First, you will define each of the specifics of your query as nc_sweetpotato_params. 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. Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. # check the class of Value column many different sets of data, and in others your queries may be larger Access Quick Stats (searchable database) The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. An official website of the United States government. Where available, links to the electronic reports is provided. 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. Any person using products listed in . For example, if someone asked you to add A and B, you would be confused. You can view the timing of these NASS surveys on the calendar and in a summary of these reports. Quick Stats. For example, in the list of API parameters shown above, the parameter source_desc equates to Program in the Quick Stats query tool. Didn't find what you're looking for? Census of Agriculture Top The Census is conducted every 5 years. I built the queries simply by selecting one or more items from each of a series of dynamic dropdown menus. This is often the fastest method and provides quick feedback on the and predecessor agencies, U.S. Department of Agriculture (USDA). All of these reports were produced by Economic Research Service (ERS. If you have already installed the R package, you can skip to the next step (Section 7.2). Have a specific question for one of our subject experts? 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. A list of the valid values for a given field is available via Here we request the number of farm operators In R, you would write x <- 1. Columns for this particular dataset would include the year harvested, county identification number, crop type, harvested amount, the units of the harvested amount, and other categories. The QuickStats API offers a bewildering array of fields on which to sampson_sweetpotato_data <- filter(nc_sweetpotato_data, county_name == "SAMPSON") 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. NC State University and NC This will call its initializer (__init__()) function, which sets the API key, the base URL for the Quick Stats API, and the name of the folder where the class will write the output CSV file that contains agricultural data. 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. Copy BibTeX Tags API reproducibility agriculture economics Altmetrics Markdown badge Figure 1. If youre not sure what spelling and case the NASS Quick Stats API uses, you can always check by clicking through the NASS Quick Stats website. developing the query is to use the QuickStats web interface. Healy. You can add a file to your project directory and ignore it via 1987. 2020. Each parameter is described on the Quick Stats Usage page, in its Quick Stats Columns Definition table, as shown below. There are thousands of R packages available online (CRAN 2020). Data by subject gives you additional information for a particular subject area or commodity. time you begin an R session. commitment to diversity. 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. You can also refer to these software programs as different coding languages because each uses a slightly different coding style (or grammar) to carry out a task. Say you want to plot the acres of sweetpotatoes harvested by year for each county in North Carolina. While I used the free Microsoft Visual Studio Community 2022 integrated development ide (IDE) to write and run the Python program for this tutorial, feel free to use your favorite code editor or IDE. This article will show you how to use Python to retrieve agricultural data with the NASS Quick Stats API. The author. If you use NASS collects and manages diverse types of agricultural data at the national, state, and county levels. Peng, R. D. 2020. To improve data accessibility and sharing, the NASS developed a Quick Stats website where you can select and download data from two of the agencys surveys. Code is similar to the characters of the natural language, which can be combined to make a sentence. An official website of the General Services Administration. All sampled operations are mailed a questionnaire and given adequate time to respond by 2019. In some cases you may wish to collect As an analogy, you can think of R as a plain text editor (such as Notepad), while RStudio is more like Microsoft Word with additional tools and options. Do this by right-clicking on the file name in Solution Explorer and then clicking [Set as Startup File] from the popup menu. For docs and code examples, visit the package web page here . 