plotting with R

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summary(cars)

##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

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Loading packages

library(datasets)

loading data

data(mtcars)

viewing first 5 rows from the dataset mtcars

head(mtcars,5)

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2

Load ggplot package

library(ggplot2)

create a scatterplot of displacement (disp) and miles per gallon (mpg)

ggplot(aes(x=disp,y=mpg,),data = mtcars)+geom_point()

Add a title

ggplot(aes(x=disp,y=mpg,),data=mtcars)+geom_point()+ggtitle("displacement vs miles per gallon")

change axis name

ggplot(aes(x=disp,y=mpg),data=mtcars)+geom_point()+ggtitle("displacement vs miles per gallon") + labs(x = "Displacement", y = "Miles per Gallon")

#make vs a factor

mtcars$vs <- as.factor(mtcars$vs)

create boxplot of the distribution for v-shaped and straight Engine

ggplot(aes(x=vs, y=mpg), data = mtcars) + geom_boxplot()

#Add color to the boxplots to help differentiate:

ggplot(aes(x=vs, y=mpg, fill = vs), data = mtcars) + 
  geom_boxplot(alpha=0.3) +
  theme(legend.position="none")

#Finally, let us create the histogram of weight wt.

ggplot(aes(x=wt),data=mtcars) + geom_histogram(binwidth=0.5)