Commit: e946b59fa3b62251c486fe1185eb50a34c80cdcf - myprojects-hg-reborn (hg)

Commit MetaInfo

• Revisión: e946b59fa3b62251c486fe1185eb50a34c80cdcf (tree)
• Tiempo: 2023-05-05 19:27:18
• Autor: Lorenzo Isella <lorenzo.isella@gmai...>
• Commiter: Lorenzo Isella

Log Message

I now use also another file for the used and approuved aid.

Cambiar Resumen

• modified: R-codes/create_csv_sdmx.R

Diferencia incremental

diff -r aaf0cf2df644 -r e946b59fa3b6 R-codes/create_csv_sdmx.R
--- a/R-codes/create_csv_sdmx.R	Mon Apr 24 11:09:10 2023 +0200
+++ b/R-codes/create_csv_sdmx.R	Fri May 05 12:27:18 2023 +0200
@@ -423,6 +423,48 @@
            "GEO"="iso2")
 
 
+
+## df_gber_objective_up <- df %>%
+##     ## filter(!is.na(all_objective_names_gber_only)) %>%
+
+##     mutate(amount_spent_aid_element_in_eur_million=if_else(!is.na(all_objective_names_gber_only),amount_spent_aid_element_in_eur_million, 0 )) %>%
+
+##     mutate(aid_element_as_percent_national_gdp=if_else(!is.na(all_objective_names_gber_only),aid_element_as_percent_national_gdp, 0 )) %>%
+
+##     mutate(aid_element_eur_adj=if_else(!is.na(all_objective_names_gber_only),aid_element_eur_adj, 0 )) %>%
+    
+##     mutate(all_objective_names_gber_only=
+##                recode(all_objective_names_gber_only,
+##  "Transport costs of goods in eligible areas (Art. 15(2))"=                     "Transport costs of goods in eligible areas (Art. 15(2)(a))"
+##                           )) %>% 
+##     group_by(year, iso2, all_objective_names_gber_only) %>%
+##     summarise(value=sum(amount_spent_aid_element_in_eur_million, na.rm=T),
+##               pc_gdp=sum(aid_element_as_percent_national_gdp, na.rm=T),
+##               value_adj=sum(aid_element_eur_adj, na.rm=T)
+##            ) %>%
+##     ungroup %>%
+##     ## left_join(y=gdp, by=c("year"="time_period",
+##     ##                       "iso2"="geo")) %>%
+##     ## mutate(pc_gdp=value/obs_value*100) %>%
+##     group_by(year, iso2) %>% 
+##     mutate(value=round_preserve_sum(value,2),
+##            pc_gdp=round_preserve_sum(pc_gdp,2),
+##            value_adj=round_preserve_sum(value_adj,2)) %>%
+##     group_modify(~ .x %>%
+##                      adorn_totals("row", fill="Total"))  %>%
+##     ungroup  %>%
+##     ## select(-obs_value) %>%
+##     mutate(DATAFLOW="COMP:AID_SCB_TYPE(1.0)",
+##            FREQ="A") %>%
+##     rename("MIO_EUR"="value",
+##            "PC_GDP"="pc_gdp",
+##            "MIO_EUR_ADJ"="value_adj") %>% 
+##     pivot_longer(cols=c(PC_GDP, MIO_EUR, MIO_EUR_ADJ), names_to="UNIT",
+##                  values_to="OBS_VALUE")  %>%
+##     rename("TIME_PERIOD"="year",
+##            "GEO"="iso2")
+
+
 ## objectives_gber <- read_csv("CL_OBJ_GBER+COMP+1.0.csv") %>%
 ##     clean_data()
 
@@ -947,7 +989,30 @@
            INST_FI,TIME_PERIOD, OBS_VALUE) 
 
