提交: 121264f50667afc4b3b8d98d5ef6e5b00927c73c - myprojects-hg-reborn (hg)

Commit MetaInfo

• 修订版: 121264f50667afc4b3b8d98d5ef6e5b00927c73c (tree)
• 时间: 2023-02-08 00:55:18
• 作者: Lorenzo Isella <lorenzo.isella@gmai...>
• Commiter: Lorenzo Isella

Log Message

I replaced most of the %>% with |>, but one is still missing.

更改概述

• modified: markdown/fiches_automatic.Rmd

差异

diff -r bd17fd027114 -r 121264f50667 markdown/fiches_automatic.Rmd
--- a/markdown/fiches_automatic.Rmd	Tue Feb 07 09:52:06 2023 +0100
+++ b/markdown/fiches_automatic.Rmd	Tue Feb 07 16:55:18 2023 +0100
@@ -28,157 +28,11 @@
 source("/home/lorenzo/myprojects-hg/R-codes/stat_lib.R")
 
 
-## iso_map <- tibble(iso3=c("AUT", "BEL", "BGR", "CYP", "CZE", "DEU", "DNK", "ESP", "EST", "FIN",
-## "FRA", 
-## "GRC", "HRV", "HUN", "IRL", "ITA", "LTU", "LUX", "LVA", "MLT",
-## "NLD", "POL", "PRT",
-## "ROM", "SVK", "SVN", "SWE"),
-## country=c("Austria", "Belgium", "Bulgaria", "Cyprus", "Czech Republic", "Germany",
-##   "Denmark", "Spain", "Estonia", "Finland", "France", "Greece",
-##   "Croatia", "Hungary", "Ireland","Italy", "Lituania", "Luxembourg",
-##   "Latvia", "Malta", "Netherlands", "Poland", "Portugal",
-##   "Romania", "Slovakia", "Slovenia", "Sweden")
-## )
-
-## add_total <- function(x, pos=1, ...){
-##     adorn_totals(x, ...) %>% as_tibble %>%
-##     move_row(nrow(.), pos)    
-## }
-
-## add_total <- function(x, pos=1, ...){
-##     x <- as_tibble(x)
-    
-##         adorn_totals(x, ...)  |>
-##         as_tibble() |> 
-##     move_row(nrow(.), pos)    
-## }
-
-
-## add_total <- function(x, pos=1, ...){
-
-
-    
-##     x |> as_tibble() |>
-##         adorn_totals( ...)  |>   
-##     as_tibble()  |>
-##     (\(x) move_row(x, nrow(x)+1, pos))()
-    
-## }
-
-
-
-## iso_map <- tibble(iso3=c("AUT", "BEL", "BGR", "CYP", "CZE", "DEU", "DNK", "ESP", "EST", "FIN",
-## "FRA", 
-## "GRC", "HRV", "HUN", "IRL", "ITA", "LTU", "LUX", "LVA", "MLT",
-## "NLD", "POL", "PRT",
-## "ROM", "SVK", "SVN", "SWE", "GBR"),
-## iso2 = c("AT", "BE",  "BG", "CY", "CZ","DE",
-##               "DK",   "ES" ,"EE",  "FI",  "FR",  "EL", "HR", "HU", "IE",
-##               "IT" , "LT","LU", "LV",  "MT", "NL", "PL",
-##               "PT", "RO", "SK", "SI", "SE", "UK"),
-
-## country=c("Austria", "Belgium", "Bulgaria", "Cyprus", "Czechia", "Germany",
-##   "Denmark", "Spain", "Estonia", "Finland", "France", "Greece",
-##   "Croatia", "Hungary", "Ireland","Italy", "Lithuania", "Luxembourg",
-##   "Latvia", "Malta", "Netherlands", "Poland", "Portugal",
-##   "Romania", "Slovakia", "Slovenia", "Sweden", "United Kingdom")
-## )
-
 
