Skip to content

README.md

Latest commit

 

History

History
43 lines (34 loc) · 2.21 KB

README.md

File metadata and controls

43 lines (34 loc) · 2.21 KB

Shinny table dashboard component.

Shinny widget trying to simulate Stephen Few table dashboard component

Inspiration

The widget is inspired by the archetype Sales Dashboard design from Few’s book Information Dashboard Design. image

Demo

Demo available at https://calindamian.shinyapps.io/sf_table_component/

Usage

Files

  • sf_table_component_demo.R : contains the demo showing how to use the module.
  • sf_table_component.R : contains code for the module

The component expects a tibble with following structure in order to work:

tb_data = tibble(measure = c ("Revenue" , "Profit" , "Order Size") 
                 , qualifiers = list (
                                     tibble (qualifier = c ("poor" , "satisfactory" , "good") 
                                             ,range = list (range (0,1000) , range (1000 , 5000) , range (5000 , 10000))  
                                             , color = c ("#525252" , "#969696"  , "#cccccc")
                                             ) 
                                    , tibble (qualifier = c ("poor" , "satisfactory" , "good") 
                                                ,range = list (range (0,100) , range (100 , 600) , range (500 , 1000))  
                                                , color = c ("#525252" , "#969696"  , "#cccccc")
                                                )  
                                    , tibble (qualifier = c ("poor" , "satisfactory" , "good") 
                                              ,range = list (range (0,10) , range (10 , 60) , range (60 , 100))  
                                              , color = c ("#525252" , "#969696"  , "#cccccc")
                                    )  
                 )
                 , actual =  c(NA , 800 , NA) #NA #c (100 , 258 , 500) #if NA last values
                 , target = c (8000 , 400 , 60)
                 , hist_data = list (tibble(x=1:12 , y= sample (1000:10000 , 12)) 
                                     , tibble(x=1:12 , y= sample (100:1000 , 12)) 
                                     , tibble(x=1:12 , y= sample (10:100 , 12)) ))