############# 35 rows
# baseline
#EU27yr19: 37
supply_details_baseline_1<- convert_supply_details(region_list= "EU27yr19",
                                                  product_list= product_list$code,
                                                  scenario_list= sanky_file1,
                                                  folder = gdx.dir)
# sc
supply_details_sc_1 <- convert_supply_details(region_list= "EU27yr19",
                                              product_list= product_list$code,
                                              scenario_list= sanky_file2,
                                              folder = gdx.dir)

######### 60 rows
supply_details_baseline_3 <- convert_supply_details(region_list= "EU",
                                              product_list= product_list.all,
                                              scenario_list= sanky_file1,
                                              folder = gdx.dir)

supply_details_sc_3 <- convert_supply_details(region_list= "EU",
                                              product_list= product_list.all,
                                              scenario_list= sanky_file2,
                                              folder = gdx.dir)



#step 2

# filter
sel_supply_details_bs_1 <-filter_supply_details(supply_details = supply_details_baseline_1, min.Level = 0, min.gross.value.added = 0)
sel_supply_details_sc_1 <-filter_supply_details(supply_details = supply_details_sc_1, min.Level = 0, min.gross.value.added = 0)

#step 3

# output tables

supply_tb <- cal_diff_percentage_change(sel_supply_details_bs_1,sel_supply_details_sc_1,supply_details = TRUE, abs = TRUE, percent_change = TRUE)


# setp 4

# make nice table

nice_supply_details_table(supply_tb, "activity", min.abs = 1000, min.percent_change = -10000) %>%
  gtsave(
    "supply_details_tb_product_list.html", inline_css = FALSE,
    path = outdata.dir)


# supply_tb %>%
#   filter(diff_level > min.abs)%>%
#   filter(diff_gross_value_added > min.abs)%>%
#   filter(level > min.percent_change)%>%
#   filter(gross_value_added > min.percent_change)
#
#
# supply_tb %>% select(2:4)



remotes::install_github('rstudio/DT')
tb <- DT::datatable(supply_tb, class = 'cell-border stripe')

mytable <- DT::datatable(supply_tb %>% janitor::remove_empty(which = "cols"), filter = 'top') %>%
  # DT::formatRound( -1, 1) %>%
  DT::formatPercentage(c('level','gross_value_added','volume'), digits = 1)
mytable
saveWidget(tb, "mytable.html")