 
 # Suppress summarise info
 options(dplyr.summarise.inform = FALSE)
 
-## '%!in%' <- function(x,y)!('%in%'(x,y))
-
-
-
-## format_col <- function(x, n, my_sep=" "){
-
-##     res <- format(round(x, n), nsmall = n, big.mark= my_sep, trim=TRUE )
-
-## return(res)
-    
-## }
-
-
-## recode_many <- function(x, old_names, new_names){
-
-##     name_lookup <- set_names(new_names, old_names) %>% as.list
-
-##     res <- recode(x, !!!name_lookup)
-##     return(res)
-    
-## }
-
-
-## my_ggplot_theme2 <- function(legend_coord){
-##     theme_bw()+
-
-##     theme(## legend.title = element_text(vjust=1,lineheight=1, size=14 ),
-
-##         legend.title = element_text(vjust = 1,lineheight=1,
-##                                     size=14, margin = margin(t = 4.5)),
-##         legend.spacing.y = grid::unit(3, "pt"),
-##         legend.text.align = 0.5,
-          
-##           panel.grid.minor = element_blank(),
-##           plot.title = element_text(lineheight=.8, size=24, face="bold",
-##           vjust=1),legend.text = element_text(vjust=.4,lineheight=1,size = 14 ),
-##           axis.title.x = element_text(size = 20, vjust=1),
-##                 axis.title.y = element_text(size = 20, angle=90, vjust=1),
-##                 axis.text.x = element_text(size=15, colour="black", vjust=1),
-##           axis.text.y = element_text(size=15, colour="black", hjust=1),
-##                           legend.position = legend_coord,
-##            strip.background = element_rect(colour = 'blue',
-##                            fill = 'white', size = 1, linetype=1),
-##                 strip.text.x = element_text(colour = 'red', angle = 0,
-##                                      size = 12, hjust = 0.5,
-##                     vjust = 0.5, face = 'bold'),
-##                    strip.text.y = element_text(colour = 'red', angle = 0,
-##                     size = 12, hjust = 0.5,
-##                     vjust = 0.5, face = 'bold'),
-     
-##           )
-## }
-
-
-
-
-## round_preserve_sum <- function(x, digits = 0) {
-##   up <- 10^digits
-##   x  <-  x * up
-##   y <-  floor(x)
-##   indices <-  tail(order(x-y), round(sum(x, na.rm=T)) - sum(y, na.rm=T))
-##   y[indices] <-  y[indices] + 1
-##   y / up
-## }
-
-
-## ##a function to move a row in a data frame.
-
-## move_row <- function(df, ini_pos, fin_pos){
-
-## ll <- nrow(df)
-    
-## row_pick <- slice(df, ini_pos)
-
-##     if (fin_pos=="last"){
-
-##            res <- df %>%
-##         slice(-ini_pos) %>% 
-##         add_row(row_pick, .before = ll)    
- 
-        
-## } else{
-    
-##     res <- df %>%
-##         slice(-ini_pos) %>% 
-##         add_row(row_pick, .before = fin_pos)    
-## }
-
-##     return(res)
-## }
 
 ############################################################################
 ############################################################################
@@ -190,10 +44,10 @@
 
 
 
-ms3 <- iso_map_eu28 %>%
-    filter(iso3==MS) %>%
-    pull(country) %>%
-    as.character
+ms3 <- iso_map_eu28 |> 
+    filter(iso3==MS) |> 
+    pull(country) |> 
+    as.character()
 
 
 ##  covid_qualifiers <- c( "Covid19-TF",
@@ -202,7 +56,7 @@
 ## )
 
 
-scoreboard <- readRDS("../scoreboard.RDS") %>%
+scoreboard <- readRDS("../scoreboard.RDS") |> 
     filter(!is.na(aid_element_eur)) |> 
     rename("year"="expenditure_year",
            "amount_spent_aid_element_in_eur_million"  ="aid_element_eur",
@@ -213,24 +67,24 @@
     ## mutate(member_state=recode_many(member_state,iso_map$country,
     ##                                 iso_map$iso3 ))
 
-scoreboard_ms <- scoreboard %>%
+scoreboard_ms <- scoreboard |> 
     filter(member_state_3_letter_codes==MS)
 
