davixcky/is_hw1.ipynb

## is_hw1.ipynb
{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "IS_HW1.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/davixcky/a9d1729af3e098a7b2ad8692297ff4a3/is_hw1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UvEzkU-64k9W",
        "colab_type": "text"
      },
      "source": [
        "# **Introducción a la Ingeniería de Sistemas**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DhIuksNiAtmU",
        "colab_type": "text"
      },
      "source": [
        "![unnamed.png](https://upload.wikimedia.org/wikipedia/commons/thumb/f/ff/Logo_uninorte_colombia.jpg/360px-Logo_uninorte_colombia.jpg)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q1dCRnET7JUK",
        "colab_type": "text"
      },
      "source": [
        "Profesor: Elías D. Niño-Ruiz, Ph.D."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JNRYWNXx6sye",
        "colab_type": "text"
      },
      "source": [
        "*   Nombre del Estudiante: David Orozco\n",
        "*   Código del Estudiante: 200152584"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "de09gPd_4TYz",
        "colab_type": "text"
      },
      "source": [
        "### ***Actividad 1 - Individual - DataFrame, Seaborn, PyPlot, y Agregación***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vzuhewTv5qiY",
        "colab_type": "text"
      },
      "source": [
        "En esta actividad, de manera individual, trabajarán sobre la base de datos de los accidentes registrados en la calle 30 de Barranquilla, Colombia. Como bien saben, la fuente de datos reposa en [Datos Abiertos](https://www.datos.gov.co/) , de manera especifica pueden consultar: [Accidentes de Tránsito Barranquilla Calle 30](https://www.datos.gov.co/Transporte/accidentes-calle-30-2015-2019/sefb-a755)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-90zLfj-8bnF",
        "colab_type": "text"
      },
      "source": [
        "Para nuestro análisis, procedemos a cargar las librerías de Python (**no olvide ejecutar TODAS las celdas de código**)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f6q5Iob77g2P",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZYf9ZNeY7d26",
        "colab_type": "text"
      },
      "source": [
        "Creamos el `DataFrame` con la base de datos alojada en el servidor de Datos Abiertos:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dk3VYRf34kBk",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_trans = pd.read_csv('https://www.datos.gov.co/api/views/yb9r-2dsi/rows.csv?accessType=DOWNLOAD');"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F8auYgO48I3_",
        "colab_type": "text"
      },
      "source": [
        "Los cincos primeros registros del DataFrame `df_trans` son:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4LXn52-B4St8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 326
        },
        "outputId": "433a9502-621a-4d1f-bd3a-b50ef8f88625"
      },
      "source": [
        "df_trans.head(5)"
      ],
      "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>FECHA_ACCIDENTE</th>\n",
              "      <th>AÑO_ACCIDENTE</th>\n",
              "      <th>MES_ACCIDENTE</th>\n",
              "      <th>DIA_ACCIDENTE</th>\n",
              "      <th>HORA_ACCIDENTE</th>\n",
              "      <th>GRAVEDAD_ACCIDENTE</th>\n",
              "      <th>CLASE_ACCIDENTE</th>\n",
              "      <th>SITIO_EXACTO_ACCIDENTE</th>\n",
              "      <th>CANT_HERIDOS_EN _SITIO_ACCIDENTE</th>\n",
              "      <th>CANT_MUERTOS_EN _SITIO_ACCIDENTE</th>\n",
              "      <th>CANTIDAD_ACCIDENTES</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>01/01/2015 12:00:00 AM</td>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>Jue</td>\n",
              "      <td>02:10:00:PM</td>\n",
              "      <td>Con heridos</td>\n",
              "      <td>Choque</td>\n",
              "      <td>VIA 40 CON 77</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>01/01/2015 12:00:00 AM</td>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>Jue</td>\n",
              "      <td>02:15:00:PM</td>\n",
              "      <td>Solo daños</td>\n",
              "      <td>Choque</td>\n",
              "      <td>CALLE 14 CR 13</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>01/01/2015 12:00:00 AM</td>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>Jue</td>\n",
              "      <td>02:20:00:PM</td>\n",
              "      <td>Solo daños</td>\n",
              "      <td>Choque</td>\n",
              "      <td>CL 74 CR 38C</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>01/01/2015 12:00:00 AM</td>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>Jue</td>\n",
              "      <td>03:30:00:PM</td>\n",
              "      <td>Con heridos</td>\n",
              "      <td>Choque</td>\n",
              "      <td>CL 45 CR 19</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>01/01/2015 12:00:00 AM</td>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>Jue</td>\n",
              "      <td>04:20:00:AM</td>\n",
              "      <td>Solo daños</td>\n",
              "      <td>Choque</td>\n",
              "      <td>CRA 15 CLLE 21</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          FECHA_ACCIDENTE  ...  CANTIDAD_ACCIDENTES\n",
              "0  01/01/2015 12:00:00 AM  ...                    1\n",
              "1  01/01/2015 12:00:00 AM  ...                    1\n",
              "2  01/01/2015 12:00:00 AM  ...                    1\n",
              "3  01/01/2015 12:00:00 AM  ...                    1\n",
              "4  01/01/2015 12:00:00 AM  ...                    1\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bb_rITOF-ZwU",
        "colab_type": "text"
      },
      "source": [
