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Get data and return a data frame

Source: R/request.R
nassqs.Rd

The primary function in the rnassqs package, nassqs makes a HTTP GET request to the USDA-NASS Quick Stats API and returns the data parsed as a data.frame, plain text, or list. Various other functions make use of nassqs to make specific queries. For a data request the Quick Stats API returns JSON that when parsed to a data.frame contains 39 columns and a varying number of rows depending on the query. Unfortunately there is not a way to restrict the number of columns.

Usage

nassqs(
  ...,
  agg_level_desc = NULL,
  asd_code = NULL,
  asd_desc = NULL,
  begin_code = NULL,
  class_desc = NULL,
  commodity_desc = NULL,
  congr_district_code = NULL,
  country_code = NULL,
  country_name = NULL,
  county_ansi = NULL,
  county_code = NULL,
  county_name = NULL,
  domaincat_desc = NULL,
  domain_desc = NULL,
  end_code = NULL,
  freq_desc = NULL,
  group_desc = NULL,
  load_time = NULL,
  location_desc = NULL,
  prodn_practice_desc = NULL,
  reference_period_desc = NULL,
  region_desc = NULL,
  sector_desc = NULL,
  short_desc = NULL,
  source_desc = NULL,
  state_alpha = NULL,
  state_ansi = NULL,
  state_fips_code = NULL,
  state_name = NULL,
  statisticcat_desc = NULL,
  unit_desc = NULL,
  util_practice_desc = NULL,
  watershed_code = NULL,
  watershed_desc = NULL,
  week_ending = NULL,
  year = NULL,
  zip_5 = NULL,
  as_numeric = TRUE,
  progress_bar = TRUE,
  format = "csv",
  as = "data.frame"
)

Arguments

...

either a named list of parameters or a series of additional parameters that include operations, e.g. year__GE = 2010 for all records in 2010 and later. See details for information on available operators.

agg_level_desc

Geographic level ("AGRICULTURAL DISTRICT", "COUNTY", "INTERNATIONAL", "NATIONAL", "REGION : MULTI-STATE", "REGION : SUB-STATE", "STATE", "WATERSHED", or "ZIP CODE").

asd_code

Agriculture statistical district code.

asd_desc

Agriculture statistical district name / description.

begin_code

Week number indicating when the data series begins.

class_desc

Commodity class.

commodity_desc

Commodity, the primary subject of interest (e.g., "CORN", "CATTLE", "LABOR", "TRACTORS", "OPERATORS").

congr_district_code

Congressional District codes.

country_code

Country code.

country_name

Country name.

county_ansi

County ANSI code.

county_code

County FIPS code.

county_name

County name.

domaincat_desc

Domain category within a domain (e.g., under domain_desc = "SALES", domain categories include $1,000 TO $9,999, $10,000 TO $19,999, etc).

domain_desc

Domain, a characteristic of operations that produce a particular commodity (e.g., "ECONOMIC CLASS", "AREA OPERATED", "NAICS CLASSIFICATION", "SALES"). For chemical usage data, the domain describes the type of chemical applied to the commodity. The domain_desc: = "TOTAL" will have no further breakouts; i.e., the data value pertains completely to the short_desc.

end_code

= Week number that the data series ends.

freq_desc

Time period type covered by the data ("ANNUAL", "SEASON", "MONTHLY", "WEEKLY", "POINT IN TIME"). "MONTHLY" often covers more than one month. "POINT IN TIME" is for a particular day.

group_desc

Commodity group within a sector (e.g., under sector_desc = "CROPS", the groups are "FIELD CROPS", "FRUIT & TREE NUTS", "HORTICULTURE", and "VEGETABLES").

load_time

Date and time of the data load, e.g. "2015-02-17 16:05:20".

location_desc

Location code, e.g. 5-digit fips code for counties.

prodn_practice_desc

Production practice, (e.g. "UNDER PROTECTION", "OWNED, RIGHTS, LEASED", "ORGANIC, TRANSITIONING", "HIRED MANAGER").

reference_period_desc

Reference period of the data (e.g. "JUN", "MID SEP", "WEEK #32").

region_desc

Region name (e.g. "TEXAS", "WA & OR", "WEST COAST", "UMATILLA").

sector_desc

Sector, the five high level, broad categories useful to narrow down choices. ("ANIMALS & PRODUCTS", "CROPS", "DEMOGRAPHICS", "ECONOMICS", or "ENVIRONMENTAL").

short_desc

A concatenation of six columns: commodity_desc, class_desc, prodn_practice_desc, util_practice_desc, statisticcat_desc, and unit_desc.

source_desc

Source of data ("CENSUS" or "SURVEY"). Census program includes the Census of Ag as well as follow up projects. Survey program includes national, state, and county surveys.

state_alpha

2-character state abbreviation, e.g. "NM".

state_ansi

State ANSI code.

state_fips_code

State FIPS code.

state_name

Full name of the state, e.g. "ALABAMA".

statisticcat_desc

Statistical category of the data (e.g., "AREA HARVESTED", "PRICE RECEIVED", "INVENTORY", "SALES").

unit_desc

The units of the data (e.g. "TONS / ACRE", "TREES", "OPERATIONS", "NUMBER", "LB / ACRE", "BU / PLANTED ACRE").

util_practice_desc

Utilization practice (e.g. "WIND", "SUGAR", "SILAGE", "ONCE REFINED", "FEED", "ANIMAL FEED").

watershed_code

Watershed code as 8-digit HUC (e.g. "13020100").

watershed_desc

Watershed/HUC name (e.g. "UPPER COLORADO").

week_ending

Date of ending week (e.g. "1975-11-22").

year

Year of the data. Conditional values are possible by appending an operation to the parameter, e.g. "year__GE = 2020" will return all records with year >= 2020. See details for more on operations.

zip_5

5-digit zip code.

as_numeric

Whether to convert data to numeric format. Conversion will replace missing notation such as "(D)" or "(Z)" with NA, but removes the need to convert to numeric format after querying.

progress_bar

Whether or not to display the progress bar.

format

The format to return the query in. Only useful if as = "text".

as

whether to return a data.frame, list, or text string. See nassqs_parse().

Value

a data frame, list, or text string of requested data.

Details

nassqs() accepts all parameters that are accepted by the USDA-NASS Quick Stats. These parameters are listed in nassqs_params(), and are used to form the data query.

Parameters can be modified by operations, which are appended to the parameter name. For example, "year__GE = 2020" will fetch data in 2020 and after. Operations can take the following form:

  • __LE: less than or equal (<=)

  • __LT: less than (<)

  • __GT: greater than (>)

  • __GE: = >=

  • __LIKE = like

  • __NOT_LIKE = not like

  • __NE = not equal

See also

nassqs_GET(), nassqs_parse(), nassqs_yields(), nassqs_acres()

Examples

if (FALSE) {
  # Get corn yields in Virginia in 2012
  params <- list(commodity_desc = "CORN",
                 year = 2012,
                 agg_level_desc = "COUNTY",
                 state_alpha = "VA",
                 statisticcat_desc = "YIELD")
  yields <- nassqs(params)
  head(yields)
}