Commit: e77d3859a5ff38494417b61d5544f5bf69462d02 - myprojects-hg-reborn (hg)

Commit MetaInfo

• Revision: e77d3859a5ff38494417b61d5544f5bf69462d02 (tree)
• Time: 2024-04-24 18:39:37
• Author: Lorenzo Isella <lorenzo.isella@gmai...>
• Commiter: Lorenzo Isella

Log Message

A simple script to get SMEs and broadband statistics from the scoreboard.

Change Summary

• add: R-codes/smes-risk.R

Incremental Difference

diff -r 651d887893b6 -r e77d3859a5ff R-codes/smes-risk.R
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/R-codes/smes-risk.R	Wed Apr 24 11:39:37 2024 +0200
@@ -0,0 +1,107 @@
+rm(list=ls())
+
+library(tidyverse)
+library(janitor)
+library(openxlsx)
+
+source("/home/lorenzo/myprojects-hg/R-codes/stat_lib.R")
+
+
+df <- readRDS("../scoreboard.RDS")
+
+df_obj_gber <- df |>
+    filter(expenditure_year==max(expenditure_year)) |>
+    find_text_filter_col(case_type, "(?i)exemption") |> 
+    group_by(scoreboard_objective, expenditure_year ) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |> 
+    arrange(expenditure_year, desc(expenditure_mio_eur ))
+
+save_excel(df_obj_gber, "scoreboard_gber_smes.xlsx", "GBER expenditure")
+
+
+
+df_obj_non_gber <- df |>
+    filter(expenditure_year==max(expenditure_year)) |>
+    find_text_filter_col(case_type, "(?i)notified") |> 
+    group_by(scoreboard_objective, expenditure_year ) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |> 
+    arrange(expenditure_year, desc(expenditure_mio_eur ))
+
+save_excel(df_obj_non_gber, "scoreboard_gber_smes.xlsx", "non-GBER expenditure")
+
+
+df_obj <- df |>
+    filter(## is.na(gber_section),
+           expenditure_year==max(expenditure_year)) |> 
+    group_by(scoreboard_objective, expenditure_year ) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |> 
+    arrange(expenditure_year, desc(expenditure_mio_eur ))
+
+
+save_excel(df_obj, "scoreboard_gber_smes.xlsx", "Total expenditure")
+
+####################################################################
+####################################################################
+####################################################################
+
+
+df_band <- df |>
+    filter(expenditure_year>=2011) |>
+    find_text_filter_col(all_intq , "(?i)broadband")
+
+df_band_year <- df_band |>
+    group_by(expenditure_year) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |>
+    arrange(expenditure_year)
+
+
+df_band_year_ms <- df_band |>
+    group_by(expenditure_year, member_state) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |>
+    arrange(expenditure_year, member_state)
+
+
+
+df_band_year_case_type <- df_band |>
+    group_by(expenditure_year, case_type) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |>
+    arrange(expenditure_year, case_type)
+
+
+df_band_year_obj <- df_band |>
+    group_by(expenditure_year, scoreboard_objective) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |>
+    arrange(expenditure_year, scoreboard_objective)
+
+
+
+df_band_year_obj_gber <- df_band |>
+    group_by(expenditure_year, primary_objective, all_gber_obj) |>
+    summarise(expenditure_mio_eur=sum(aid_element_eur, na.rm=T)) |>
+    ungroup() |>
+    arrange(expenditure_year,primary_objective, all_gber_obj)
+
+
+save_excel(df_band_year, "broadband.xlsx" ,"expenditure_year")
+
+save_excel(df_band_year_ms, "broadband.xlsx", "expenditure_year_MS")
+
+save_excel(df_band_year_case_type, "broadband.xlsx", "expenditure_year_case")
+
+save_excel(df_band_year_obj, "broadband.xlsx", "expenditure_year_objective")
+
+save_excel(df_band_year_obj_gber, "broadband.xlsx", "expenditure_year_primary_gber")
+
+
+
+
+
+
+print("So far so good")