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. Web Page Resources For most Column or Header Name values, the first value, in lowercase, is the API parameter name, like those shown above. Either 'CENSUS' or 'SURVEY'", https://quickstats.nass.usda.gov/api#param_define. There are times when your data look like a 1, but R is really seeing it as an A. The data found via the CDQT may also be accessed in the NASS Quick Stats database. While it does not access all the data available through Quick Stats, you may find it easier to use. The query in 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. to the Quick Stats API. Before sharing sensitive information, make sure you're on a federal government site. U.S. Department of Agriculture, National Agricultural Statistics Service (NASS). Griffin, T. W., and J. K. Ward. Contact a specialist. Statistics by State Explore Statistics By Subject Citation Request Most of the information available from this site is within the public domain. Finally, format will be set to csv, which is a data file format type that works well in Tableau Public. For example, say you want to know which states have sweetpotato data available at the county level. Call the function stats.get_data() with the parameters string and the name of the output file (without the extension). This image shows how working with the NASS Quick Stats API is analogous to ordering food at a restaurant. You can see a full list of NASS parameters that are available and their exact names by running the following line of code. Click the arrow to access Quick Stats. This reply is called an API response. AG-903. Including parameter names in nassqs_params will return a into a data.frame, list, or raw text. 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. and you risk forgetting to add it to .gitignore. Website: https://ask.usda.gov/s/, June Turner, Director Email: / Phone: (202) 720-8257, Find contact information for Regional and State Field Offices. These collections of R scripts are known as R packages. You can do this by including the logic statement source_description == SURVEY & county_name != "OTHER (COMBINED) COUNTIES" inside the filter function. install.packages("tidyverse") Corn stocks down, soybean stocks down from year earlier ggplot(data = nc_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)) + facet_wrap(~ county_name) And data scientists, analysts, engineers, and any member of the public can freely tap more than 46 million records of farm-related data managed by the U.S. Department of Agriculture (USDA). Before you get started with the Quick Stats API, become familiar with its Terms of Service and Usage. The CDL is a crop-specific land cover classification product of more than 100 crop categories grown in the United States. Thsi package is now on CRAN and can be installed through the typical method: install.packages ("usdarnass") Alternatively, the most up-to-date version of the package can be installed with the devtools package. rnassqs (R NASS Quick Stats) rnassqs allows users to access the USDA's National Agricultural Statistics Service (NASS) Quick Stats data through their API. 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 your R packages are loaded, you can tell R what your NASS Quick Stats API key is. More specifically, the list defines whether NASS data are aggregated at the national, state, or county scale. 2019-67021-29936 from the USDA National Institute of Food and Agriculture. Tip: Click on the images to view full-sized and readable versions. You can read more about the available NASS Quick Stats API parameters and their definitions by checking out the help page on this topic. modify: In the above parameter list, year__GE is the its a good idea to check that before running a query. In this publication we will focus on two large NASS surveys. This example in Section 7.8 represents a path name for a Mac computer, but a PC path to the desktop might look more like C:\Users\your\Desktop\nc_sweetpotato_data_query_on_20201001.csv. In addition, you wont be able lock ( To demonstrate the use of the agricultural data obtained with the Quick Stats API, I have created a simple dashboard in Tableau Public. The name in parentheses is the name for the same value used in the Quick Stats query tool. However, beware that this will be a development version: # install.packages ("devtools") devtools :: install_github ("rdinter . R sessions will have the variable set automatically, It is best to start by iterating over years, so that if you nassqs does handles The United States is blessed with fertile soil and a huge agricultural industry. ~ Providing Timely, Accurate and Useful Statistics in Service to U.S. Agriculture ~, County and District Geographic Boundaries, Crop Condition and Soil Moisture Analytics, Agricultural Statistics Board Corrections, Still time to respond to the 2022 Census of Agriculture, USDA to follow up with producers who have not yet responded, 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), 2022 Census of Agriculture due next week Feb. 6, Corn and soybean production down in 2022, USDA reports nc_sweetpotato_data_sel <- select(nc_sweetpotato_data_raw, county_name, year, source_desc, Value) U.S. National Agricultural Statistics Service (NASS) Summary "The USDA's National Agricultural Statistics Service (NASS) conducts hundreds of surveys every year and prepares reports covering virtually every aspect of U.S. agriculture. The sample Tableau dashboard is called U.S. The API will then check the NASS data servers for the data you requested and send your requested information back. This is less easy because you have to enter (or copy-paste) the key each Its very easy to export data stored in nc_sweetpotato_data or sampson_sweetpotato_data as a comma-separated variable file (.CSV) in R. To do this, you can use the write_csv( ) function. A locked padlock Dont repeat yourself. Building a query often involves some trial and error. year field with the __GE modifier attached to Data request is limited to 50,000 records per the API. Each language has its own unique way of representing meaning, using these characters and its own grammatical rules for combining these characters. However, the NASS also allows programmatic access to these data via an application program interface as described in Section 2. valid before attempting to access the data: Once youve built a query, running it is easy: Putting all of the above together, we have a script that looks The types of agricultural data stored in the FDA Quick Stats database. 