This peer assessed assignment has two parts. First, you will create a Shiny application and deploy it on Rstudio’s servers. Second, you will use Slidify or Rstudio Presenter to prepare a reproducible pitch presentation about your application.
-This app helps you to compare different cars, using the mtcars dataset from [R].
-Choose some caractheristcs of the cars that you desire: Cylinders, Horse Power and Transmission Quater Mile Time. The table will show only the cars with the filters selected. You can sort the table according to the variable you want by clicking the arrows at the top of the table.
The data used in the app comes from the Motor Trend Car Road Tests (mtcars) dataset. The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models). We can look to some carachteristics of the data:
head(mtcars)[,1:3]
## mpg cyl disp
## Mazda RX4 21.0 6 160
## Mazda RX4 Wag 21.0 6 160
## Datsun 710 22.8 4 108
## Hornet 4 Drive 21.4 6 258
## Hornet Sportabout 18.7 8 360
## Valiant 18.1 6 225
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
Here we can see the relationship between variables: miles per gallon(mpg) and horsepower(hp).
library(carData);library(car)
scatterplotMatrix(~mpg+hp, data=mtcars, cex.axis=1.5)