R_Practice_Code.R

# Practice1- Find out the difference between 689 and 53 using R as a calculator

689-53

# P2- Assign values to variables and do computation

x<-9
y<- 16

x+y
x-y
sqrt(x)
sqrt(y)
sqrt(x)+sqrt(y)

# P3- Create a vector using 'concatenate' or 'combine' function

z <- c(1,2,3,5,9,10)
z
z*2+150

# P4- Vector "Recyling"

c(1,2,3,4) + c(0,10)

# P5- Get working directory and set working directory
getwd()
setwd("C:/Users/rpand/Desktop/Documents/Classes/Classes/basic_stats")

# P6- list all objects in the workspace
ls()

# P7- list all files in the working directory
list.files()

# P8- Getting help on any function
?list.files()

#P9- Sequencing
1:15
15:0
pi:20
seq(0,20,0.5)
seq(1,20, length=40)
rep(c(1,2,3), times=25)
rep(c(1,2,3), each=25)

#P10- Reading data

cars <- read.csv("Worksheet in statistics_intro_day1n2.csv")

# P11- Subsetting dataframe

newcars1 <- cars[1:10,1:3]
newcars2 <- cars[1:10, c(1,8,9)]
newcars3 <- cars[1:10, c("Origin", "Year")]

# P12 - Find rows with max, min etc. 

newcars4<- cars[which.max(cars$MPG),]
newcars5<- cars[cars$MPG == max(cars$MPG),]
newcars6<- cars[which.min(cars$MPG),]
newcars7<- cars[cars$MPG == min(cars$MPG),]

# P13- Creating New Variables in the dataset
cars$MPGpCYL <- cars$MPG/cars$Cylinders
cars$Mileage <- ifelse(cars$MPG >= 30, "Good", "Not so Good")

# P14- Summarizing data
head(cars)
tail(cars)
str(cars)
dim(cars)
str(cars)
names(cars)
ncol(cars)
nrow(cars)
class(cars)

# P15- Descriptive Stats
attach(cars)
mean(MPG)
median(MPG)
mode(MPG)
var(MPG)
sd(MPG)
range(MPG)
min(MPG)
max(MPG)
quantile(MPG, seq(0,1,0.05))

#Correlations

cor(newcars, use="complete.obs", method="pearson") 
cor(newcars$MPG, newcars$Weight)

# Count of cars by Origin
library(plyr) # install.packages("plyr")
count(cars, 'Origin')

# Write the output to Excel (csv) file. 
write.csv(count(cars, 'Origin'), "Countsheet.csv")

# Means, max, min by Origin

aggregate(MPG, list(Origin), mean)
aggregate(MPG, list(Origin), max)
aggregate(MPG, list(Origin), min)

# P16- plots

library(ggplot2) # may need to install this package using install.packages()
library(gridExtra)

p <- ggplot(cars, aes(Origin, MPG))

p + geom_boxplot(aes(fill = Origin))

p1 <- ggplot(cars, aes(x=Horsepower, y= Weight))
p1+geom_point(aes(color=factor(Origin))) + scale_color_manual(values = c("Green", "Purple", "Orange"))