Price also depends on the diamond’s cut, color, and clarity. - Color: best(D) to worst(J) - Clarity: measures how clear the diamond is from best to worst (IF, VVS2, VVS1, VS2, VS1, SI2, SI1, I1) - Cut: quality of the diamond from best to worst (Ideal, Premium, Very Good, Good, Fair)

This app will predict diamond price based on your input of these factors

Here is a summary of the “diamonds” dataset found in the ggplot2 R package. As you can see, the factors were measured in over 50,000 diamonds

## tibble [53,940 x 5] (S3: tbl_df/tbl/data.frame)
##  $ carat  : num [1:53940] 0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
##  $ cut    : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
##  $ color  : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
##  $ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
##  $ price  : int [1:53940] 326 326 327 334 335 336 336 337 337 338 ...

• shiny app: swarajmohanty.shinyapps.io/Diamond_cost_pre/
• source code: https://github.com/swarajmohanty/Diamond_cost_predication