Dimonds Reproducible Pitch

Michelle Tan
01/20/2018

First Slide

Diamond Analysis Report Diamond Data Analysis Report enabled developing data products using shiny apps being embeded within RMarkDown.

Using PageUp and PageDown keys all the slides can be traversed.

For more details on authoring R presentations please visit https://michelletan.shinyapps.io/DiamondsApp/. This presentation contains documentation for the Diamond price prediction application. The application can be found

This application it is building linear regression model using `diamonds` data set and is predicting the price of a diamond depending of its properties.The application allows the user to select:

source code in github https://github.com/Michelletan78/Course-_project_Shiny-Application-and-Reproducible–Pitch

For more details on authoring R presentations please visit https://support.rstudio.com/hc/en-us/articles/200486468. Application Overview

  • Bullet 1 Diamonds Properties can be analysed using several Parameters.

  • Bullet 2 Carat,Price,sample size,color Depth are some of the common parameters.

  • Bullet 3 This Report enables to pick the right parameters for the best Diamond selection.

Slide With Code

The data used for this application is diamonds data set, which is part of ggplot2 package. Containing information about 53940 diamonds with 10 variables.

data("diamonds")

Slide With Plot

# A tibble: 6 x 10
  carat       cut color clarity depth table price     x     y     z
  <dbl>     <ord> <ord>   <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
1  0.23     Ideal     E     SI2  61.5    55   326  3.95  3.98  2.43
2  0.21   Premium     E     SI1  59.8    61   326  3.89  3.84  2.31
3  0.23      Good     E     VS1  56.9    65   327  4.05  4.07  2.31
4  0.29   Premium     I     VS2  62.4    58   334  4.20  4.23  2.63
5  0.31      Good     J     SI2  63.3    58   335  4.34  4.35  2.75
6  0.24 Very Good     J    VVS2  62.8    57   336  3.94  3.96  2.48