This presentation is a part of final project assignment in the Developing Data Product course of Coursera Data Science Specialization track. Here, first we create a Shiny app and deploy it on Rstudio’s servers. In the app we analyse the mileage per galon of the mtcars data categorically.

• Form of Input used: Select Input
• Reactive output displayed as a result of server calculatin.
• The server.R and ui.R codes are posted on github at: https://github.com/bbhusal/Developing-Data-Product-Final-Project
• The App can be found at: https://bbhusal.shinyapps.io/W4_Assignment/

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). Out of the 10 five are categorical. We can look to some carachteristics of the data:

##                    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

This app can be a very useful tool to analyse the gas mileage of a car in different aspects. So it could be helpful to decide the selection of right car.