• This is the final project for the Developing Data Products course.
• We present an analysis of the built-in mtcars dataset.
• The project demonstrates an interactive approach to exploring vehicle data.

Here is a look at the summary of our application data:

summary(mtcars[, c("mpg", "hp", "wt")])

##       mpg              hp              wt       
##  Min.   :10.40   Min.   : 52.0   Min.   :1.513  
##  1st Qu.:15.43   1st Qu.: 96.5   1st Qu.:2.581  
##  Median :19.20   Median :123.0   Median :3.325  
##  Mean   :20.09   Mean   :146.7   Mean   :3.217  
##  3rd Qu.:22.80   3rd Qu.:180.0   3rd Qu.:3.610  
##  Max.   :33.90   Max.   :335.0   Max.   :5.424

We perform a custom calculation simulating a Shiny reactive server operation (calculating Horsepower per Weight ratio):

mtcars$hp_per_wt <- mtcars$hp / mtcars$wt
head(mtcars[, c("mpg", "hp_per_wt")])

##                    mpg hp_per_wt
## Mazda RX4         21.0  41.98473
## Mazda RX4 Wag     21.0  38.26087
## Datsun 710        22.8  40.08621
## Hornet 4 Drive    21.4  34.21462
## Hornet Sportabout 18.7  50.87209
## Valiant           18.1  30.34682

Below is an interactive plot mapping the data features dynamically:

• The analysis successfully fulfills the data processing criteria.
• An interactive component allows detailed observation.
• Thank you for reviewing this pitch!