Assignent 2

#Creating the Vectors:

a<-c(2,5,6,7)
b<-c(1,0,9,8)
c<-c(6,5,8,3)

Rowbinding the vector to form a 4x3 Matrix

mat<-rbind(a,b,c)
mat
##   [,1] [,2] [,3] [,4]
## a    2    5    6    7
## b    1    0    9    8
## c    6    5    8    3

Naming Matrix

colnames(mat)<-c("Mon", "Tue", "Wed", "Thu")
rownames(mat)<-c("Present","Absent","On leave")
mat
##          Mon Tue Wed Thu
## Present    2   5   6   7
## Absent     1   0   9   8
## On leave   6   5   8   3

Calculating Sums

row<-rowSums(mat)
row
##  Present   Absent On leave 
##       20       18       22
col<-colSums(mat)
col
## Mon Tue Wed Thu 
##   9  10  23  18

Plotting mtcars

data<-mtcars
str(data)
## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
library(ggplot2)
library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
library(ggthemes)

#Scatterplot of mpg vs disp

p<-ggplot(data=data)+theme_economist()
p1<-p+
   geom_point(mapping=aes(x=mpg,y=disp), col="Blue")
p2<-ggplotly(p1)
p2

Boxplot of mpg with gear

q<-ggplot(data=data, aes(gear, mpg))+theme_economist()
q1<-q+
   geom_boxplot(notch=TRUE, col="Blue")+
   facet_wrap(~gear, nrow=2)
q2<-ggplotly(q1)
## Warning: Continuous x aesthetic
## ℹ did you forget `aes(group = ...)`?
q2

Histogram of disp

h<-ggplot(data=data, aes(disp))+theme_economist()
h1<-h+
   geom_histogram()+
   geom_freqpoly()
h2<-ggplotly(h1)
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
h2