An API request occurs when you programmatically send a data query from software on your computer (for example, R, Section 4) to the API for some NASS survey data that you want. Retrieve the data from the Quick Stats server.
It allows you to customize your query by commodity, location, or time period. The API only returns queries that return 50,000 or less records, so Web Page Resources The use of a callback function parameter, not shown in the example above, is beyond the scope of this article. To submit, please register and login first. Finally, it will explain how to use Tableau Public to visualize the data. a list of parameters is helpful. Either 'CENSUS' or 'SURVEY'", https://quickstats.nass.usda.gov/api#param_define. Federal government websites often end in .gov or .mil. It is simple and easy to use, and provides some functions to help navigate the bewildering complexity of some Quick Stats data. The primary benefit of rnassqs is that users need not download data through repeated . You can then visualize the data on a map, manipulate and export the results, or save a link for future use. write_csv(data = nc_sweetpotato_data, path = "Users/your/Desktop/nc_sweetpotato_data_query_on_20201001.csv"). If you download NASS data without using computer code, you may find that it takes a long time to manually select each dataset you want from the Quick Stats website. If all works well, then it should be completed within a few seconds and it will write the specified CSV file to the output folder. http://quickstats.nass.usda.gov/api/api_GET/?key=PASTE_YOUR_API_KEY_HERE&source_desc=SURVEY§or_desc%3DFARMS%20%26%20LANDS%20%26%20ASSETS&commodity_desc%3DFARM%20OPERATIONS&statisticcat_desc%3DAREA%20OPERATED&unit_desc=ACRES&freq_desc=ANNUAL&reference_period_desc=YEAR&year__GE=1997&agg_level_desc=NATIONAL&state_name%3DUS%20TOTAL&format=CSV. Some care Statistics Service, Washington, D.C. URL: https://quickstats.nass.usda.gov [accessed Feb 2023] . Each language has its own unique way of representing meaning, using these characters and its own grammatical rules for combining these characters. 'OR'). rnassqs: An R package to access agricultural data via the USDA National Agricultural Statistics Service (USDA-NASS) 'Quick Stats' API. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. Second, you will use the specific information you defined in nc_sweetpotato_params to make the API query. Here are the pairs of parameters and values that it will submit in the API call to retrieve that data: Following is the full encoded URL that the program below creates and sends with the Quick Stats API. In this case, the NC sweetpotato data will be saved to a file called nc_sweetpotato_data_query_on_20201001.csv on your desktop. Figure 1. Say you want to plot the acres of sweetpotatoes harvested by year for each county in North Carolina. These include: R, Python, HTML, and many more. time, but as you become familiar with the variables and calls of the The NASS helps carry out numerous surveys of U.S. farmers and ranchers. N.C. Before you make a specific API query, its best to see whether the data are even available for a particular combination of parameters. Tip: Click on the images to view full-sized and readable versions. You know you want commodity_desc = SWEET POTATOES, agg_level_desc = COUNTY, unit_desc = ACRES, domain_desc = TOTAL, statisticcat_desc = "AREA HARVESTED", and prodn_practice_desc = "ALL PRODUCTION PRACTICES". The data found via the CDQT may also be accessed in the NASS Quick Stats database. Before sharing sensitive information, make sure you're on a federal government site. Instructions for how to use Tableau Public are beyond the scope of this tutorial. Call 1-888-424-7828 NASS Customer Support is available Monday - Friday, 8am - 5pm CT Please be prepared with your survey name and survey code. 2020. Because R is accessible to so many people, there is a great deal of collaboration and sharing of R resources, scripts, and knowledge. In addition, you wont be able An official website of the United States government. However, beware that this will be a development version: # install.packages ("devtools") devtools :: install_github ("rdinter . How to install Tableau Public and learn about it if you want to try it to visualize agricultural data or use it for other projects. nassqs_params() provides the parameter names, While the Quick Stats database contains more than 52 million records, any call using GET /api/api_GET query is limited to a 50,000-record result set. the project, but you have to repeat this process for every new project,