-year_focus <- scoreboard_ms %>%
-    pull(year) %>%
+year_focus <- scoreboard_ms |> 
+    pull(year) |> 
     max()
 
 
 ini_focus <- year_focus-10
 
 
-cases <- scoreboard_ms %>%
+cases <- scoreboard_ms |> 
     filter(year==max(year),
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0
-           )%>% 
+           ) |> 
     select(member_state_3_letter_codes,case_no, year,amount_spent_aid_element_in_eur_million,
-           procedure_name) %>%
+           procedure_name) |> 
     ## filter(grepl("SA.", case_no)) %>%
     distinct(case_no,.keep_all =T )
 
@@ -238,24 +92,24 @@
 
 
 
-total_amount_eu27 <- scoreboard %>%
+total_amount_eu27 <- scoreboard |> 
     filter(year==max(year),
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0,
            member_state_3_letter_codes %in% iso_map_eu27$iso3
-           ) %>%
+           ) |> 
     summarise(total=sum(amount_spent_aid_element_in_eur_million))
 
 
 
-total_amount_eu27_covid <- scoreboard %>%
+total_amount_eu27_covid <- scoreboard |> 
     filter(year==max(year),
            ## all_intq %in% covid_qualifiers,
            covid==T,
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0,
            member_state_3_letter_codes %in% iso_map_eu27$iso3
-           ) %>%
+           ) |> 
     summarise(total=sum(amount_spent_aid_element_in_eur_million)) |>
     ungroup()
 
@@ -272,7 +126,7 @@
     ungroup()
 
 
-total_amount_MS_covid <- scoreboard %>%
+total_amount_MS_covid <- scoreboard |> 
     filter(year==max(year),
            member_state_3_letter_codes==MS,
            ## all_intq %in% covid_qualifiers,
@@ -280,38 +134,38 @@
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0,
            member_state_3_letter_codes %in% iso_map_eu27$iso3
-           ) %>%
+           ) |> 
     summarise(total=sum(amount_spent_aid_element_in_eur_million)) |>
     ungroup()
 
 
-covid_summary <- total_amount_eu27 %>%
-    rename("total_eu"="total") %>%
+covid_summary <- total_amount_eu27 |> 
+    rename("total_eu"="total") |> 
     mutate(total_eu27_covid=total_amount_eu27_covid$total,
            total_ms=total_amount_MS$total,
-           total_ms_covid=total_amount_MS_covid$total) %>%
+           total_ms_covid=total_amount_MS_covid$total) |> 
     mutate(eu_covid_percentage=total_eu27_covid/total_eu,
            ms_covid_percentage=total_ms_covid/total_ms)
 
-covid_summary_long <- covid_summary %>%
-    select(contains("percentage")) %>%
+covid_summary_long <- covid_summary |> 
+    select(contains("percentage")) |> 
     pivot_longer(cols =  c(eu_covid_percentage ,
                            ms_covid_percentage
-                           ) ,  names_to= "country", values_to="covid_percentage" ) %>%
-    mutate(ll=format_col(covid_percentage*100,1)) %>%
-    mutate(ll=paste(ll, "%", sep="")) %>%
-    arrange(country) %>%
+                           ) ,  names_to= "country", values_to="covid_percentage" ) |> 
+    mutate(ll=format_col(covid_percentage*100,1)) |> 
+    mutate(ll=paste(ll, "%", sep="")) |> 
+    arrange(country) |> 
     mutate(country=fct_inorder(country))
 
 
 
 n_cases <- nrow(cases)
 
-stat_cases <- cases %>%
-    tabyl(procedure_name) %>%
-    mutate(percent=round_preserve_sum(percent*100,1)) %>%
-    add_total() %>% 
-    mutate(percent=format_col(percent,1)) %>% 
+stat_cases <- cases |> 
+    tabyl(procedure_name) |> 
+    mutate(percent=round_preserve_sum(percent*100,1)) |> 
+    add_total() |> 
+    mutate(percent=format_col(percent,1)) |> 
     mutate(percent=paste(percent, "%", sep="")) 
 
