nicolasfstgelais / dbExtract

Function to extract data from water quality databases

dbExtract: aggregate water quality databases

dbExtract is a package to extract data from water quality databases and create an aggregated database based on keywords.

Install

You can install the development version version from gitHub

install.packages("devtools")
devtools::install_github("nicolasfstgelais/dbExtract")

Using dbExtract

Load the package:

library("dbExtract")

Initialize file structure

dbExtract_init()

dbExtract() is based on a specific structure of files to initialize (with examples) the folder structure run the dbExtract_init(). If thedirectory where you want to initialize dbExtract is different from the working directory, change the working directory using setwd(path). We highly recommand to run all the dbExtract functions from a R project created within the working directory.

Add a dataset

Datasets should be added in the raw folder (see data README for details)

Extract and merge data

dbExtract() can be use to extract and merge data from multiple locations, coming from multiple databases. The dbExtract() function look for specifc keywords in each database (in wide or long format) based on the keyword in raw/inputs/categories.csv (see input README for details on how to fill the categories file).

For data with temporal replication

(see input README for details)

dbExtract_init(inputFile = "temporalDB.csv")

For data without temporal replication

(see input README for details)

dbExtract_init(inputFile = "stationsDB.csv")

Prepare data

dataPrep(stationsPath="data/dbExtract_stationsDB.csv",guidePath="raw/criteria/guidelines.csv",temporalPath="data/dbExtract_temporalDB.csv",by="ym") to *data/temporalDBwide.csv"

This function prepare the different data source needed for the classification step. First the guidelines.csv is normalized. Units are checked in the dbExtract_temporalDB.csv and the data is summarized either by date (by="d"), year+month (by="ym") or month by="m") and exported in a wide format

Classify sites

sitesClassification(temporalPath="data/temporalDBwide.csv",selSpaces=c("irrigation","livestock","drink","aquatic","recreational","oligotrophic","mesotrophic","eutrophic")

sitesClassification() evaluate for each service seleted in the selSpaces argument (by default irrigation, livestock, drink, aquatic, recreational, oligotrophic, mesotrophic et eutrophic) based on the temporal database