Harvest and Analyze Agricultural Data with the USDA NASS API, Python The USDA NASS Quick Stats API provides direct access to the statistical information in the Quick Stats database. NASS Regional Field Offices maintain a list of all known operations and use known sources of operations to update their lists. .Renviron, you can enter it in the console in a session. That file will then be imported into Tableau Public to display visualizations about the data. install.packages("tidyverse")
NC State University and NC In this example, the sum function is doing a task that you can easily code by using the + sign, but it might not always be easy for you to code up the calculations and analyses done by a function. The following are some of the types of data it stores and makes available: NASS makes data available through CSV and PDF files, charts and maps, a searchable database, pre-defined queries, and the Quick Stats API. By setting domain_desc = TOTAL, you will get the total acreage of sweetpotatoes in the county as opposed to the acreage of sweetpotates in the county grown by operators or producers of specific demographic groups that contribute to the total acreage of harvested sweetpotatoes in the county. The advantage of this You can read more about the available NASS Quick Stats API parameters and their definitions by checking out the help page on this topic. N.C. Once you know North Carolina has data available, you can make an API query specific to sweetpotatoes in North Carolina. # plot Sampson county data
class(nc_sweetpotato_data_survey$Value)
However, the NASS also allows programmatic access to these data via an application program interface as described in Section 2. Programmatic access refers to the processes of using computer code to select and download data. Accessing data with computer code comes in handy when you want to view data from multiple states, years, crops, and other categories. The latest version of R is available on The Comprehensive R Archive Network website. parameters. To improve data accessibility and sharing, the NASS developed a "Quick Stats" website where you can select and download data from two of the agency's surveys. As an example, one year of corn harvest data for a particular county in the United States would represent one row, and a second year would represent another row. You can then visualize the data on a map, manipulate and export the results as an output file compatible for updating databases and spreadsheets, or save a link for future use. You do this by using the str_replace_all( ) function. The query in The ARMS is collected each year and includes data on agricultural production practices, agricultural resource use, and the economic well-being of farmers and ranchers (ARMS 2020). and rnassqs will detect this when querying data. Here are the two Python modules that retrieve agricultural data with the Quick Stats API: To run the program, you will need to install the Python requests and urllib packages. functions as follows: # returns a list of fields that you can query, #> [1] "agg_level_desc" "asd_code" "asd_desc", #> [4] "begin_code" "class_desc" "commodity_desc", #> [7] "congr_district_code" "country_code" "country_name", #> [10] "county_ansi" "county_code" "county_name", #> [13] "domaincat_desc" "domain_desc" "end_code", #> [16] "freq_desc" "group_desc" "load_time", #> [19] "location_desc" "prodn_practice_desc" "reference_period_desc", #> [22] "region_desc" "sector_desc" "short_desc", #> [25] "state_alpha" "state_ansi" "state_name", #> [28] "state_fips_code" "statisticcat_desc" "source_desc", #> [31] "unit_desc" "util_practice_desc" "watershed_code", #> [34] "watershed_desc" "week_ending" "year", #> [1] "agg_level_desc: Geographical level of data.
Access Data from the NASS Quick Stats API rnassqs - rOpenSci To use a restaurant analogy, you can think of the NASS Quick Stats API as the waitstaff at your favorite restaurant, the NASS data servers as the kitchen, the software on your computer as the waitstaffs order notepad, and the coder as the customer (you) as shown in Figure 1. Once the You can see whether a column is a character by using the class( ) function on that column (that is, nc_sweetpotato_data_survey$Value where the $ helps you access the Value column in the nc_sweetpotato_data_survey variable). Once you have a The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. Looking for U.S. government information and services? Section 207(f)(2) of the E-Government Act of 2002 requires federal agencies to develop an inventory of information to be published on their Web sites, establish a schedule for publishing information, make those schedules available for public comment, and post the schedules and priorities on the Web site. It accepts a combination of what, where, and when parameters to search for and retrieve the data of interest.
We summarize the specifics of these benefits in Section 5. Access Quick Stats Lite . Quick Stats System Updates provides notification of upcoming modifications. To use a baking analogy, you can think of the script as a recipe for your favorite dessert. lock ( sampson_sweetpotato_data <- filter(nc_sweetpotato_data, county_name == "SAMPSON")
rnassqs tries to help navigate query building with The sample Tableau dashboard is called U.S. Once in the tool please make your selection based on the program, sector, group, and commodity. An application program interface, or API for short, helps coders access one software program from another. time you begin an R session. You can check by using the nassqs_param_values( ) function. file. Before using the API, you will need to request a free API key that your program will include with every call using the API. A function in R will take an input (or many inputs) and give an output. A&T State University, in all 100 counties and with the Eastern Band of Cherokee Quick Stats Lite provides a more structured approach to get commonly requested statistics from our online database. Depending on what agency your survey is from, you will need to contact that agency to update your record. session. Working for Peanuts: Acquiring, Analyzing, and Visualizing Publicly Available Data. Journal of the American Society of Farm Managers and Rural Appraisers, p156-166. If you use it, be sure to install its Python Application support. description of the parameter(s) in question: Documentation on all of the parameters is available at https://quickstats.nass.usda.gov/api#param_define. You can also make small changes to the script to download new types of data. 2019. It is a comprehensive summary of agriculture for the US and for each state. secure websites.
Quick Stats database - Providing Central Access to USDA's Open You can use many software programs to programmatically access the NASS survey data. Agricultural Commodity Production by Land Area. The types of agricultural data stored in the FDA Quick Stats database. However, other parameters are optional. See the Quick Stats API Usage page for this URL and two others. After you have completed the steps listed above, run the program. Dynamic drill-down filtered search by Commodity, Location, and Date range, beginning with Census or Survey data. 4:84.
Quick Stats Lite provides a more structured approach to get commonly requested statistics from . Any person using products listed in . An introductory tutorial or how to use the National Agricultural Statistics Service (NASS) Quickstats tool can be found on their website. Contact a specialist. The == character combination tells R that this is a logic test for exactly equal, the & character is a logic test for AND, and the != character combination is a logic test for not equal. NASS - Quick Stats. Need Help? The Python program that calls the NASS Quick Stats API to retrieve agricultural data includes these two code modules (files): Scroll down to see the code from the two modules.
USDA - National Agricultural Statistics Service - Quick Stats Data by subject gives you additional information for a particular subject area or commodity. following: Subsetting by geography works similarly, looping over the geography In file run_usda_quick_stats.py create the parameters variable that contains parameter and value pairs to select data from the Quick Stats database. If you think back to algebra class, you might remember writing x = 1. Winter Wheat Seedings up for 2023, 12/13/22 NASS to publish milk production data in updated data dissemination format, 11/28/22 USDA-NASS Crop Progress report delayed until Nov. 29, 10/28/22 NASS reinstates Cost of Pollination survey, 09/06/22 NASS to review acreage information, 09/01/22 USDA NASS reschedules 2021 Conservation Practice Adoption Motivations data highlights release, 05/06/22 Respond Now to the 2022 Census of Agriculture, 08/05/20 The NASS Mission: We do it for you, 04/11/19 2017 Census of Agriculture Highlight Series Farms and Land in Farms, 04/11/19 2017 Census of Agriculture Highlight Series Economics, 04/11/19 2017 Census of Agriculture Highlight Series Demographics, 02/08/23 Crop Production (February 2023), 01/31/23 Cattle & Sheep and Goats (January 2023), 12/23/22 Quarterly Hogs and Pigs (December 2022), 12/15/22 2021 Certified Organics (December 2022), Talking About NASS - A guide for partners and stakeholders, USDA and NASS Anti-Harassment Policy Statement, REE Reasonable Accommodations and Personal Assistance Services, Safeguarding America's Agricultural Statistics Report and Video, Agriculture Counts - The Founding and Evolution of the National Agricultural Statistics Service 1957-2007, Hours: 7:30 a.m. - 4:00 p.m. Eastern Time Monday - Friday, except federal holidays Toll-Free: (800) 727-9540, Hours: 9:00 a.m. - 5:30 p.m. Eastern Time Monday - Friday, except federal holidays Toll-Free: (833) One-USDA
Also, before running the program, create the folder specified in the self.output_file_path variable in the __init__() function of the c_usda_quick_stats class. NASS develops these estimates from data collected through: Dynamic drill-down filtered search by Commodity, Location, and Date range, (dataset) USDA National Agricultural Statistics Service (2017). Where available, links to the electronic reports is provided. This article will provide you with an overview of the data available on the NASS web pages. One way it collects data is through the Census of Agriculture, which surveys all agricultural operations with $1,000 or more of products raised or sold during the census year. It allows you to customize your query by commodity, location, or time period. If you have already installed the R package, you can skip to the next step (Section 7.2). 2017 Census of Agriculture. The National Agricultural Statistics Service (NASS) is part of the United States Department of Agriculture. token API key, default is to use the value stored in .Renviron .
nass_data: Get data from the Quick Stats query in usdarnass: USDA NASS For most Column or Header Name values, the first value, in lowercase, is the API parameter name, like those shown above. In the example program, the value for api key will be replaced with my API key. Then you can use it coders would say run the script each time you want to download NASS survey data. Agricultural Census since 1997, which you can do with something like. Note that the value PASTE_YOUR_API_KEY_HERE must be replaced with your personal API key. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture. In the example shown below, I selected census table 1 Historical Highlights for the state of Minnesota from the 2017 Census of Agriculture. Create a worksheet that allows the user to select a commodity (corn, soybeans, selected) and view the number of acres planted or harvested from 1997 through 2021. Otherwise the NASS Quick Stats API will not know what you are asking for. Agricultural Resource Management Survey (ARMS).
Citation Request - USDA - National Agricultural Statistics Service Homepage API makes it easier to download new data as it is released, and to fetch You can then visualize the data on a map, manipulate and export the results, or save a link for future use. Quick Stats Lite provides a more structured approach to get commonly requested statistics from our online database. Cooperative Extension prohibits discrimination and harassment regardless of age, color, disability, family and marital status, gender identity, national origin, political beliefs, race, religion, sex (including pregnancy), sexual orientation and veteran status. You can also export the plots from RStudio by going to the toolbar > Plots > Save as Image. As an example, you cannot run a non-R script using the R software program.
As a result, R coders have developed collections of user-friendly R scripts that accomplish themed tasks. Once youve installed the R packages, you can load them. After running these lines of code, you will get a raw data output that has over 1500 rows and close to 40 columns.
Using rnassqs to automate running your script, since it will stop and ask you to Open Tableau Public Desktop and connect it to the agricultural CSV data file retrieved with the Quick Stats API through the Python program described above. Now you have a dataset that is easier to work with. There is no description for this organization, National Agricultural Statistics Service, Department of Agriculture. Next, you can define parameters of interest. Journal of Open Source Software , 4(43 . file, and add NASSQS_TOKEN =
to the Corn stocks down, soybean stocks down from year earlier
Special Tabulations and Restricted Microdata, 02/15/23 Still time to respond to the 2022 Census of Agriculture, USDA to follow up with producers who have not yet responded, 02/15/23 Still time to respond to the 2022 Puerto Rico Census of Agriculture, USDA to follow-up with producers who have not yet responded (Puerto Rico - English), 01/31/23 United States cattle inventory down 3%, 01/30/23 2022 Census of Agriculture due next week Feb. 6, 01/12/23 Corn and soybean production down in 2022, USDA reports
One way of USDA NASS Quick Stats API | ProgrammableWeb
Here we request the number of farm operators or the like) in lapply. its a good idea to check that before running a query. Finally, format will be set to csv, which is a data file format type that works well in Tableau Public. The inputs to this function are 2 and 10 and the output is 12. The waitstaff and restaurant use that number to keep track of your order and bill (Figure 1). Create an instance called stats of the c_usda_quick_stats class. Official websites use .govA R sessions will have the variable set automatically, In registering for the key, for which you must provide a valid email address. You can view the timing of these NASS surveys on the calendar and in a summary of these reports. A script includes a collection of code that, when taken together, defines a series of steps the coder wants his or her computer to carry out. Writer, photographer, cyclist, nature lover, data analyst, and software developer. commitment to diversity. You can add a file to your project directory and ignore it via How do I use the National Agricultural Statistics Service Quickstats tool? USDA National Agricultural Statistics Service Cropland Data - USGS If you are using Visual Studio, then set the Startup File to the file run_usda_quick_stats.py. The Comprehensive R Archive Network (CRAN), Weed Management in Nurseries, Landscapes & Christmas Trees, NC Its recommended that you use the = character rather than the <- character combination when you are defining parameters (that is, variables inside functions). Data are currently available in the following areas: Pre-defined queries are provided for your convenience. Alternatively, you can