relates to GWELLS-QAQC-RShiny-Dashboard Github repo (https://github.com/bcgov/GWELLS-QAQC-RShiny-Dashboard)
The purpose of the code in this repo is to maintain 3 files derived from the the gwells.csv file provided by the Government of British-Columbia.
Three CSVs appear in the data/
folder. They are all updated on a daily basis:
wells.csv
is an identical copy of the gwells.csv
with an additional column: date_added
. This column represents the first date a well was spotted by this script.
-
wells_geocoded.csv
is the result of passing thewells.csv
through thepython gwells_locationqa geocode
python script from the bcgov/GWELLS_LocationQA repo. -
wells_qa.csv
is the result of passingwells.csv
andwells_geocoded.csv
through thepython gwells_locationqa qa
python script from the bcgov/GWELLS_LocationQA repo.
The daily updates occur daily thanks to scheduled github actions at depends on the Docker Image created specifically for this project. The image was tailored to include all the R, Python and spatial dependencies required to run the Python scripts created by Simon Norris and build on the rocker/geospatial:4.1.2
docker image.
The three CSVs will then be used to feed the shiny app (code) created for this Code With Us project.
Here is a diagram of the whole process:
We recognize that it would have been better practice to save this data in an SQL table instead of a CSV inside a github repo. We built the code for this purpose, which is why most files in this repository exist in two copies: one with a "_csv" suffix and another with the "_sql" suffix. Due to cost issue, it was decided to use the CSV approach. The _sql code was kept in this repo in case this approach is retained in the future.
This repo was originally created by Simon Coulombe during a "Code With Us" opportunity in January 2022.