        "**Punto 1.** Elabore un gráfico de violin (`violinplot`) en donde se muestre el número de accidentes por día de la semana. ¿Qué conclusiones puede sacar con fundamento en el gráfico?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g6qvt9R4-4Rx",
        "colab_type": "text"
      },
      "source": [
        "**Respuesta.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Utl5k8QlDWG-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 280
        },
        "outputId": "6771673f-ba4c-4cf4-be46-d00854033d26"
      },
      "source": [
        "label_dia = ['Dom', 'Lun', 'Mar', 'Mié', 'Jue', 'Vie', 'Sáb']\n",
        "\n",
        "df_semana= df_trans.copy()\n",
        "sns.violinplot(data=df_semana,\n",
        "               x='DIA_ACCIDENTE',\n",
        "               y='CANTIDAD_ACCIDENTES',\n",
        "               order=label_dia);\n"
      ],
      "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": "markdown",
      "metadata": {
        "id": "yLwmGXx4-ZId",
        "colab_type": "text"
      },
      "source": [
        "El dia con mayor numero de accidentes (por dia) es el viernes"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2xfXLGk5_gyJ",
        "colab_type": "text"
      },
      "source": [
        "**Punto 2.** Elabore un gráfico de caja (`boxplot`) en donde se muestre el número de accidentes por la gravedad de este. ¿Qué puede concluir de la gráfica obtenida?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kWJkAH4R_0MG",
        "colab_type": "text"
      },
      "source": [
        "**Respuesta.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IheJ50nf_1WM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "dc2b1743-28c6-4015-8c0e-fcd1d89cd2d6"
      },
      "source": [
        "labels_stick = ['Solo daños', 'Con heridos', 'Con muertos']\n",
        "\n",
        "df_accidentes = df_trans.copy()\n",
        "sns.boxplot(data=df_accidentes,\n",
        "            x='GRAVEDAD_ACCIDENTE',\n",
        "            y='CANTIDAD_ACCIDENTES',\n",
        "            order=labels_stick)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f3062fa95c0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "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": "markdown",
      "metadata": {
        "id": "idoDH8XgDnBb",
        "colab_type": "text"
      },
      "source": [
        "La gravedad \"Con heridos\" y \"Con muertos\", son muy similares, en cambio \"Solo danos\", tiene un punto max de 2.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZOvVN5GUB41A",
        "colab_type": "text"
      },
      "source": [
        "**Punto 3.** ¿Cuántos accidentes ocurren por día de la semana? Exporte el resultado a un archivo de Excel. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cex6TLpLCRja",
        "colab_type": "text"
      },
      "source": [
        "**Respuesta.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "URgqQKnxCTHo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_accidents_by_day = df_trans.copy()\n",
        "df_accidents_by_day = df_accidents_by_day[['DIA_ACCIDENTE', 'CANTIDAD_ACCIDENTES']]\n",
        "df_accidents_by_day = df_accidents_by_day.groupby(by=['DIA_ACCIDENTE']).count()\n",
        "\n",
        "label_dia = ['Dom', 'Lun', 'Mar', 'Mié', 'Jue', 'Vie', 'Sáb']\n",
        "df_accidents_by_day = df_accidents_by_day.reindex(label_dia)\n",
        "\n",
        "df_accidents_by_day.to_excel('output_ex3.xlsx')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZdJk_O3l9ZC-",
        "colab_type": "text"
      },
      "source": [
        "El domingo es el dia donde menos accidentes han ocurrido y el viernes, todo lo contrario."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J7eCs671Cg6t",
        "colab_type": "text"
      },
      "source": [
        "**Punto 4.** Elabore un reporte en donde se muestre, por año, el número de accidentes dependiento de su gravedad. Exporte el DataFrame resultante a un archivo de Excel. ¿Qué conclusiones puede sacar con base al informe generado?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "16TJczBrC9G2",
        "colab_type": "text"
      },
      "source": [
        "**Respuesta.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wLl5wxPlC-z7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_accidents_by_year = df_trans.copy()\n",
        "df_accidents_by_year = df_accidents_by_year[['AÑO_ACCIDENTE', 'GRAVEDAD_ACCIDENTE', 'CANTIDAD_ACCIDENTES']]\n",
        "df_accidents_by_year = df_accidents_by_year.groupby(by=['AÑO_ACCIDENTE', 'GRAVEDAD_ACCIDENTE']).count()\n",
        "\n",
        "df_accidents_by_year.to_excel('output_ex4.xlsx')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uG_SlUvX97qg",
        "colab_type": "text"
      },
      "source": [
        "La mayoria de los accidentes son de gravedad \"Solo danos\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8_jKQBv464An",
        "colab_type": "text"
      },
      "source": [
        "**Recuerde:** En este curso no se tolerará el plagio. Sin excepción, en caso de presentarse esta situación, a los estudiantes involucrados se les iniciará proceso de investigación, y se actuará en conformidad con el Reglamento de Estudiantes de la Universidad del Norte. El plagio incluye: usar contenidos sin la debida referencia, de manera literal o con mínimos cambios que no alteren el espíritu del texto/código; adquirir con o sin intención, trabajos de terceros y presentarlos parcial o totalmente como propios; presentar trabajos en grupo donde alguno de los integrantes no trabajó o donde no se hubo trabajo en equipo demostrable; entre otras situaciones definidas en el manual de fraude académico de la Universidad del Norte:\n",
        "\n",
        "(https://guayacan.uninorte.edu.co/normatividad_interna/upload/File/Guia_Prevencion_Fraude%20estudiantes(5).pdf )."
      ]
    }
  ]
}