After additional columns(i.e. datetime
, and monitorID
)
have been applied to an EPA dataframe, we are ready to
pull out site information associated with unique monitorID.
These will be rearranged into a dataframe organized as deployment-by-property with one row for each monitorID.
This site information found in tbl
is augmented so that we end up with a uniform
set of properties associated with each monitorID. The list of
columns in the returned meta
dataframe is:
> names(p$meta) [1] "monitorID" "longitude" "latitude" [4] "elevation" "timezone" "countryCode" [7] "stateCode" "siteName" "agencyName" [10] "countyName" "msaName" "monitorType" [13] "monitorInstrument" "aqsID" "pwfslID" [16] "pwfslDataIngestSource" "telemetryAggregator" "telemetryUnitID"
epa_createMetaDataframe(tbl, pwfslDataIngestSource = "EPA",
existingMeta = NULL, addGoogleMeta = TRUE)
an EPA raw tibble after metadata enhancement
identifier for the source of monitoring data, e.g. 'EPA_hourly_88101_2016.zip'
existing 'meta' dataframe from which to obtain metadata for known monitor deployments
logicial specifying wheter to use Google elevation and reverse geocoding services
A meta
dataframe for use in a ws_monitor object.