pas_enhanceRawData: Enhance synoptic data from PurpleAir

In MazamaScience/AirSensor2: Process and Display Data from Air Quality Sensors

Enhance synoptic data from PurpleAir

Description

Enhance raw synoptic data from PurpleAir to create an improved dataframe compatible with the MazamaLocationUtils package.

Steps include:

1) Replace variable names with more consistent, human readable names.

2) Add spatial metadata for each sensor including:

• timezone – Olson timezone

• countryCode – ISO 3166-1 alpha-2

• stateCode – ISO 3166-2 alpha-2

3) Convert data types from character to POSIXct and numeric.

4) Add additional metadata items:

• sensorManufacturer = "PurpleAir"

Limiting spatial searches by country can greatly speed up the process of enhancement. This is performed by providing a vector of ISO country codes to the countryCodes argument. By default, no subsetting is performed.

Users may further improve performance by also specifying stateCodes when countryCodes is limited to a single country.

When a single US state is specified, named counties may be specified to further speed up performance.

Usage

pas_enhanceRawData(
  pas_raw = NULL,
  countryCodes = "US",
  stateCodes = NULL,
  counties = NULL
)

Arguments

pas_raw	Dataframe returned by pas_downloadParseRawData.
countryCodes	ISO 3166-1 alpha-2 country codes used to subset the data.
stateCodes	ISO-3166-2 alpha-2 state codes used to subset the data.
counties	US county names or 5-digit FIPS codes used to subset the data.

Value

Enhanced dataframe of synoptic PurpleAir data.

References

PurpleAir

PurpleAir API

PurpleAir Terms of service

PurpleAir Data license

PurpleAir Data Attribution

See Also

pas_downloadParseRawData

MazamaScience/AirSensor2 documentation built on Oct. 31, 2024, 1:39 a.m.