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\\. rnassqs: Access the NASS 'Quick Stats' API. ggplot(data = sampson_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)). Quick Stats Lite provides a more structured approach to get commonly requested statistics from . 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). 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. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. You can also set the environmental variable directly with 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. Need Help? Create a worksheet that shows the number of acres harvested for top commodities from 1997 through 2021. If you are interested in trying Visual Studio Community, you can install it here. To submit, please register and login first. Corn stocks down, soybean stocks down from year earlier If you use Visual Studio, you can install them through the IDEs menu by following these instructions from Microsoft. You can also make small changes to the script to download new types of data. Then you can use it coders would say run the script each time you want to download NASS survey data. 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. Language feature sets can be added at any time after you install Visual Studio. Parameters need not be specified in a list and need not be 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. Retrieve the data from the Quick Stats server. As an example, you cannot run a non-R script using the R software program. 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. which at the time of this writing are. Skip to 6. Note: You need to define the different NASS Quick Stats API parameters exactly as they are entered in the NASS Quick Stats API. You can think of a coding language as a natural language like English, Spanish, or Japanese. This publication printed on: March 04, 2023, Getting Data from the National Agricultural Statistics Service (NASS) Using R. Skip to 1. If you use this function on the Value column of nc_sweetpotato_data_survey, R will return character, but you want R to return numeric. Second, you will use the specific information you defined in nc_sweetpotato_params to make the API 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. Next, you can define parameters of interest. want say all county cash rents on irrigated land for every year since This function replaces spaces and special characters in text with escape codes that can be passed, as part of the full URL, to the Quick Stats web server. How to Develop a Data Analytics Web App in 3 Steps Alan Jones in CodeFile Data Analysis with ChatGPT and Jupyter Notebooks Zach Quinn in Pipeline: A Data Engineering Resource Creating The Dashboard That Got Me A Data Analyst Job Offer Youssef Hosni in Level Up Coding 20 Pandas Functions for 80% of your Data Science Tasks Help Status Writers Blog Use nass_count to determine number of records in query. Grain sorghum (Sorghum bicolor) is one of the most important cereal crops worldwide and is the third largest grain crop grown in the United. object generated by the GET call, you can use nassqs_GET to 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). Agricultural Commodity Production by Land Area. An open-standard file format that uses human-readable text to transmit data objects consisting of attribute-value pairs and array data types. To cite rnassqs in publications, please use: Potter NA (2019). Accessed: 01 October 2020. This number versus character representation is important because R cannot add, subtract, multiply, or divide characters. Statistics Service, Washington, D.C. URL: https://quickstats.nass.usda.gov [accessed Feb 2023] . There is no description for this organization, National Agricultural Statistics Service, Department of Agriculture. Accessed online: 01 October 2020. Additionally, the CoA includes data on land use, land ownership, agricultural production practices, income, and expenses at the farm and ranch level. Then we can make a query. 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 To run the script, you click a button in the software program or use a keyboard stroke that tells your computer to start going through the script step by step. like: The ability of rnassqs to iterate over lists of It allows you to customize your query by commodity, location, or time period. Read our Quick Stats System Updates provides notification of upcoming modifications. Texas Crop Progress and Condition (February 2023) USDA, National Agricultural Statistics Service, Southern Plains Regional Field Office Seven Day Observed Regional Precipitation, February 26, 2023. 