| Title: | Import Air Quality Monitoring Data in a Fast and Easy Way |
|---|---|
| Description: | A collection of tools to access prepared air quality monitoring data files from web servers with ease and speed. Air quality data are sourced from open and publicly accessible repositories and can be found in these locations: <https://www.eea.europa.eu/data-and-maps/data/airbase-the-european-air-quality-database-8> and <https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm>. The web server space has been provided by Ricardo Energy & Environment. |
| Authors: | Stuart K. Grange [cre, aut] |
| Maintainer: | Stuart K. Grange <[email protected]> |
| License: | GPL-3 | file LICENSE |
| Version: | 0.2.23 |
| Built: | 2025-03-11 05:17:12 UTC |
| Source: | https://github.com/skgrange/saqgetr |
Pseudo-function to re-export magrittr's pipe.
Pseudo-function to re-export dplyr's common functions.
Function to get saqgetr air quality observations.
get_saq_observations( site, variable = NA, start = NA, end = NA, valid_only = FALSE, tz = "UTC", verbose = FALSE )get_saq_observations( site, variable = NA, start = NA, end = NA, valid_only = FALSE, tz = "UTC", verbose = FALSE )
site |
A vector of sites to import. Use get_saq_sites to find what sites are available. |
variable |
An optional variable vector. If not used, all variables will be returned. |
start |
Start date for returned observations. Can either be a date string in
|
end |
End date for returned observations. Can either be a date string in
|
valid_only |
Should only valid observations be kept? |
tz |
Time zone for the observations' dates. |
verbose |
Should the function give messages? |
Tibble.
Stuart K. Grange.
get_saq_sites, saq_clean_observations
# Load a site's data data_hafodyrynys <- get_saq_observations( site = "gb1038a", start = 2018, end = 2018 ) # Print tibble print(data_hafodyrynys) # Get multiple sites nox and ozone data for between a date range data_many <- get_saq_observations( site = c("gb1014a", "gb1044a", "gb1060a"), variable = c("nox", "no2", "o3"), start = 2018, end = 2022, verbose = TRUE ) # Print tibble print(data_many) # Sites and site names data_many %>% dplyr::distinct(site)# Load a site's data data_hafodyrynys <- get_saq_observations( site = "gb1038a", start = 2018, end = 2018 ) # Print tibble print(data_hafodyrynys) # Get multiple sites nox and ozone data for between a date range data_many <- get_saq_observations( site = c("gb1014a", "gb1044a", "gb1060a"), variable = c("nox", "no2", "o3"), start = 2018, end = 2022, verbose = TRUE ) # Print tibble print(data_many) # Sites and site names data_many %>% dplyr::distinct(site)
Function to get air quality time series processes serviced by the saqgetr package.
get_saq_processes(file = NA)get_saq_processes(file = NA)
file |
File of processes helper table. |
Tibble.
Stuart K. Grange.
# Get processes data_processes <- get_saq_processes()# Get processes data_processes <- get_saq_processes()
Function to get simple summaries of air quality observations.
get_saq_simple_summaries(file = NA, summary = "annual_means", tz = "UTC")get_saq_simple_summaries(file = NA, summary = "annual_means", tz = "UTC")
file |
File of simple summaries table. |
summary |
Summary period to import. Can either be |
tz |
Time zone for the observations' dates. |
Tibble.
Stuart K. Grange.
# Import annual means data_annual <- get_saq_simple_summaries(summary = "annual_means") ## Not run: # Import monthly means, quite a large request so will take some time data_month <- get_saq_simple_summaries(summary = "monthly_means") ## End(Not run)# Import annual means data_annual <- get_saq_simple_summaries(summary = "annual_means") ## Not run: # Import monthly means, quite a large request so will take some time data_month <- get_saq_simple_summaries(summary = "monthly_means") ## End(Not run)
Function to import information for monitoring sites/stations/facilities serviced by the saqgetr package.
get_saq_sites(file = NA)get_saq_sites(file = NA)
file |
File of sites helper table. |
Tibble.
Stuart K. Grange.
# Load sites table data_sites <- get_saq_sites()# Load sites table data_sites <- get_saq_sites()
Function to import summary integers for used in the saqgetr package.
get_saq_summaries(file = NA)get_saq_summaries(file = NA)
file |
File of summary helper table. |
Tibble.
Stuart K. Grange.
# Get summary integers data_summary_integers <- get_saq_summaries()# Get summary integers data_summary_integers <- get_saq_summaries()
Function to import validity integers for used in the saqgetr package.
get_saq_validity(file = NA)get_saq_validity(file = NA)
file |
File of validity helper table. |
Tibble.
Stuart K. Grange.
# Get validity integers data_validity_integers <- get_saq_validity()# Get validity integers data_validity_integers <- get_saq_validity()
get_saq_observations function.Function to clean and format observational data from saqgetr's
get_saq_observations function.
saq_clean_observations(df, summary = "hour", valid_only = TRUE, spread = FALSE)saq_clean_observations(df, summary = "hour", valid_only = TRUE, spread = FALSE)
df |
Tibble/data frame from |
summary |
Summary to filter data to. Default is |
valid_only |
Should only valid observations be kept? |
spread |
Should the data be "spread" where the data frame is reshaped so pollutants form variables/columns. This format is usually what is desired when using openair. |
Tibble.
Stuart K. Grange
# Load a site's data data_hafodyrynys <- get_saq_observations( site = "gb1038a", start = 2018, end = 2018 ) # Keep only valid and hourly data data_hafodyrynys_hourly <- data_hafodyrynys %>% saq_clean_observations(summary = "hour", valid_only = TRUE) %>% print() # Spread hourly data, a different table format here data_hafodyrynys_hourly_spread <- data_hafodyrynys %>% saq_clean_observations(summary = "hour", valid_only = TRUE, spread = TRUE) %>% print()# Load a site's data data_hafodyrynys <- get_saq_observations( site = "gb1038a", start = 2018, end = 2018 ) # Keep only valid and hourly data data_hafodyrynys_hourly <- data_hafodyrynys %>% saq_clean_observations(summary = "hour", valid_only = TRUE) %>% print() # Spread hourly data, a different table format here data_hafodyrynys_hourly_spread <- data_hafodyrynys %>% saq_clean_observations(summary = "hour", valid_only = TRUE, spread = TRUE) %>% print()
Functions for time zone strings.
tz_central() tz_eastern()tz_central() tz_eastern()
Stuart K. Grange
Squash the global variable notes when building a package.