",
+              "Jim             17.0           18.0            23.0              4.0   \n",
+              "Huck             4.0            8.0             1.0              0.0   \n",
+              "\n",
+              "      CHAPTER XXXVIII.  CHAPTER XXXIX.  CHAPTER XL.  CHAPTER XLI.  \\\n",
+              "Tom               32.0            11.0         11.0           8.0   \n",
+              "Jim               27.0            10.0         13.0           0.0   \n",
+              "Huck               2.0             0.0          3.0           0.0   \n",
+              "\n",
+              "      CHAPTER XLII.  CHAPTER THE LAST  \n",
+              "Tom            30.0               6.0  \n",
+              "Jim            12.0               6.0  \n",
+              "Huck            2.0               3.0  \n",
+              "\n",
+              "[3 rows x 43 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-d5dafd07-f0bf-4f6f-a1c2-760c48abfcba\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <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>CHAPTER I.</th>\n",
+              "      <th>CHAPTER II.</th>\n",
+              "      <th>CHAPTER III.</th>\n",
+              "      <th>CHAPTER IV.</th>\n",
+              "      <th>CHAPTER V.</th>\n",
+              "      <th>CHAPTER VI.</th>\n",
+              "      <th>CHAPTER VII.</th>\n",
+              "      <th>CHAPTER VIII.</th>\n",
+              "      <th>CHAPTER IX.</th>\n",
+              "      <th>CHAPTER X.</th>\n",
+              "      <th>...</th>\n",
+              "      <th>CHAPTER XXXIV.</th>\n",
+              "      <th>CHAPTER XXXV.</th>\n",
+              "      <th>CHAPTER XXXVI.</th>\n",
+              "      <th>CHAPTER XXXVII.</th>\n",
+              "      <th>CHAPTER XXXVIII.</th>\n",
+              "      <th>CHAPTER XXXIX.</th>\n",
+              "      <th>CHAPTER XL.</th>\n",
+              "      <th>CHAPTER XLI.</th>\n",
+              "      <th>CHAPTER XLII.</th>\n",
+              "      <th>CHAPTER THE LAST</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Tom</th>\n",
+              "      <td>6.0</td>\n",
+              "      <td>24.0</td>\n",
+              "      <td>5.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>15.0</td>\n",
+              "      <td>14.0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>9.0</td>\n",
+              "      <td>32.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>30.0</td>\n",
+              "      <td>6.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Jim</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>17.0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>23.0</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>27.0</td>\n",
+              "      <td>10.0</td>\n",
+              "      <td>13.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>12.0</td>\n",
+              "      <td>6.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Huck</th>\n",
+              "      <td>3.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>5.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>3.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>3 rows × 43 columns</p>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d5dafd07-f0bf-4f6f-a1c2-760c48abfcba')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-d5dafd07-f0bf-4f6f-a1c2-760c48abfcba button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-d5dafd07-f0bf-4f6f-a1c2-760c48abfcba');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 4
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### **c)** Exportamos la tabla a un archivo CSV."
+      ],
+      "metadata": {
+        "id": "lMZQxz4M5ksw"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.to_csv(\"Data.csv\")"
+      ],
+      "metadata": {
+        "id": "lYmsH3ygXDDe"
+      },
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### **d)** Importamos el archivo CSV guardado usando Pandas y hacemos un gráfico de la ocurrencia acumulada (cumsum) de los caracteres."
+      ],
+      "metadata": {
+        "id": "LbEEi2PU50Kn"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "data=pd.read_csv(\"/content/Data.csv\",index_col='Unnamed: 0')\n",
+        "data"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 271
+        },
+        "id": "iCzteGRG58It",
+        "outputId": "a53d3af5-9c16-465c-a54b-adf579a809aa"
+      },
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "      CHAPTER I.  CHAPTER II.  CHAPTER III.  CHAPTER IV.  CHAPTER V.  \\\n",
+              "Tom          6.0         24.0           5.0          0.0         0.0   \n",
+              "Jim          0.0         16.0           0.0          8.0         0.0   \n",
+              "Huck         3.0          2.0           2.0          1.0         0.0   \n",
+              "\n",
+              "      CHAPTER VI.  CHAPTER VII.  CHAPTER VIII.  CHAPTER IX.  CHAPTER X.  ...  \\\n",
+              "Tom           0.0           2.0            2.0          0.0         0.0  ...   \n",
+              "Jim           0.0           0.0           22.0         11.0        19.0  ...   \n",
+              "Huck          2.0           0.0            5.0          1.0         0.0  ...   \n",
+              "\n",
+              "      CHAPTER XXXIV.  CHAPTER XXXV.  CHAPTER XXXVI.  CHAPTER XXXVII.  \\\n",
+              "Tom             15.0           14.0            18.0              9.0   \n",
+              "Jim             17.0           18.0            23.0              4.0   \n",
+              "Huck             4.0            8.0             1.0              0.0   \n",
+              "\n",
+              "      CHAPTER XXXVIII.  CHAPTER XXXIX.  CHAPTER XL.  CHAPTER XLI.  \\\n",
+              "Tom               32.0            11.0         11.0           8.0   \n",
+              "Jim               27.0            10.0         13.0           0.0   \n",
+              "Huck               2.0             0.0          3.0           0.0   \n",
