how to cite usda nass quick stats

The data include the total crops and cropping practices for each county, and breakouts for irrigated and non-irrigated practices for many crops, for selected States. rnassqs: Access the NASS 'Quick Stats' API. For docs and code examples, visit the package web page here . use nassqs_record_count(). NASS Reports Crop Progress (National) Crop Progress & Condition (State) or the like) in lapply. = 2012, but you may also want to query ranges of values. 2017 Ag Atlas Maps. Because R is accessible to so many people, there is a great deal of collaboration and sharing of R resources, scripts, and knowledge. *In this Extension publication, we will only cover how to use the rnassqs R package. 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. Website: https://ask.usda.gov/s/, June Turner, Director Email: / Phone: (202) 720-8257, Find contact information for Regional and State Field Offices. 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 they became available in 2008, you can iterate by doing the To demonstrate the use of the agricultural data obtained with the Quick Stats API, I have created a simple dashboard in Tableau Public. The Comprehensive R Archive Network (CRAN), Weed Management in Nurseries, Landscapes & Christmas Trees, NC A&T State University. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). In the beginning it can be more confusing, and potentially take more About NASS. 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. It allows you to customize your query by commodity, location, or time period. You dont need all of these columns, and some of the rows need to be cleaned up a little bit. This is less easy because you have to enter (or copy-paste) the key each Taken together, R reads this statement as: filter out all rows in the dataset where the source description column is exactly equal to SURVEY and the county name is not equal to OTHER (COMBINED) COUNTIES. 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. Agricultural Census since 1997, which you can do with something like. Title USDA NASS Quick Stats API Version 0.1.0 Description An alternative for downloading various United States Department of Agriculture (USDA) data from <https://quickstats.nass.usda.gov/> through R. . # look at the first few lines Which Software Programs Can Be Used to Programmatically Access NASS Survey Data? Quick Stats contains official published aggregate estimates related to U.S. agricultural production. Downloading data via 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. Didn't find what you're looking for? The rnassqs R package provides a simple interface for accessing the United States Department of Agriculture National Agricultural Statistics Service (USDA-NASS) 'Quick Stats' API. 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. nc_sweetpotato_data_survey <- filter(nc_sweetpotato_data_sel, source_desc == "SURVEY" & county_name != "OTHER (COMBINED) COUNTIES") return the request object. Each parameter is described on the Quick Stats Usage page, in its Quick Stats Columns Definition table, as shown below. Most queries will probably be for specific values such as year The use of a callback function parameter, not shown in the example above, is beyond the scope of this article. It is simple and easy to use, and provides some functions to help navigate the bewildering complexity of some Quick Stats data. Otherwise the NASS Quick Stats API will not know what you are asking for. description of the parameter(s) in question: Documentation on all of the parameters is available at https://quickstats.nass.usda.gov/api#param_define. Finally, format will be set to csv, which is a data file format type that works well in Tableau Public. ggplot(data = nc_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)) + facet_wrap(~ county_name) You can get an API Key here. This reply is called an API response. 2020. nc_sweetpotato_data <- select(nc_sweetpotato_data_survey_mutate, -Value) Multiple values can be queried at once by including them in a simple The API request is the customers (your) food order, which the waitstaff wrote down on the order notepad. 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 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. The census takes place once every five years, with the next one to be completed in 2022. If you are using Visual Studio, then set the Startup File to the file run_usda_quick_stats.py. Quick Stats Lite provides a more structured approach to get commonly requested statistics from . nassqs is a wrapper around the nassqs_GET An official website of the United States government. The latest version of R is available on The Comprehensive R Archive Network website. The data found via the CDQT may also be accessed in the NASS Quick Stats database. Next, you can use the filter( ) function to select data that only come from the NASS survey, as opposed to the census, and represents a single county. Accessed online: 01 October 2020. Some care Programmatic access refers to the processes of using computer code to select and download data. However, here are the basic steps to install Tableau Public and build and publish the dashboard: After completing this tutorial, you should have a general understanding of: I can imagine many use cases for projects that would use data from the Quick Stats database. rnassqs tries to help navigate query building with The agency has the distinction of being known as The Fact Finders of U.S. Agriculture due to the abundance of . ggplot(data = sampson_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)). 2019-67021-29936 from the USDA National Institute of Food and Agriculture. 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. An official website of the United States government. You can first use the function mutate( ) to rename the column to harvested_sweetpotatoes_acres. list with c(). The QuickStats API offers a bewildering array of fields on which to nassqs_auth(key = "ADD YOUR NASS API KEY HERE"). For example, you can write a script to access the NASS Quick Stats API and download data. If you are interested in trying Visual Studio Community, you can install it here. Accessed: 01 October 2020. Skip to 3. 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. R Programming for Data Science. variable (usually state_alpha or county_code Provide statistical data related to US agricultural production through either user-customized or pre-defined queries. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. Accessed online: 01 October 2020. Corn production data goes back to 1866, just one year after the end of the American Civil War. For example, you will get an error if you write commodity_desc = SWEET POTATO (that is, dropping the ES) or write commodity_desc = sweetpotatoes (that is, with no space and all lowercase letters). You will need this to make an API request later. Production and supplies of food and fiber, prices paid and received by farmers, farm labor and wages, farm finances, chemical use, and changes in the demographics of U.S. producers are only a few examples. The Census Data Query Tool (CDQT) is a web based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. So, you may need to change the format of the file path value if you will run the code on Mac OS or Linux, for example: self.output_file_path = rc:\\usda_quickstats_files\\. Corn stocks down, soybean stocks down from year earlier # drop old Value column DSFW_Peanuts: Analysis of peanut DSFW from USDA-NASS databases. Say you want to plot the acres of sweetpotatoes harvested by year for each county in North Carolina. the .gov website. Parameters need not be specified in a list and need not be Why Is it Beneficial to Access NASS Data Programmatically? N.C. To browse or use data from this site, no account is necessary. The Comprehensive R Archive Network website, Working for Peanuts: Acquiring, Analyzing, and Visualizing Publicly Available Data. After running this line of code, R will output a result. What R Tools Are Available for Getting NASS Data? You can check by using the nassqs_param_values( ) function. For most Column or Header Name values, the first value, in lowercase, is the API parameter name, like those shown above. subset of values for a given query. The Census Data Query Tool (CDQT) is a web-based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. Washington and Oregon, you can write state_alpha = c('WA', In both cases iterating over The sample Tableau dashboard is called U.S. # select the columns of interest Now that youve cleaned the data, you can display them in a plot. class(nc_sweetpotato_data_survey$Value) I built the queries simply by selecting one or more items from each of a series of dynamic dropdown menus. You can then visualize the data on a map, manipulate and export the results, or save a link for future use. Share sensitive information only on official, In this example shown below, I used Quick Stats to build a query to retrieve the number of acres of corn harvested in the US from 2000 through 2021. Lock 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. The report shows that, for the 2017 census, Minnesota had 68,822 farm operations covering 25,516,982 acres. For example, in the list of API parameters shown above, the parameter source_desc equates to Program in the Quick Stats query tool. 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. To install packages, use the code below. The site is secure. Second, you will use the specific information you defined in nc_sweetpotato_params to make the API query.