This presentation contains documentation for the Diamond price prediction application. The application can be found through the below mentioned link https://ashishveera.shinyapps.io/Course-Project-Shiny-Application-and-Reproducible-Pitch/
11/29/2017
This presentation contains documentation for the Diamond price prediction application. The application can be found through the below mentioned link https://ashishveera.shinyapps.io/Course-Project-Shiny-Application-and-Reproducible-Pitch/
This application is building a linear regression model using diamonds data set and is predicting the price of a diamond depending on its properties.The application allows the user to select: - Carat - Cut - Color - Clarity
Finally, builds a plot and gives predicted price of the diamond.
The data used for this application is diamonds data set, which is part of ggplot2 package. This data set contains the information about 53940 diamonds with 10 variables:
## carat cut color clarity ## Min. :0.2000 Fair : 1610 D: 6775 SI1 :13065 ## 1st Qu.:0.4000 Good : 4906 E: 9797 VS2 :12258 ## Median :0.7000 Very Good:12082 F: 9542 SI2 : 9194 ## Mean :0.7979 Premium :13791 G:11292 VS1 : 8171 ## 3rd Qu.:1.0400 Ideal :21551 H: 8304 VVS2 : 5066 ## Max. :5.0100 I: 5422 VVS1 : 3655 ## J: 2808 (Other): 2531 ## depth table price x ## Min. :43.00 Min. :43.00 Min. : 326 Min. : 0.000 ## 1st Qu.:61.00 1st Qu.:56.00 1st Qu.: 950 1st Qu.: 4.710 ## Median :61.80 Median :57.00 Median : 2401 Median : 5.700 ## Mean :61.75 Mean :57.46 Mean : 3933 Mean : 5.731 ## 3rd Qu.:62.50 3rd Qu.:59.00 3rd Qu.: 5324 3rd Qu.: 6.540 ## Max. :79.00 Max. :95.00 Max. :18823 Max. :10.740 ## ## y z ## Min. : 0.000 Min. : 0.000 ## 1st Qu.: 4.720 1st Qu.: 2.910 ## Median : 5.710 Median : 3.530 ## Mean : 5.735 Mean : 3.539 ## 3rd Qu.: 6.540 3rd Qu.: 4.040 ## Max. :58.900 Max. :31.800 ##
The application is built using Shiny package and the source code is in 2 files: - ui.R - server.R
These files can be found here: