コミット: db3f264ed161cbc6a75db74b3dabddec6a54a665 - myprojects-hg-reborn (hg)

コミットメタ情報

• リビジョン: db3f264ed161cbc6a75db74b3dabddec6a54a665 (tree)
• 日時: 2022-09-22 19:38:45
• 作者: Lorenzo Isella <lorenzo.isella@gmai...>
• コミッター: Lorenzo Isella

ログメッセージ

I now use the right variable for the scoreboard objectives.

変更サマリ

• modified: R-codes/shiny_scoreboard.R
• modified: markdown/report_generator_scoreboard.Rmd

差分

diff -r 8cb4e420b633 -r db3f264ed161 R-codes/shiny_scoreboard.R
--- a/R-codes/shiny_scoreboard.R	Thu Sep 22 10:29:40 2022 +0200
+++ b/R-codes/shiny_scoreboard.R	Thu Sep 22 12:38:45 2022 +0200
@@ -165,10 +165,13 @@
 
 df_sc <- df_sc_ini |>
     select(member_state, expenditure_year, harmonised_aid_instrument,
-           harmonised_primary_obj, aid_element_eur, case_number,
+           ## harmonised_primary_obj
+           scoreboard_objective
+         , aid_element_eur, case_number,
            case_type,  co_financing_percentage, covid) |>
-    mutate(harmonised_aid_instrument=remove_trailing_spaces(harmonised_aid_instrument),
-           harmonised_primary_obj=remove_trailing_spaces(harmonised_primary_obj)   ) |>
+    ## mutate(harmonised_aid_instrument=remove_trailing_spaces(harmonised_aid_instrument)## ,
+    ##        ## harmonised_primary_obj=remove_trailing_spaces(harmonised_primary_obj)  
+    ##        ) |>
     filter(!is.na(aid_element_eur))
 
 instrument <- df_sc |>
@@ -177,7 +180,8 @@
     unique()
 
 objective <- df_sc |>
-    pull(harmonised_primary_obj) |>
+    ## pull(harmonised_primary_obj) |>
+    pull(scoreboard_objective) |>
     sort() |>
     unique()
 
@@ -386,7 +390,8 @@
                ## expenditure_year %in% seq(2010,2020),
                case_type %in% input$case_type,
                harmonised_aid_instrument %in% input$instruments,
-               harmonised_primary_obj %in% input$objectives
+               ## harmonised_primary_obj
+               scoreboard_objective %in% input$objectives
                    )
     })
 
@@ -605,7 +610,7 @@
 
 
             data_sel() |>
-                group_by(expenditure_year, harmonised_primary_obj ) |>
+                group_by(expenditure_year, scoreboard_objective ) |>
                 summarise(exp_mio_eur=sum(aid_element_eur, na.rm=T)) |>
                 ungroup() |>
                 mutate(exp_mio_eur=round_preserve_sum(exp_mio_eur,2)) 
@@ -617,7 +622,7 @@
         objective_agg_long <- reactive({
 
             data_sel() |>
-                group_by(harmonised_primary_obj ) |>
+                group_by(scoreboard_objective ) |>
                 summarise(exp_mio_eur=sum(aid_element_eur, na.rm=T)) |>
                 ungroup() |>
                 mutate(exp_mio_eur=round_preserve_sum(exp_mio_eur,2)) |>
@@ -641,8 +646,8 @@
     
     yearly_objective_agg_long_top <- reactive({
         yearly_objective_agg_long() |>
-            mutate(harmonised_primary_obj_top=fct_lump_n(harmonised_primary_obj,k_levels, exp_mio_eur, "All Other Objectives")) |>
-            group_by(expenditure_year, harmonised_primary_obj_top) |>
+            mutate(scoreboard_objective_top=fct_lump_n(scoreboard_objective,k_levels, exp_mio_eur, "All Other Objectives")) |>
+            group_by(expenditure_year, scoreboard_objective_top) |>
             summarise(exp_mio_eur=sum(exp_mio_eur)) |>
             ungroup()
         
@@ -896,13 +901,13 @@
 
 
         n_colors <- yearly_objective_agg_long_top() |>
-            pull(harmonised_primary_obj_top) |> 
+            pull(scoreboard_objective_top) |> 
             unique() |> 
             length()
 
         fig <-  plot_ly(yearly_objective_agg_long_top(),
                         x = ~expenditure_year, y = ~exp_mio_eur,
-                            type = 'bar', color = ~harmonised_primary_obj_top,
+                            type = 'bar', color = ~scoreboard_objective_top,
                             ## symbol = ~anno,
                             colors = viridis_pal(option = "H")(n_colors))  %>%
                 layout(hovermode = "x unified",xaxis = list(title="",

diff -r 8cb4e420b633 -r db3f264ed161 markdown/report_generator_scoreboard.Rmd
--- a/markdown/report_generator_scoreboard.Rmd	Thu Sep 22 10:29:40 2022 +0200
+++ b/markdown/report_generator_scoreboard.Rmd	Thu Sep 22 12:38:45 2022 +0200
@@ -355,7 +355,7 @@
 ft <- objective_agg_long() |> 
     flextable()  |> 
     ## add_header_row(values = c(paste("State Aid Measures in ", year_focus, sep="")) ) %>%
-    set_header_labels(harmonised_primary_obj="Harmonized Objective",
+    set_header_labels(scoreboard_objective="Harmonized Objective",
                       exp_mio_eur="Aid (mio EUR)",
                       percentage="Percentage of Total Aid",
                       cumulative_percentage="Cumulative Percentage"
@@ -393,7 +393,7 @@
 
 ggplot(data = yearly_objective_agg_long_top(), aes(x  = expenditure_year,
                                               y=exp_mio_eur,
-                                      fill=harmonised_primary_obj_top)) +
+                                      fill=scoreboard_objective_top)) +
     geom_bar(position=position_dodge2(preserve="single"), stat="identity", alpha=1, color="black")+
     ## scale_fill_viridis("Vehicle Brand\nOrigin",breaks=mybreaks, labels= mylabels, discrete=T)+
     ##     scale_colour_viridis("Vehicle Brand\nOrigin",breaks=mybreaks, labels= mylabels, discrete=T)+