Shiny Application and Reproducible Pitch

This presentation is part of the last course Developing Data Products. The peer assessed assignment has two parts:

Create a Shiny application and deploy it on Rstudio’s servers.
Use Slidify or Rstudio Presenter to prepare a reproducible pitch presentation about the application.

Slidify presentation: https://roxtrejos.shinyapps.io/sarp/

I have selected mtcars to develop my product for this assigment.

    library(shiny)
    library(datasets)
    library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

    library(ggplot2)
    library(car)

## Loading required package: carData

## 
## Attaching package: 'car'

## The following object is masked from 'package:dplyr':
## 
##     recode

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)

##                    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
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

    scatterplotMatrix(~mpg+disp+wt, data=mtcars, cex.axis=1.5)

    plot <- ggplot(data=mtcars, aes(x=hp, y = mpg))+
            geom_point(aes(color = as.factor(cyl)), alpha = 0.9)
        plot