From a7df76d46c34c9178e7b70be23cbd9709a5c6fb4 Mon Sep 17 00:00:00 2001 From: "WUR\\simon083" <wolfram.simon@wur.nl> Date: Fri, 4 Feb 2022 19:38:27 +0100 Subject: [PATCH] deleted weired headers --- R_to_SQL_database/Cifos_Model_Data_EU.R | 45 ++----------------------- 1 file changed, 3 insertions(+), 42 deletions(-) diff --git a/R_to_SQL_database/Cifos_Model_Data_EU.R b/R_to_SQL_database/Cifos_Model_Data_EU.R index ea575a3..caa8e80 100644 --- a/R_to_SQL_database/Cifos_Model_Data_EU.R +++ b/R_to_SQL_database/Cifos_Model_Data_EU.R @@ -1,15 +1,12 @@ -Loading packages -------------------------------------------------------- + +# Loading packages -------------------------------------------------------- # Loading the packages # .libPaths("C:/Wolfram_Admin/R-4.1.2/R-4.1.2/library") # install.packages("easypackages", dependencies = T) # library("easypackages") # Loading packages easypackages::packages("odbc","DBI", "RSQLite", "dbplyr", "readxl", "fuzzyjoin", -<<<<<<< HEAD - "sqldf", "downloader", "tidyverse", "janitor", "FAOSTAT", -======= "sqldf", "downloader", "tidyverse", "janitor", "FAOSTAT", ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 "validate") # https://www.youtube.com/watch?v=CydajdNRJOU ----------------------------- @@ -247,7 +244,7 @@ dat_crop_final = read_csv("Input_data/dat_crop_with_grass_final.csv") %>% # Adding the grass to the old crop name columns so it will not result in NA later. dplyr::mutate(old_cifos_crop = case_when(is.na(old_cifos_crop) ~ crop_cifos, TRUE ~ old_cifos_crop)) - + # Fuzzy join of processing sheet and the crop map # crop_map_cifos_procraw = dat_proc = Processing_sheet %>% @@ -508,11 +505,7 @@ proc_new = tibble("crop_cifos" = NA, "proc_raw" = NA, "proc_in" = NA, "proc_out" add_row(crop_cifos = "cassava" , proc_raw = "cassava" , proc_in = "cassava_tapiocain", proc_out = "cassava_tapioca", value = 0.2, dietary_products = "Cassava and products") %>% add_row(crop_cifos = "cassava" , proc_raw = "cassava" , proc_in = "cassava_dryin", proc_out = "cassava_dry", value = 0.35, dietary_products = "Cassava and products") %>% add_row(crop_cifos = "cassava" , proc_raw = "cassava" , proc_in = "cassava_starchin", proc_out = "cassava_starch", value = 0.25, dietary_products = "Cassava and products") %>% -<<<<<<< HEAD - -======= ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 # Pearl millet -- Source: from Technical Conversion Factors for Agricultural Commodities (http://countrystat.org/resources/documents/tcf.pdf); adjusted commodity tree; fractions from "cereals/millet" # levels: only one level add_row(crop_cifos = "pearl_millet" , proc_raw = "pearl_millet" , proc_in = "pearl_millet_flourin", proc_out = "pearl_millet_flour", value = 0.86, dietary_products = "Millet and products") %>% @@ -870,21 +863,6 @@ dat_proc_asf = clean_names() %>% rename(proc_raw = pro_raw) %>% slice(269:363) %>% dplyr::mutate(dietary_products= case_when(proc_raw == "Milk" ~ "Milk - Excluding Butter", -<<<<<<< HEAD - TRUE ~ dietary_products), - dietary_products= case_when(proc_out == "Butter" ~ "Butter, Ghee", - TRUE ~ dietary_products), - dietary_products= case_when(dietary_products == "Fish (Calculated CiFoS)" ~ "Fish, Seafood", - TRUE ~ dietary_products), - proc_out = case_when(proc_out == "Butter_Milk" ~ "Butter_milk", - TRUE ~ proc_out)) #this was written with a uppercase here and a lower case in the food losses sheet - - - -Processing_sheet_final = bind_rows(dat_proc_new %>% dplyr::select(-crop_cifos),dat_proc_asf) -write_csv(Processing_sheet_final, "Input_data/processing_sheet.csv") - -======= TRUE ~ dietary_products), dietary_products= case_when(proc_out == "Butter" ~ "Butter, Ghee", TRUE ~ dietary_products), @@ -898,7 +876,6 @@ write_csv(Processing_sheet_final, "Input_data/processing_sheet.csv") Processing_sheet_final = bind_rows(dat_proc_new %>% dplyr::select(-crop_cifos),dat_proc_asf) write_csv(Processing_sheet_final, "Input_data/processing_sheet.csv") ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 # Human nutrition sheet --------------------------------------------------- # Human nutrtion sheet @@ -1007,11 +984,7 @@ hum_nutr_all = bind_rows(food_old_match, food_psf_new, food_asf) # check = full_join(hum_nutr_all, proc_new, by = c("product"="proc_out")) write_csv(hum_nutr_all, "Input_data/hum_nutr_all.csv") -<<<<<<< HEAD - -======= ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 # Animal nutrition new ---------------------------------------------------- # Cifos sheet @@ -2159,11 +2132,7 @@ crop_other_new = distinct_at(vars(crop_cifos),.keep_all = T) %>% drop_na(crop_cifos) write_csv(crop_other_new, "Input_Data/crop_other_new.csv") -<<<<<<< HEAD - -======= ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 # cropnutr = read_excel('C:/Wolfram_Admin/GAMS/EU_model_frmSep21/cifos-model_eu/European_CiFoS_model_data.xlsx',sheet="CropNutr") # write_csv(cropnutr,"Input_data/cropnutr_old") cropnutr = read_csv("Input_data/cropnutr_old") @@ -2174,13 +2143,8 @@ cropnutr_new = full_join(crop_map %>% dplyr::select(old_cifos_crop, crop_cifos), by = c("crop_cifos_old"="old_cifos_crop")) %>% relocate(crop_cifos, .before = crop_cifos_old) %>% dplyr::select(-crop_cifos_old) -<<<<<<< HEAD - - write_csv(cropnutr_new, "Input_data/cropnutr_new.csv") -======= write_csv(cropnutr_new, "Input_data/cropnutr_new.csv") ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 # CropFert_New NOT DONE! ------------------------------------------------------------ # CropFert_New = read_excel("C:/Wolfram_Admin/GAMS/EU_model_frmSep21/cifos-model_eu/European_CiFoS_model_data.xlsx", sheet = "CropFert_New") @@ -2311,7 +2275,6 @@ write_csv(animal_map, "Input_Data/diets_animal_crop_datamap.csv") # # Animals # #Animal_yield sheet # 1. Yields (column D row 2) -<<<<<<< HEAD @@ -2323,5 +2286,3 @@ write_csv(animal_map, "Input_Data/diets_animal_crop_datamap.csv") -======= ->>>>>>> bdd608029dd5899a8a1a0b93359f2d957d331ba1 -- GitLab