probando-con-r.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Probando con R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Con la herramienta Jupyter Notebook en esta nueva práctica utilizaremos el lenguaje de programación R. Este lenguaje es usado para tareas de análisis estadístico y la aplicación de gráficos a partir de unos datos. \n",
    "\n",
    "R es un lenguaje de programación que se diferencia del resto se \n",
    "trata de un lenguaje que realiza las acciones solicitadas sin ser necesario la compilación previa. Además, en este enfoque del análisis estadístico es clave es donde encontramos la diferencia en el resto, pues es muy funcional para el análisis de datos. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Instalar librerías"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Las librerías son herramientas que nos permiten desarrollar más de un lenguaje de programación con el que trabajemos, en esta práctica será lenguaje R. Para instalar liberías se debería hacer esto, pero en la clase no se pudo realizar. Instalar el paquete ggplot2 se realiza a través de la función R: \n",
    "\n",
    "`install.packages(ggplot2\")`\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importar librerías"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En este apartado se importa la librería que se puede cargar en este notebook usando la función `library()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(ggplot2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Crear Datos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para ello hemos seleccionados los datos que queremos que sean representados. A partir de un ggplot ya creado con anterioridad y ofrecido por el profesor, cambiaremos en él los nombres y los datos. En este apartado hubo un fallo en la clase que no se pudo solucionar y por ello no sabría como completar este apartado. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lylOQhJ/KTV3AhJrtIchCR+0mpuhCRX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\nAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bajas <- c(rep(\"Tanques\" , 2) , rep(\"Artillería\" , 2) , rep(\"Aeronaves\" , 2) )\n",
    "paises <- rep(c(\"Rusia\", \"Ucrania\"), 3)\n",
    "value <- abs(rnorm(12 , 0 , 15))\n",
    "data <- data.frame(bajas, paises, value)\n",
    "\n",
    "# Grouped\n",
    "ggplot(data, aes(fill=paises, y=value, x=bajas)) + \n",
    "    geom_bar(position=\"dodge\", stat=\"identity\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}