query values Agricultural Chemical Usage - Field Crops and Potatoes NASS Winter Wheat Seedings up for 2023, NASS to publish milk production data in updated data dissemination format, USDA-NASS Crop Progress report delayed until Nov. 29, NASS reinstates Cost of Pollination survey, USDA NASS reschedules 2021 Conservation Practice Adoption Motivations data highlights release, Respond Now to the 2022 Census of Agriculture, 2017 Census of Agriculture Highlight Series Farms and Land in Farms, 2017 Census of Agriculture Highlight Series Economics, 2017 Census of Agriculture Highlight Series Demographics, NASS Climate Adaptation and Resilience Plan, Statement of Commitment to Scientific Integrity, USDA and NASS Civil Rights Policy Statement, Civil Rights Accountability Policy and Procedures, Contact information for NASS Civil Rights Office, International Conference on Agricultural Statistics, Agricultural Statistics: A Historical Timeline, As We Recall: The Growth of Agricultural Estimates, 1933-1961, Safeguarding America's Agricultural Statistics Report, Application Programming Interfaces (APIs), Economics, Statistics and Market Information System (ESMIS). Also note that I wrote this program on a Windows PC, which uses back slashes (\) in file names and folder names. This is why functions are an important part of R packages; they make coding easier for you. Its main limitations are 1) it can save visualization projects only to the Tableau Public Server, 2) all visualization projects are visible to anyone in the world, and 3) it can handle only a small number of input data types. Do this by right-clicking on the file name in Solution Explorer and then clicking [Set as Startup File] from the popup menu. request. Source: National Weather Service, www.nws.noaa.gov Drought Monitor, Valid February 21, 2023. rnassqs: An R package to access agricultural data via the USDA National Also, be aware that some commodity descriptions may include & in their names. Census of Agriculture Top The Census is conducted every 5 years. Each parameter is described on the Quick Stats Usage page, in its Quick Stats Columns Definition table, as shown below. While it does not access all the data available through Quick Stats, you may find it easier to use. USDA-NASS Quick Stats (Crops) WHEAT.pdf PDF 1.42 MB . ggplot(data = sampson_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)). The <- character combination means the same as the = (that is, equals) character, and R will recognize this. The county data includes totals for the Agricultural Statistics Districts (county groupings) and the State. You can also set the environmental variable directly with RStudio is another open-source software that makes it easier to code in R. The latest version of RStudio is available at the RStudio website. You can define the query output as nc_sweetpotato_data. A list of the valid values for a given field is available via to the Quick Stats API. Providing Central Access to USDAs Open Research Data. downloading the data via an R script creates a trail that you can revisit later to see exactly what you downloaded.It also makes it much easier for people seeking to . As mentioned in Section 1, you can visit the NASS Quick Stats website, click through the options, and download the data. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production. In R, you would write x <- 1. R is an open source coding language that was first developed in 1991 primarily for conducting statistical analyses and has since been applied to data visualization, website creation, and much more (Peng 2020; Chambers 2020). Code is similar to the characters of the natural language, which can be combined to make a sentence. First, you will define each of the specifics of your query as nc_sweetpotato_params. want say all county cash rents on irrigated land for every year since Why Is it Beneficial to Access NASS Data Programmatically? A locked padlock 2020. The United States is blessed with fertile soil and a huge agricultural industry. Email: askusda@usda.gov
(PDF) USDA-NASS Quick Stats (Crops) WHEAT - ResearchGate Feel free to download it and modify it in the Tableaue Public Desktop application to learn how to create and publish Tableau visualizations. This is less easy because you have to enter (or copy-paste) the key each script creates a trail that you can revisit later to see exactly what For example, commodity_desc refers to the commodity description information available in the NASS Quick Stats API and agg_level_desc refers to the aggregate level description of NASS Quick Stats API data. NASS makes it easy for anyone to retrieve most of the data it captures through its Quick Stats database search web page. In the get_data() function of c_usd_quick_stats, create the full URL. Due to suppression of data, the For docs and code examples, visit the package web page here .
