getting started with RStudio

getting started with RStudio.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rstudio OverView"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R-Studio overview  \n",
    "we have 4 panes  \n",
    "1) script pan - to write and save the programing script  \n",
    "2) Console pane - where all the code will get executed  \n",
    "3) Environment/history pane - displays all the variables created,functions used with in the current session  \n",
    "4) Helper pane - contains multiple tabs to install/display pacakges, view visualization plots,  \n",
    "locate files within the workspace \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "help(mean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# getting and setting workspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "'C:/Users/Suresh/mlclassscripts'"
      ],
      "text/latex": [
       "'C:/Users/Suresh/mlclassscripts'"
      ],
      "text/markdown": [
       "'C:/Users/Suresh/mlclassscripts'"
      ],
      "text/plain": [
       "[1] \"C:/Users/Suresh/mlclassscripts\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to display current working directory use getwd() function\n",
    "getwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# to set up workspace or working directory use setwd() function\n",
    "#syntax is shown below\n",
    "setwd(\"path\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "setwd(\"C:\\\\Suresh\\\\R&D\\\\Projects\\\\ML classroom training\\\\sessions\")\n",
    "setwd(\"C:/Suresh/R&D/Projects/ML classroom training/sessions\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# getting help in R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get help within R environment, we use help() function to get the documentation for any of the functions/packages available within R environment.   \n",
    "To see the arguments required for a function, we use args() function.  \n",
    "to see the example of a function, example() function is used.  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "help(\"stats\")\n",
    "help(\"mean\")\n",
    "args(\"mean\")\n",
    "example(\"mean\")\n",
    "\n",
    "#getting help documentation for a package\n",
    "help(package=\"caret\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# online help for R programming"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can get online help on available packages in R from official website of R-Cran  \n",
    "https://cran.r-project.org/web/views/\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also get online support for our day to day activities from below websites:  \n",
    "https://stackoverflow.com/  \n",
    "https://stats.stackexchange.com  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Installing Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#install pacakges in R can be done in two ways,\n",
    "#1) using install.packages() function and from the bottom right pane of Rstudio\n",
    "install.packages(\"randomForest\")\n",
    "\n",
    "#loading of installed or downloaded packages can be done using library() function. Note that we can only load the package if\n",
    "# we have installed the package already within our R environment\n",
    "library(cluster)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#below code to first verify if the library is installed in the R environment, if it is not available\n",
    "# then the package will get installed.\n",
    "if(!library(cluster)){\n",
    "install.pacakges(\"cluster\")\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# basic operations in R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Adding two numericals\n",
    "1+1\n",
    "\n",
    "#multiplying two numericals\n",
    "10*2\n",
    "\n",
    "#dividing two numericals\n",
    "10/2\n",
    "\n",
    "#applying modulus operation on two numericals\n",
    "10%%2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# printing results to R console"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#printing the data on the console\n",
    "print(10*2)\n",
    "\n",
    "print(\"data science\")\n",
    "\n",
    "print(pi^2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Variable declaration and assignment in R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "variable assignment: In the below example, we are creating variable named z:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "z <-  100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we use left arrow or = symbol for variable assignment. Its always good practice to use left arrow for assignment.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "z = 10.009\n",
    "z <- 10.009"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading existing or default datasets available in R environment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we can access default datasets avaiable in R using data() function.  \n",
    "data() function will displays all the avaiable datasets within R.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to load a specific dataset into R, we need to give the dataset name as argument to the data() function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data(AirPassengers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Viewing data of R objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To view first 5 records of a R object (ex:dataframe), we use head() function.  \n",
    "head() function expects the data object as argument and prints the first 5 records on the R console.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "head(AirPassengers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to view all the records in a nice tabular view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "View(AirPassengers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Getting the decription and structure of R object"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "use str function to see the descriptions of the data object,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "str(AirPassengers)"
   ]
  }
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