## ----setup, include=FALSE, cache=FALSE---------------------------------------- library("knitr") opts_chunk$set(fig.path='figure/', fig.align='center', fig.show='hold', warning=FALSE, message=FALSE, tidy=FALSE, results='hide', eval=FALSE, concordance=TRUE) options(replace.assign=TRUE,width=80) ## ----Install the FAOSTAT package - CRAN--------------------------------------- # if(!is.element("FAOSTAT", .packages(all.available = TRUE))) # install.packages("FAOSTAT") # library(FAOSTAT) ## ----Install the FAOSTAT package - git repo----------------------------------- # if(!is.element("FAOSTAT", .packages(all.available = TRUE))) # remotes::install_gitlab(repo="paulrougieux/faostatpackage/FAOSTAT") # library(FAOSTAT) ## ----Vignette----------------------------------------------------------------- # help(package = "FAOSTAT") # vignette("FAOSTAT", package = "FAOSTAT") ## ----FAO-bulk-url, eval=FALSE------------------------------------------------- # library(FAOSTAT) # df <- get_faostat_bulk_url("https://bulks-faostat.fao.org/production/Inputs_LandUse_E_All_Data_(Normalized).zip", # data_folder = "data_raw") ## ----FAO-read-fao, eval=FALSE------------------------------------------------- # # Get data for Cropland (6620) Area (5110) in Antigua and Barbuda (8) in 2017 # df = read_fao(area_codes = "8", element_codes = "5110", item_codes = "6620", year_codes = "2017") # # Load cropland area for a range of years # df = read_fao(area_codes = "106", element_codes = "5110", item_codes = "6620", year_codes = 2010:2020) ## ----FAO-search1, eval=FALSE-------------------------------------------------- # library(FAOSTAT) # # Create a folder to store the data # data_folder <- "data_raw" # dir.create(data_folder) # # # Login to the API -- creates an access token # faostat_login() # # # Load information about all datasets into a data frame # fao_metadata <- FAOsearch() # # # Find datasets whose titles contain the word "crop" # FAOsearch(dataset="crop", full = FALSE) # # # Load crop production data # crop_production <- get_faostat_bulk(code = "QCL", data_folder = data_folder) # # Show the structure of the data # str(crop_production) # # # Cache the file in the serialized RDS format for fast reuse later. # saveRDS(crop_production, "data_raw/crop_production_e_all_data.rds") # # Load your local version of the data from the RDS file # crop_production <- readRDS("data_raw/crop_production_e_all_data.rds") ## ----FAO-check, eval=FALSE---------------------------------------------------- # FAOchecked.df = FAOcheck(var = FAOquery.df$varName, year = "Year", # data = FAO.lst$entity, type = "multiChina", # take = "simpleCheck") ## ----WB-download, eval=FALSE-------------------------------------------------- # ## Download World Bank data and meta-data # WB.lst = getWDItoSYB(indicator = c("SP.POP.TOTL", "NY.GDP.MKTP.CD"), # name = c("totalPopulation", "GDPUSD"), # getMetaData = TRUE, printMetaData = TRUE) ## ----fill-countrycode, eval=FALSE-------------------------------------------- # ## Just a demonstration # Demo = WB.lst$entity[, c("Country", "Year", "totalPopulation")] # demoResult = fillCountryCode(country = "Country", data = Demo, # outCode = "ISO2_WB_CODE") # # ## Countries have not been filled in. # unique(demoResult[is.na(demoResult$ISO2_WB_CODE), "Country"]) ## ----translate, warning=TRUE, eval=FALSE------------------------------------- # ## Countries which are not listed under the ISO2 international standard. # FAO.df = translateCountryCode(data = FAOchecked.df, from = "FAOST_CODE", # to = "ISO2_CODE") # # ## Countries which are not listed under the UN M49 system. # WB.df = translateCountryCode(data = WB.lst$entity, from = "ISO2_WB_CODE", # to = "UN_CODE") ## ----merge, warning=TRUE, eval=FALSE----------------------------------------- # merged.df = mergeSYB(FAOchecked.df, WB.lst$entity, outCode = "FAOST_CODE") ## ----FAO-search2, eval=FALSE-------------------------------------------------- # library(tidyr) # # Reuse the data folder created above # data_folder <- "data_raw" # dir.create(data_folder) # # # Load food balance data # fbs <- get_faostat_bulk("FBS", data_folder) # # # Reshape to wide format # fbs_wide <- pivot_wider(fbs, names_from=year, values_from=value) ## ----Scale to basic unit, eval=FALSE------------------------------------------ # multipliers = data.frame(Variable = c("arableLand", "cerealExp", "cerealProd", # "totalPopulation", "GDPUSD"), # Multipliers = c("thousand", NA, NA, NA, NA), # stringsAsFactors = FALSE) # multipliers[, "Multipliers"] = # as.numeric(translateUnit(multipliers[, "Multipliers"])) # preConstr.df = scaleUnit(merged.df, multipliers) ## ----Construction, eval=FALSE------------------------------------------------- # con.df = data.frame(STS_ID = c("arableLandPC", "arableLandShareOfTotal", # "totalPopulationGeoGR", "totalPopulationLsGR", # "totalPopulationInd", "totalPopulationCh"), # STS_ID_CONSTR1 = c(rep("arableLand", 2), # rep("totalPopulation", 4)), # STS_ID_CONSTR2 = c("totalPopulation", NA, NA, NA, NA, NA), # STS_ID_WEIGHT = rep("totalPopulation", 6), # CONSTRUCTION_TYPE = c("share", "share", "growth", "growth", # "index", "change"), # GROWTH_RATE_FREQ = c(NA, NA, 10, 10, NA, 1), # GROWTH_TYPE = c(NA, NA, "geo", "ls", NA, NA), # BASE_YEAR = c(NA, NA, NA, NA, 2000, NA), # AGGREGATION = rep("weighted.mean", 6), # THRESHOLD_PROP = rep(60, 6), # stringsAsFactors = FALSE) # # postConstr.lst = with(con.df, # constructSYB(data = preConstr.df, # origVar1 = STS_ID_CONSTR1, # origVar2 = STS_ID_CONSTR2, # newVarName = STS_ID, # constructType = CONSTRUCTION_TYPE, # grFreq = GROWTH_RATE_FREQ, # grType = GROWTH_TYPE, # baseYear = BASE_YEAR)) ## ----aggregation, eval=FALSE-------------------------------------------------- # ## Compute aggregates under the FAO continental region. # relation.df = FAOregionProfile[, c("FAOST_CODE", "UNSD_MACRO_REG")] # # Macroregion.df = Aggregation(data = postConstr.lst$data, # relationDF = relation.df, # aggVar = c("arableLand", "totalPopulation", # "arableLandPC"), # weightVar = c(NA, NA, "totalPopulation"), # aggMethod = c("sum", "sum", "weighted.mean"), # applyRules = TRUE, # keepUnspecified = TRUE, # unspecifiedCode = "NotClassified", # thresholdProp = c(rep(0.65,3)))