USDA - National Agricultural Statistics Service - Publications - Report Skip to 5. For For example, in the list of API parameters shown above, the parameter source_desc equates to Program in the Quick Stats query tool. Quick Stats is the National Agricultural Statistics Service's (NASS) online, self-service tool to access complete results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. PDF Texas Crop Progress and Condition For Note: When a line of R code starts with a #, R knows to read this # symbol as a comment and will skip over this line when you run your code. Accessed online: 01 October 2020. NASS conducts hundreds of surveys every year and prepares reports covering virtually every aspect of U.S. agriculture. method is that you dont have to think about the API key for the rest of Peng, R. D. 2020. When you are coding, its helpful to add comments so you will remember or so someone you share your script with knows what you were trying to do and why. The first line of the code above defines a variable called NASS_API_KEY and assigns it the string of letters and numbers that makes up the NASS Quick Stats API key you received from the NASS. # look at the first few lines
The Comprehensive R Archive Network website, Working for Peanuts: Acquiring, Analyzing, and Visualizing Publicly Available Data. For example, you can write a script to access the NASS Quick Stats API and download data. While Quick Stats and Quick Stats Lite retrieve agricultural survey data (collected annually) and census data (collected every five years), the Census Data Query Tool is easier to use but retrieves only census data. In this case, you can use the string of letters and numbers that represents your NASS Quick Stats API key to directly define the key parameter that the function needs to work. There are thousands of R packages available online (CRAN 2020). Winter Wheat Seedings up for 2023, 12/13/22 NASS to publish milk production data in updated data dissemination format, 11/28/22 USDA-NASS Crop Progress report delayed until Nov. 29, 10/28/22 NASS reinstates Cost of Pollination survey, 09/06/22 NASS to review acreage information, 09/01/22 USDA NASS reschedules 2021 Conservation Practice Adoption Motivations data highlights release, 05/06/22 Respond Now to the 2022 Census of Agriculture, 08/05/20 The NASS Mission: We do it for you, 04/11/19 2017 Census of Agriculture Highlight Series Farms and Land in Farms, 04/11/19 2017 Census of Agriculture Highlight Series Economics, 04/11/19 2017 Census of Agriculture Highlight Series Demographics, 02/08/23 Crop Production (February 2023), 01/31/23 Cattle & Sheep and Goats (January 2023), 12/23/22 Quarterly Hogs and Pigs (December 2022), 12/15/22 2021 Certified Organics (December 2022), Talking About NASS - A guide for partners and stakeholders, USDA and NASS Anti-Harassment Policy Statement, REE Reasonable Accommodations and Personal Assistance Services, Safeguarding America's Agricultural Statistics Report and Video, Agriculture Counts - The Founding and Evolution of the National Agricultural Statistics Service 1957-2007, Hours: 7:30 a.m. - 4:00 p.m. Eastern Time Monday - Friday, except federal holidays Toll-Free: (800) 727-9540, Hours: 9:00 a.m. - 5:30 p.m. Eastern Time Monday - Friday, except federal holidays Toll-Free: (833) One-USDA