In SWS-Methodology/faoswsIndustrial: Package to perform the imputation of industrial data

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About this document

This vignette is a detailed guide of the various data sources used in the Industrial Use.

## Load required functions
library(data.table)
library(knitr)
library(igraph)

1 Data Sources

1.1 Flow Chart

Description of how the Industrial Use works

1.2 Example of tables

• usda domain, usda_psd dataset. In this table there are the vegetables oils data by country and year provided by the United States Department of Agriculture.

d=data.table(geographicUsda=c("CA", "CA", "CA", "CH", "CH", "CH"), measuredElementPsd=140.08, 
measuredItemPsd=c("4239100", "4239100", "4239100", "0813100", "0813100", "0813100"),
timePointYears = rep(c(2015, 2014, 2013), 2), Value=c(120, 108, 85, 1000, 980, 960))
kable(d, format = "markdown", padding = 0)

• industrialUse domain, biofuel dataset. In this table there are the biofuels (such as maize) by country and year.

d=data.table(geographicAreaM49=112, measuredItemCPC="01801", 
timePointYears = seq(2000, 2005), Value=c(39.63288, 40.95939, 42.25281, 43.67861, 44.90584, 46.82236),
flagObservationStatus_measuredElement_5150 = "",
flagMethod_measuredElement_5150 = "")
kable(d, format = "markdown", padding = 0)

2 Process of Industrial Use

1. to pull the vegetables oils data by country and year provided by the United States Department of Agriculture and stored in usda/usda_psd. The values are in 1000 MT. We have to convert the country code provided by USDA to m49 country codes and the item psd to cpc codes as well. There are two datasets mapping these codes and they are stored on SWS Datatables. You find the oilseed data set in this link: https://apps.fas.usda.gov/psdonline/psdDownload.aspx

d=data.table(geographicUsda=c("CA", "CA", "CA", "CH", "CH", "CH"), measuredElementPsd=140.08, 
measuredItemPsd=c("4239100", "4239100", "4239100", "0813100", "0813100", "0813100"),
timePointYears = rep(c(2015, 2014, 2013), 2), Value=c(120, 108, 85, 1000, 980, 960))
kable(d, format = "markdown", padding = 0)

1. to pull the biofuels data by country and year provided by the OECD-FAO (Make double check) and stored in industrialUse/biofuel. The values are in tonnes.

d=data.table(geographicAreaM49=112, measuredItemCPC="01801", 
timePointYears = seq(2000, 2005), Value=c(39.63288, 40.95939, 42.25281, 43.67861, 44.90584, 46.82236),
flagObservationStatus_measuredElement_5150 = "",
flagMethod_measuredElement_5150 = "")
kable(d, format = "markdown", padding = 0)

1. to merge both datasets by country/year/cpc and calculate the quantity of industrial utilization. This quantity is just the sum of both values from each table. It's relevant to say that we have to convert the values from the second dataset to 1000 MT multiplying by 1,000. This dataset was saved in domain = "agriculture", dataset = "aproduction", data = industrialUsesData.

d=data.table(geographicUsda=100, measuredItemCPC=2163, 
timePointYears = seq(1992, 1997), 
measuredElement = "5195",
Value=c(15000, 39000, 62000, 57000, 45000, 25000),
flagObservationStatus = "I",
flagMethod = "e")
kable(d, format = "markdown", padding = 0)

SWS-Methodology/faoswsIndustrial documentation built on May 9, 2019, 11:48 a.m.