 
@@ -326,38 +180,38 @@
 
 
 
-old_cases <- scoreboard %>%
+old_cases <- scoreboard |> 
     filter(year>=ini_focus, year!= year_focus,  member_state_3_letter_codes==MS)
 
 new_cases_list <- setdiff(cases$case_no, old_cases$case_no)
 
-cases_new <- scoreboard_ms %>%
+cases_new <- scoreboard_ms |> 
     filter(case_no %in% new_cases_list ,
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0
-           )%>% 
+           ) |> 
     select(member_state_3_letter_codes,case_no, year,amount_spent_aid_element_in_eur_million,
-           procedure_name) %>%
+           procedure_name) |> 
     ## filter(grepl("SA.", case_no)) %>%
     distinct(case_no,.keep_all =T )
 
-stat_cases_new <- cases_new %>%
-    tabyl(procedure_name) %>%
+stat_cases_new <- cases_new |> 
+    tabyl(procedure_name) |> 
     mutate(percent=round(percent*100,1))
 
 
 if (nrow(stat_cases_new)==0){
-    stat_cases_new <- stat_cases_new %>%
+    stat_cases_new <- stat_cases_new |> 
         add_row(percent=0)
 
     
 }
 
-stat_cases2 <- scoreboard %>%
-    filter(year>=ini_focus, member_state_3_letter_codes==MS)  %>%
-    group_by(year, procedure_name) %>%
-    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million/1e3)) %>%
-    ungroup 
+stat_cases2 <- scoreboard |> 
+    filter(year>=ini_focus, member_state_3_letter_codes==MS) |> 
+    group_by(year, procedure_name) |> 
+    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million/1e3)) |> 
+    ungroup() 
 
 
 ## stat_cases3 <- scoreboard %>%
@@ -375,69 +229,84 @@
 ##     mutate(percent=paste(percent, "%", sep="")) 
 
 
-stat_cases3 <- scoreboard %>%
-    filter(year>=ini_focus, member_state_3_letter_codes==MS)  %>%
+stat_cases3 <- scoreboard |> 
+    filter(year>=ini_focus, member_state_3_letter_codes==MS) |> 
     ## mutate(procedure2=if_else(procedure_name=="General Block Exemption Regulation", "(G)BER", procedure_name)) %>% 
-    group_by( procedure_name) %>%
-    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)/1e3) %>%
-    ungroup  %>%
-    mutate(expenditure=round_preserve_sum(expenditure, 1)) %>%
-    mutate(percent=expenditure/sum(expenditure)*100) %>%
-    mutate(percent=round_preserve_sum(percent,1)) %>%
-    add_total() %>% 
+    group_by( procedure_name) |> 
+    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)/1e3)  |> 
+    ungroup()  |> 
+    mutate(expenditure=round_preserve_sum(expenditure, 1)) |> 
+    mutate(percent=expenditure/sum(expenditure)*100)  |> 
+    mutate(percent=round_preserve_sum(percent,1))  |> 
+    add_total()  |> 
     mutate(percent=format_col(percent,1),
-           expenditure=format_col(expenditure,1)) %>%
-    mutate(percent=paste(percent,"%", sep="")) %>%
+           expenditure=format_col(expenditure,1)) |> 
+    mutate(percent=paste(percent,"%", sep=""))  |> 
     mutate(expenditure=if_else(expenditure!="0.0", expenditure,"less than 0.1"),
            percent=if_else(percent!="0.0%", percent, "less than 0.1%"))
 
 
 
