R Studio Environment
R Location (OSX)
$ ls –l /Library/Frameworks/R.framework/Versions
#Get R Version
version
Environment
getwd()
setwd(“/Users/avkashchauhan/work/global”)
getwd()
dir()
#Getting Help
help(getwd)
#Reading a File
help(read.csv)
filename <- “test.csv”
filex <- read.csv(filename, header = TRUE, sep=”,”)
filex
summary(filex)
filex$id
filex$name
filex$age
filex$zip
names(filex)
attributes(filex)
# Listing All Vars
ls()
# ls() – List of all variables
# DataTypes & number Assignment
asc <- c(1,2,3,4,5,6,7,8,9,10)
# What is c? c is “combine”
asc[2]
asc[5]
asc[5:6]
asc[1:9]
View(asc)
a <- 10
a
a[1]
a[3]
help(sqrt)
a <- sqrt(10)
a
a <- sqrt(10*a)
a
asc
mean(asc)
median(asc)
help(var)
typeof(asc)
typeof(a)
# String data type
a <- c(“this”, “is”, “so”, “fun”)
a
a[1]
typeof(a)
#Understanding c or combine
a <- 10
> a
[1] 10
> a[1]
[1] 10
> a[2]
[1] NA
> a <- c(10)
> a
[1] 10
> a[2]
[1] NA
# DATAFRAME
# creating a data frame
a <- c(1,2,3,4,5,6,7,8,9,10)
b <- c(10,20,30,40,50,60,70,80,90,100)
ab <- data.frame(first=a, second=b)
ab
ab[1]
ab[1][1]
ab[1][2] ß XXX
ab[2]
ab[2][1]
ab[2][2] ß XXX
ab$first
ab$second
ab$second[1]
ab$second[3]
ab$first[10]
View(ab)
#Logical
a <- c(TRUE)
a
typeof(a)
a <- c(FALSE)
a
typeof(a)
#Conditions in R
a <- c(TRUE)
if(!a) a <- c(FALSE)
a ß Still TRUE
if(a) a <- c(FALSE)
a ß FALSE Now
a <- c(TRUE,FALSE)
a
a[1]
a[2]
if (a[1]) a[2] <- TRUE
a
Factor in R – A “factor” is a vector whose elements can take on one of a specific set of values. For example, “Sex” will usually take on only the values “M” or “F,” whereas “Name” will generally have lots of possibilities. The set of values that the elements of a factor can take are called its levels.
a <- factor(c(“Male”, “Female”, “Female”, “Male”, “Male”))
a
a <- factor(c(“A”,”A”,”B”,”A”,”B”,”B”,”C”,”A”,”C”))
a
Tables: (One way and two way)
a <- factor(c(“Male”, “Female”, “Female”, “Male”, “Male”))
a
mytable <- table(a)
a
mytable
summary(a)
attributes(a)
#datatype check R
#Example #1
a <- c(1,2,4)
is.numeric(a)
is.factor(a)
#Example #2
b <- factor(c(“M”, “F”))
b
is.factor(b)
is.numeric(b)
Graph Plotting in R
Using Library ggplot2
#installing ggplot2
install.packages(“ggplot2”)
also installing the dependencies ‘colorspace’, ‘Rcpp’, ‘stringr’, ‘RColorBrewer’, ‘dichromat’, ‘munsell’, ‘labeling’, ‘plyr’, ‘digest’, ‘gtable’, ‘reshape2’, ‘scales’, ‘proto’
Using ggplot2 Library
library(ggplot2)
detach(package:ggplot2)
head(diamonds)
View(diamonds)
qplot(clarity, data=diamonds, fill=cut, geom=”bar”)
qplot(clarity, data=diamonds, geom=”bar”, fill=cut, position=”stack”)
qplot(clarity, data=diamonds, geom=”freqpoly”, group=cut, colour=cut, position=”identity”)
qplot(carat, data=diamonds, geom=”histogram”, binwidth=0.1)
qplot(carat, data=diamonds, geom=”histogram”, binwidth=0.01)
Graph Source: http://www.ceb-institute.org/bbs/wp-content/uploads/2011/09/handout_ggplot2.pdf
Keywords: R, Analysis, ggplot,
Everything Artificial Intelligence 