Visualization Process

Sowmya Puranam

Library
library("ggplot2")

Questions

Find the mtcars data in R. This is the dataset that you will use to create your graphics.

summary(mtcars)
##       mpg             cyl             disp             hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##       drat             wt             qsec             vs        
##  Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
##  1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
##  Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
##  Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
##  3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
##  Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
##        am              gear            carb      
##  Min.   :0.0000   Min.   :3.000   Min.   :1.000  
##  1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
##  Median :0.0000   Median :4.000   Median :2.000  
##  Mean   :0.4062   Mean   :3.688   Mean   :2.812  
##  3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
##  Max.   :1.0000   Max.   :5.000   Max.   :8.000
str(mtcars)
## '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 ...

1. Create a pie chart showing the proportion of cars from the mtcars data set that have different carb values.

ggplot(data=mtcars, aes(x = factor(1), fill = factor(carb)))+ ylab("Proportions of carburetors") + xlab("") +geom_bar(width = 1) +coord_polar(theta = "y")

We can first create a bar chart for the mtcars dataset and then use the “coord_polar” to create a PIE chart. From the Pie chart we can see that the proportion of cars with 2 and 4 carburetors are high whereas lowest number of cars are seen to have 8 or 6 carburetors.

2. Create a bar graph, that shows the number of each gear type in mtcars.

We can use ggplot and geom_bar to create this bar chart. As it can be observed from the graph, cars with 3 gears are seen to be the maximum.

ggplot(data=mtcars, aes(x=gear, fill=factor(gear))) + geom_bar(stat="count")

3. Next show a stacked bar graph of the number of each gear type and how they are further divided out by cyl.

ggplot(data=mtcars, aes(x=factor(gear), fill=factor(cyl))) + ylab("Values of cyl") +
       xlab("Gear Type")  + geom_bar()

This graph displays the cars classified according to gear type( 3,4 ,5) and the number of cylinders per gear group. It can be seen that out of 15 cars that have 3 gears, only 1 car has 4 cylinders, 2 have 6 cylinders and 12 cars have 8 cylinders.

4. Draw a scatter plot showing the relationship between wt and mpg.

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

We can create the scatter plot by using ggplot and layer geom_point(). The scatter plot shows the relation between miles per gallon and weight and the mileage is seen to decrease with increasing weight. This is defenitely logical since fuel efficiency tends to decrease with an increase in weight.

5. Design a visualization of your choice using the data and write a brief summary about why you chose that visualization.

boxplot(mpg~am,mtcars,xlab = "Automatic and manual transmission", ylab = "Miles per gallons (mpg)",main = " Relationship between Transmission Type And Mpg ")

This plot shows the relationship between the type of transmission and miles per gallon. Box plot provides a measure of mean of response variable for each level of independent variable on the x-axis and also provides the interquartile range of the data for each level of independent variable that provides a nice visual interpretation of the variance of data point in those levels.

I chose this comparison because gas mileage and transmission type has always been one of the important criteria while picking a car and as it can also be seen from the plot, manual cars are likely little more fuel efficient than the automatic cars.