 
-top5 <- cases  %>%
-    group_by(case_no) %>%
+## top5 <- cases  %>%
+##     group_by(case_no) %>%
+##     summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)) %>%
+##     ungroup %>% 
+##     arrange(desc(expenditure)) %>%
+##     mutate(share=expenditure/sum(expenditure)) %>%
+##     slice(1:5) %>%
+##     mutate(cum_share=cumsum(share),
+##            cum_expenditure=cumsum(expenditure)) %>%
+##     filter(expenditure>0)
+
+
+top5 <- scoreboard_ms  |> 
+    filter(year==max(year)) |> 
+    group_by(case_no) |> 
     summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)) %>%
-    ungroup %>% 
-    arrange(desc(expenditure)) %>%
-    mutate(share=expenditure/sum(expenditure)) %>%
-    slice(1:5) %>%
+    ungroup()  |> 
+    arrange(desc(expenditure))  |> 
+    mutate(share=expenditure/sum(expenditure))  |> 
+    slice(1:5)  |> 
     mutate(cum_share=cumsum(share),
-           cum_expenditure=cumsum(expenditure)) %>%
+           cum_expenditure=cumsum(expenditure))  |> 
     filter(expenditure>0)
 
 
-top5_share <- top5 %>%
-    pull(cum_share) %>%
-    max() %>%
-    "*"(100) %>%
+
+
+top5_share <- top5  |> 
+    pull(cum_share)  |> 
+    max()  |> 
+    multiply_by(100)  |> 
     round(1)
 
 
-top5_expenditure <- top5 %>%
-    pull(cum_expenditure) %>%
+top5_expenditure <- top5 |> 
+    pull(cum_expenditure) |> 
     max()
 
 
 
 
-total_expenditure <- scoreboard_ms %>%
-    filter(year>=ini_focus) %>% 
-    pull(amount_spent_aid_element_in_eur_million) %>%
-    sum(na.rm=T) %>% "/"(1e3) %>%
+total_expenditure <- scoreboard_ms |> 
+    filter(year>=ini_focus) |> 
+    pull(amount_spent_aid_element_in_eur_million) |> 
+    sum(na.rm=T)  |>  divide_by(1e3)  |> 
     round(1)
 
-total_expenditure_last <- scoreboard_ms %>%
-    filter(year==year_focus) %>% 
-    pull(amount_spent_aid_element_in_eur_million) %>%
-    sum(na.rm=T) %>% "/"(1e3) %>%
+total_expenditure_last <- scoreboard_ms |> 
+    filter(year==year_focus) |> 
+    pull(amount_spent_aid_element_in_eur_million) |> 
+    sum(na.rm=T)  |> divide_by(1e3) |> 
     round(2)
 
 
-cofinancing <- scoreboard_ms %>%
+cofinancing <- scoreboard_ms |> 
     filter( year==max(year),
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0
-           ) %>%
+           )  |> 
     mutate(expenditure=amount_spent_aid_element_in_eur_million*
                co_financed)
 
@@ -445,9 +314,9 @@
 
 
 
-cofinancing_expenditure <- cofinancing %>%
-    pull(expenditure) %>%
-    sum %>%
+cofinancing_expenditure <- cofinancing |> 
+    pull(expenditure) |> 
+    sum() |> 
     round(0)
 
 
@@ -455,67 +324,67 @@
                            *100,1)
 
 
-cofinancing_objective <- cofinancing %>%
-    group_by(scoreboard_objective) %>%
-    summarise(expenditure_objective=sum(expenditure)) %>%
-    ungroup %>%
-    arrange(desc(expenditure_objective)) %>%
-    mutate(share=expenditure_objective/sum(expenditure_objective)*100) %>%
+cofinancing_objective <- cofinancing |> 
+    group_by(scoreboard_objective) |> 
+    summarise(expenditure_objective=sum(expenditure)) |> 
+    ungroup() |> 
+    arrange(desc(expenditure_objective)) |> 
+    mutate(share=expenditure_objective/sum(expenditure_objective)*100)  |> 
     mutate(share=round_preserve_sum(share,1))
 
 
 
