generateaWhereDataset: generateaWhereDataset
In aWhereAPI/aWhere-R-Charts: Make Charts using output from aWhere API

Description Usage Arguments Details Value References Examples

generateaWhereDataset Generate a basic aWhere weather dataset for a given point and timespan.

generateaWhereDataset(
  lat,
  lon,
  day_start,
  day_end,
  year_start,
  year_end,
  verbose = TRUE,
  appendPrevDataPull = TRUE,
  removeFeb29Data = FALSE
)

`lat`	numeric latitude point in decimal degrees (required)
`lon`	numeric longitude point in decimal degrees (required)
`day_start`	character string in YYYY-MM-DD format, denoting the first day for which you want weather data retrieved (required)
`day_end`	character string in YYYY-MM-DD format, denoting the last day for which you want weather data retrieved (required)
`year_start`	numeric in YYYY format, denoting the first year of data which should be included in the norms calculation. (required)
`year_end`	numeric in YYYY format, denoting the last year of data which should be included in the norms calculation (required)
`verbose`	print additional diagnostic messages during runtime (optional)
`appendPrevDataPull`	disable behavior for R to request and append only novel data for the current location but instead to create data object fresh at all times (optional)
`removeFeb29Data`	automatically remove Feb 29th data (optional)

This function returns an organized dataset from the aWhere API with a pre-set list of variables for the given coordinates and spanning the entire input datespan, which can include forecasted dates. Forecast data will be returned in 24-hour/1-day blocks, in order to be harmonious with the past observed data. The pre-set variables include temperature, rainfall, PET, P/PET, GDDs, and variable accumulations. The pre-set list is not customizable. Users who wish to investigate other variables returned by the aWhere API - like humidity, solar radiation, and more - should use the base functions provided in the aWhereAPI package. This function is intended to get a user started with retrieving data and analyzing it quickly, without the need for making multiple function calls or merging the results.

dataframe with the following schema: latitude, longitude, date, day, accumulatedGdd.amount, accumulatedGdd.average, accumulatedGdd.stdDev, accumulatedPet.amount, accumulatedPet.average, accumulatedPet.stdDev, accumulatedPpet.amount, accumulatedPpet.average, accumulatedPpet.stdDev, accumulatedPrecipitation.amount, accumulatedPrecipitation.average, accumulatedPrecipitation.stdDev, gdd.amount, gdd.average, gdd.stdDev, pet.amount, pet.average, pet.stdDev, ppet.amount, ppet.average, ppet.stdDev, precipitation.amount, precipitation.average, precipitation.stdDev, relativeHumidity.max.amount, relativeHumidity.max.average, relativeHumidity.max.stdDev, relativeHumidity.min.amount, relativeHumidity.min.average, relativeHumidity.min.stdDev, solar.amount, solar.average, solar.stdDev, temperatures.max.amount, temperatures.max.average, temperatures.max.stdDev, temperatures.min.amount, temperatures.min.average, temperatures.min.stdDev, wind.average.amount, wind.average.average, wind.average.stdDev, wind.dayMax.amount, wind.dayMax.average, wind.dayMax.stdDev

http://developer.awhere.com/api/reference/

## Not run: generateaWhereDataset(lat = 30.685
                              ,lon = 72.928
                              ,day_start = "2018-09-01"
                              ,day_end = "2019-01-20"
                              ,year_start = 2008
                              ,year_end = 2018)
## End(Not run)