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. nassqs_parse function that will process a request object geographies. Accessing data with computer code comes in handy when you want to view data from multiple states, years, crops, and other categories. capitalized. For example, if youd like data from both reference_period_desc "Period" - The specic time frame, within a freq_desc. This work is supported by grant no. The API response is the food made by the kitchen based on the written order from the customer to the waitstaff. replicate your results to ensure they have the same data that you Have a specific question for one of our subject experts? 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 USDA-NASS Quick Stats (Crops) WHEAT.pdf PDF 1.42 MB . You can check by using the nassqs_param_values( ) function. You can get an API Key here. It accepts a combination of what, where, and when parameters to search for and retrieve the data of interest. Do pay attention to the formatting of the path name. DRY. Remember to request your personal Quick Stats API key and paste it into the value for self.api_key in the __init__() function in the c_usda_quick_stats class. both together, but you can replicate that functionality with low-level 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. some functions that return parameter names and valid values for those Agricultural Census since 1997, which you can do with something like. request. example. You might need to do extra cleaning to remove these data before you can plot. A&T State University. api key is in a file, you can use it like this: If you dont want to add the API key to a file or store it in your R Programming for Data Science. Instructions for how to use Tableau Public are beyond the scope of this tutorial. Email: askusda@usda.gov Quick Stats Lite provides a more structured approach to get commonly requested statistics from our online database. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). Beginning in May 2010, NASS agricultural chemical use data are published to the Quick Stats 2.0 database only (full-text publications have been discontinued), and can be found under the NASS Chemical Usage Program. # select the columns of interest Because R is accessible to so many people, there is a great deal of collaboration and sharing of R resources, scripts, and knowledge. Access Quick Stats Lite . # plot Sampson county data than the API restriction of 50,000 records. You can define the query output as nc_sweetpotato_data. To browse or use data from this site, no account is necessary. secure websites. These include: R, Python, HTML, and many more. Many coders who use R also download and install RStudio along with it. class(nc_sweetpotato_data_survey$Value) Sys.setenv(NASSQS_TOKEN = . Here is the format of the base URL that will be used in this articles example: http://quickstats.nass.usda.gov/api/api_GET/?key=api key&{parameter parameter}&format={json | csv | xml}. For more specific information please contact nass@usda.gov or call 1-800-727-9540. United States Dept. Decode the data Quick Stats data in utf8 format. a list of parameters is helpful. The agency has the distinction of being known as The Fact Finders of U.S. Agriculture due to the abundance of . Please click here to provide feedback for any of the tools on this page. This is why functions are an important part of R packages; they make coding easier for you. Official websites use .govA Besides requesting a NASS Quick Stats API key, you will also need to make sure you have an up-to-date version of R. If not, you can download R from The Comprehensive R Archive Network. However, other parameters are optional. The Cropland Data Layer (CDL) is a product of the USDA National Agricultural Statistics Service (NASS) with the mission "to provide timely, accurate and useful statistics in service to U.S. agriculture" (Johnson and Mueller, 2010, p. 1204). National Agricultural Statistics Service (NASS) Quickstats can be found on their website. The database allows custom extracts based on commodity, year, and selected counties within a State, or all counties in one or more States. .gitignore if youre using github. they became available in 2008, you can iterate by doing the by operation acreage in Oregon in 2012. The CoA is collected every five years and includes demographics data on farms and ranches (CoA, 2020). Finally, it will explain how to use Tableau Public to visualize the data. Once you have a sum of all counties in a state will not necessarily equal the state Generally the best way to deal with large queries is to make multiple national agricultural statistics service (NASS) at the USDA. The census takes place once every five years, with the next one to be completed in 2022. However, the NASS also allows programmatic access to these data via an application program interface as described in Section 2. Read our 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. For Often 'county', 'state', or 'national', but can include other levels as well", #> [2] "source_desc: Data source. Not all NASS data goes back that far, though.