+              "\n",
+              "      CHAPTER XLII.  CHAPTER THE LAST  \n",
+              "Tom            30.0               6.0  \n",
+              "Jim            12.0               6.0  \n",
+              "Huck            2.0               3.0  \n",
+              "\n",
+              "[3 rows x 43 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-da6fab08-f93e-4599-929e-3d0384044370\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
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+              "    .dataframe tbody tr th {\n",
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+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
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+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>CHAPTER I.</th>\n",
+              "      <th>CHAPTER II.</th>\n",
+              "      <th>CHAPTER III.</th>\n",
+              "      <th>CHAPTER IV.</th>\n",
+              "      <th>CHAPTER V.</th>\n",
+              "      <th>CHAPTER VI.</th>\n",
+              "      <th>CHAPTER VII.</th>\n",
+              "      <th>CHAPTER VIII.</th>\n",
+              "      <th>CHAPTER IX.</th>\n",
+              "      <th>CHAPTER X.</th>\n",
+              "      <th>...</th>\n",
+              "      <th>CHAPTER XXXIV.</th>\n",
+              "      <th>CHAPTER XXXV.</th>\n",
+              "      <th>CHAPTER XXXVI.</th>\n",
+              "      <th>CHAPTER XXXVII.</th>\n",
+              "      <th>CHAPTER XXXVIII.</th>\n",
+              "      <th>CHAPTER XXXIX.</th>\n",
+              "      <th>CHAPTER XL.</th>\n",
+              "      <th>CHAPTER XLI.</th>\n",
+              "      <th>CHAPTER XLII.</th>\n",
+              "      <th>CHAPTER THE LAST</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Tom</th>\n",
+              "      <td>6.0</td>\n",
+              "      <td>24.0</td>\n",
+              "      <td>5.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>15.0</td>\n",
+              "      <td>14.0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>9.0</td>\n",
+              "      <td>32.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>30.0</td>\n",
+              "      <td>6.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Jim</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>17.0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>23.0</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>27.0</td>\n",
+              "      <td>10.0</td>\n",
+              "      <td>13.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>12.0</td>\n",
+              "      <td>6.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Huck</th>\n",
+              "      <td>3.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>5.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>3.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>3 rows × 43 columns</p>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-da6fab08-f93e-4599-929e-3d0384044370')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-da6fab08-f93e-4599-929e-3d0384044370 button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-da6fab08-f93e-4599-929e-3d0384044370');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 6
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "Tom = np.cumsum(data.iloc[0].to_numpy())\n",
+        "Jim = np.cumsum(data.iloc[1].to_numpy())\n",
+        "Huck = np.cumsum(data.iloc[2].to_numpy())\n",
+        "caps = np.arange(1,44)\n",
+        "\n",
+        "plt.figure(figsize=(10,6))\n",
+        "plt.plot(caps,Tom,\"ro-\",label=\"Tom\")\n",
+        "plt.plot(caps,Jim,\"ko-\",label=\"Jim\")\n",
+        "plt.plot(caps,Huck,\"bo-\",label=\"Huck\")\n",
+        "plt.xlabel(\"Chapters\")\n",
+        "plt.ylabel(\"Cumulative sum of appearances\")\n",
+        "plt.xticks(np.arange(0,45,2))\n",
+        "plt.grid()\n",
+        "plt.legend()\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 388
+        },
+        "id": "77sSeFaK6EWQ",
+        "outputId": "80cc5156-6994-4e42-d633-abd2e51595fb"
+      },
+      "execution_count": 24,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 720x432 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### **Análisis**\n",
+        "\n",
+        "* Sobre Jim, notamos que es el personaje que  tiene mayor suma total de apariciones a medida que aumentan los capítulos, apartir del capítulo 8 y hasta el final del libro. Por lo tanto, es el personaje principal y aquél sobre el que gira la trama del libro; podemos catalogarlo como un personaje de alto impacto respecto a los demás a partir del capítulo 8. Sin embargo, antes del capítulo 8 es un personaje de impacto medio respecto a los demás. \n",
+        "\n",
+        "* Sobre Tom, notamos que tiene un impacto en la historia poco pero constante hasta el capítulo 32, sin superar la suma de 50 apariciones a lo largo de estos capítulos. En los primeros 8 capítulos podemos catalogarlo como personaje de alto impacto, en los capítulos del 8 al 22 de impacto medio. Dado que la variación en la suma total de apariciones a partir del capítulo 18 hasta el 32 es constante, su aparición en estos capítulos es mínima y no aporta a la historia. Posterior al capítulo 32 la suma de apariciones totales de Tom aumentan linealmente, tomando un lugar considerable en la historia pero manteniendo su impacto medio.  \n",
+        "\n",
+        "* Sobre Huck, notamos que su impacto en la historia a través de todos los capítulos es bajo y con tendencia lineal plana al alza , es decir, pendiente positiva pero menor a uno. Cabe resaltar que a partir del capítulo 23 hasta el 32, las apariciones de Tom y Huck son igual de pobres, nulas, no aportan a la historia. "
+      ],
+      "metadata": {
+        "id": "cpc9kxSuLzCv"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        ""
+      ],
+      "metadata": {
+        "id": "JYXrUJagR5Qm"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file