 
-    used_13 <- bind_rows(used1, used2, used3) |>
+
+used4 <- read_csv("other_used2.csv") %>%
+    rename("country"="Member State") %>%
+    mutate(country=recode(country, "Czech Republic"="Czechia")) %>% 
+    mutate(UNIT="MIO_EUR", FREQ="A") %>%
+    pivot_longer(cols=starts_with("2"),
+                 names_to="TIME_PERIOD",
+                 values_to="OBS_VALUE") %>%
+    mutate(TIME_PERIOD=as.numeric(TIME_PERIOD),
+           OBS_VALUE=as.numeric(OBS_VALUE)) %>%
+    na_num_to_pattern(0)  %>%
+    mutate(INST_FI="INST4") %>%
+    left_join(y=iso_map_eu28, by="country") %>%
+    rename("GEO"="iso2") %>%
+    mutate(DATAFLOW="COMP:AID_FI_USED(1.0)") %>% 
+    complete(GEO, UNIT, INST_FI,
+             DATAFLOW, FREQ, TIME_PERIOD, fill=list(OBS_VALUE=0)) %>%
+    select(DATAFLOW, FREQ, GEO,UNIT,
+           INST_FI,TIME_PERIOD, OBS_VALUE) 
+
+
+
+
+    used_13 <- bind_rows(used1, used2, used3, used4) |>
         filter(GEO!="UK") ## this year I remove the UK
 
 used_total <- used_13 %>%
@@ -973,7 +1038,8 @@
 
 
 df_used_finance_fin_save <- df_used_finance_fin%>%
-    mutate(OBS_VALUE=format_col(OBS_VALUE,2,""))
+    mutate(OBS_VALUE=format_col(OBS_VALUE,2,"")) |>
+    filter(GEO!="UK")
 
 write_csv(df_used_finance_fin_save, "./finance_used/aid_fi_used+COMP+3.0.sdmx.csv")
 write_tsv(df_used_finance_fin_save, "./finance_used/aid_fi_used+COMP+3.0.sdmx.tsv")
@@ -1049,7 +1115,31 @@
            INST_FI,TIME_PERIOD, OBS_VALUE) 
 
 
-used_13 <- bind_rows(used1, used2, used3)
+
+used4 <- read_csv("other_approuved2.csv") %>%
+    rename("country"="Member State") %>%
+    mutate(country=recode(country, "Czech Republic"="Czechia")) %>% 
+    mutate(UNIT="MIO_EUR", FREQ="A") %>%
+    pivot_longer(cols=starts_with("2"),
+                 names_to="TIME_PERIOD",
+                 values_to="OBS_VALUE") %>%
+    mutate(TIME_PERIOD=as.numeric(TIME_PERIOD),
+           OBS_VALUE=as.numeric(OBS_VALUE)) %>%
+    na_num_to_pattern(0)  %>%
+    mutate(INST_FI="INST4") %>%
+    left_join(y=iso_map_eu28, by="country") %>%
+    rename("GEO"="iso2") %>%
+    mutate(DATAFLOW="COMP:AID_FI_APPROVED(1.0)") %>% 
+    complete(GEO, UNIT, INST_FI,
+             DATAFLOW, FREQ, TIME_PERIOD, fill=list(OBS_VALUE=0)) %>%
+    select(DATAFLOW, FREQ, GEO,UNIT,
+           INST_FI,TIME_PERIOD, OBS_VALUE) 
+
+
+
+
+
+used_13 <- bind_rows(used1, used2, used3, used4)
 
 used_total <- used_13 %>%
     group_by(DATAFLOW, FREQ, GEO, UNIT, TIME_PERIOD  ) %>%
@@ -1075,7 +1165,8 @@
 
 
 df_approved_finance_fin_save <- df_approved_finance_fin %>%
-    mutate(OBS_VALUE=format_col(OBS_VALUE,2,""))
+    mutate(OBS_VALUE=format_col(OBS_VALUE,2,"")) |>
+    filter(GEO!="UK")
 
 
 write_csv(df_approved_finance_fin_save, "./finance_approuved/aid_fi_approved+COMP+3.0.sdmx.csv")