Connect_R_to_SQL_DB

Loading packages

.libPaths("C:/Wolfram_Admin/R-4.1.1/library")
#install.packages(c("odbc","DBI", "RSQLite", "dbplyr", "tidyverse"))
library("odbc")
library("DBI")
library("RSQLite")
library("dbplyr")
library("tidyverse")

## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --

## v ggplot2 3.3.5     v purrr   0.3.4
## v tibble  3.1.4     v dplyr   1.0.7
## v tidyr   1.1.3     v stringr 1.4.0
## v readr   2.0.1     v forcats 0.5.1

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::ident()  masks dbplyr::ident()
## x dplyr::lag()    masks stats::lag()
## x dplyr::sql()    masks dbplyr::sql()

Establishing the connection to the database

Database name: CIFOS_model_WJS Schema: cifos_crop

con <- dbConnect(odbc::odbc(), 
                 .connection_string = "Driver={MySQL ODBC 8.0 Unicode Driver};",
                 Server = "localhost", Database = "cifos_crop", UID = "root", PWD = "154236w.S",
                 Port = 3306)

Crops

source(“Functions_cifos/function_collection.R”)

Countries

Soil

Agroeclological zones

Zones (AEZ, Soil, Adm0)

Land use type

Ndeposition

Emission factors

Defined target views/tables (Anita and Hannah)

Yield scneario

dat_current_potential_zon=read_csv(“Input_data/Yield_scenario_debug.csv”)

CountryZone_Area_Scenarios

LUT_area = read_csv(“Input_data/LUT_all.csv”)

Pasture_Area

LUT_area_pasture=read.csv(“Input_data/LUT_crop_pasture_area.csv”)

Area_Yield_Baseline

Baseline_yield_area=read_csv(“Input_data/Area_Yield_Baseline.csv”)

Area_Yield_Potential

Suitable_yield_area= read_csv(“Input_data/Suitable_yield_area.csv”)

s