 
-expenditure_by_objective <- scoreboard_ms %>%
+expenditure_by_objective <- scoreboard_ms  |> 
     filter(year==max(year),
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0
-           )%>%
+           ) |> 
     mutate(scoreboard_objective=recode(scoreboard_objective,
-             "Other"="Other policy objectives"       )) %>% 
-    group_by(scoreboard_objective) %>%
-    summarise(expenditure_objective=sum(amount_spent_aid_element_in_eur_million)) %>%
-    ungroup %>%
-    arrange(desc(expenditure_objective)) %>%    
-    mutate(objectives_reduced=if_else(scoreboard_objective %in% scoreboard_objective[1:4], scoreboard_objective, "Other policy objectives" )) %>%
-    group_by(objectives_reduced) %>%
-    summarise(expenditure2=sum(expenditure_objective)) %>%
-    ungroup %>%
-    arrange(desc(expenditure2)) %>%
-    mutate(share=expenditure2/sum(expenditure2)) %>%
-    mutate(share2=round_preserve_sum(share*100,1))  %>%
-    mutate(share_label=paste(as.character(share2), "%", sep="")) %>%
-    move_row(which(.$objectives_reduced=="Other policy objectives"), nrow(.)) %>%
+             "Other"="Other policy objectives"       ))  |> 
+    group_by(scoreboard_objective)  |> 
+    summarise(expenditure_objective=sum(amount_spent_aid_element_in_eur_million)) |> 
+    ungroup() |> 
+    arrange(desc(expenditure_objective)) |> 
+    mutate(objectives_reduced=if_else(scoreboard_objective %in% scoreboard_objective[1:4], scoreboard_objective, "Other policy objectives" )) |> 
+    group_by(objectives_reduced)  |> 
+    summarise(expenditure2=sum(expenditure_objective))  |> 
+    ungroup() |> 
+    arrange(desc(expenditure2))  |> 
+    mutate(share=expenditure2/sum(expenditure2)) |> 
+    mutate(share2=round_preserve_sum(share*100,1))  |> 
+    mutate(share_label=paste(as.character(share2), "%", sep=""))  %>%
+    move_row(which(.$objectives_reduced=="Other policy objectives"), nrow(.))  |> 
     ## mutate(objectives_reduced=wrapper1(objectives_reduced, 25)) %>% 
-    mutate(objectives_reduced=factor(objectives_reduced)) %>%
+    mutate(objectives_reduced=factor(objectives_reduced))  |> 
     mutate(objectives_reduced=fct_inorder(objectives_reduced))
 
-expenditure_gber <- scoreboard_ms %>%
+expenditure_gber <- scoreboard_ms  |> 
     filter(year==max(year),
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0
-           )%>%
-    filter(!is.na(all_objective_names_gber_only)) %>% 
-    group_by(all_objective_names_gber_only) %>%
-    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)) %>%
-    ungroup %>%
-    arrange(desc(expenditure)) %>%
-    mutate(share=expenditure/sum(expenditure)) %>%
+           ) |> 
+    filter(!is.na(all_objective_names_gber_only))  |> 
+    group_by(all_objective_names_gber_only)  |> 
+    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)) |> 
+    ungroup() |> 
+    arrange(desc(expenditure))  |> 
+    mutate(share=expenditure/sum(expenditure))  |> 
     mutate(share2=round_preserve_sum(share*100,1))
 
 
-expenditure_aid <- scoreboard_ms %>%
+expenditure_aid <- scoreboard_ms  |> 
     filter(year==max(year),
            ## duration_end>=max(year),
            amount_spent_aid_element_in_eur_million>0
-           )%>%
-    filter(!is.na(harmonised_aid_instrument))  %>%
-    group_by(harmonised_aid_instrument) %>%
-    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million)) %>%
-    ungroup %>%
-    arrange(desc(expenditure)) %>%
-    mutate(share=expenditure/sum(expenditure)) %>%
-    mutate(share2=round_preserve_sum(share*100,1)) %>%
+           ) |> 
+    filter(!is.na(harmonised_aid_instrument))  |> 
+    group_by(harmonised_aid_instrument)  |> 
+    summarise(expenditure=sum(amount_spent_aid_element_in_eur_million))  |> 
+    ungroup() |> 
+    arrange(desc(expenditure))  |> 
+    mutate(share=expenditure/sum(expenditure)) |> 
+    mutate(share2=round_preserve_sum(share*100,1)) |> 
     mutate(expenditure2=round(expenditure,0))
 
 ```