In registering for the key, for which you must provide a valid email address. 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. NASS has also developed Quick Stats Lite search tool to search commodities in its database. install.packages("tidyverse") For example, say you want to know which states have sweetpotato data available at the county level. Chambers, J. M. 2020. 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. You can define the query output as nc_sweetpotato_data. The last step in cleaning up the data involves the Value column. Census of Agriculture Top The Census is conducted every 5 years. 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. 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 query in the QuickStats API requires authentication. Each parameter is described on the Quick Stats Usage page, in its Quick Stats Columns Definition table, as shown below. NASS - Quick Stats Quick Stats database Back to dataset Quick Stats database Dynamic drill-down filtered search by Commodity, Location, and Date range, beginning with Census or Survey data. Then you can use it coders would say run the script each time you want to download NASS survey data. and rnassqs will detect this when querying data. An introductory tutorial or how to use the National Agricultural Statistics Service (NASS) Quickstats tool can be found on their website. About NASS. The Comprehensive R Archive Network (CRAN). I built the queries simply by selecting one or more items from each of a series of dynamic dropdown menus. R Programming for Data Science. 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. In this publication we will focus on two large NASS surveys. How to write a Python program to query the Quick Stats database through the Quick Stats API. Note: In some cases, the Value column will have letter codes instead of numbers. script creates a trail that you can revisit later to see exactly what object generated by the GET call, you can use nassqs_GET to list with c(). Lock That file will then be imported into Tableau Public to display visualizations about the data. NASS Reports Crop Progress (National) Crop Progress & Condition (State) 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\\. The CDL is a crop-specific land cover classification product of more than 100 crop categories grown in the United States. Federal government websites often end in .gov or .mil. N.C. It allows you to customize your query by commodity, location, or time period. Please note that you will need to fill in your NASS Quick Stats API key surrounded by quotation marks. . 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. Potter, (2019). Then you can plot this information by itself. Read our Accessing data with computer code comes in handy when you want to view data from multiple states, years, crops, and other categories. Indians. Figure 1. The API will then check the NASS data servers for the data you requested and send your requested information back. Working for Peanuts: Acquiring, Analyzing, and Visualizing Publicly Available Data. Journal of the American Society of Farm Managers and Rural Appraisers, p156-166. Based on this result, it looks like there are 47 states with sweetpotato data available at the county level, and North Carolina is one of them. It allows you to customize your query by commodity, location, or time period. This is less easy because you have to enter (or copy-paste) the key each The site is secure. Building a query often involves some trial and error. Corn stocks down, soybean stocks down from year earlier Website: https://ask.usda.gov/s/, June Turner, Director Email: / Phone: (202) 720-8257, Find contact information for Regional and State Field Offices. commitment to diversity. For example, you can write a script to access the NASS Quick Stats API and download data. 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 ggplot(data = nc_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)) + facet_wrap(~ county_name) If you have already installed the R package, you can skip to the next step (Section 7.2). For docs and code examples, visit the package web page here . A Medium publication sharing concepts, ideas and codes. Before using the API, you will need to request a free API key that your program will include with every call using the API. https://data.nal.usda.gov/dataset/nass-quick-stats. An open-standard file format that uses human-readable text to transmit data objects consisting of attribute-value pairs and array data types. 2020. For example, we discuss an R package for downloading datasets from the NASS Quick Stats API in Section 6. USDA-NASS Quick Stats (Crops) WHEAT.pdf PDF 1.42 MB . 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. In some environments you can do this with the PIP INSTALL utility. First, obtain an API key from the Quick Stats service: https://quickstats.nass.usda.gov/api. Install. Open source means that the R source code the computer code that makes R work can be viewed and edited by the public. description of the parameter(s) in question: Documentation on all of the parameters is available at https://quickstats.nass.usda.gov/api#param_define. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. For example, you some functions that return parameter names and valid values for those Each table includes diverse types of data. The USDAs National Agricultural Statistics Service (NASS) makes the departments farm agricultural data available to the public on its website through reports, maps, search tools, and its NASS Quick Stats API. You can view the timing of these NASS surveys on the calendar and in a summary of these reports. In the example program, the value for api key will be replaced with my API key. 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 . ggplot(data = sampson_sweetpotato_data) + geom_line(aes(x = year, y = harvested_sweetpotatoes_acres)). That is an average of nearly 450 acres per farm operation. The .gov means its official. 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. 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. The last thing you might want to do is save the cleaned-up data that you queried from the NASS Quick Stats API. 2017 Census of Agriculture - Census Data Query Tool, QuickStats Parameter Definitions and Operators, Agricultural Statistics Districts (ASD) zipped (.zip) ESRI shapefile format for download, https://data.nal.usda.gov/dataset/nass-quick-stats, National Agricultural Library Thesaurus Term, hundreds of sample surveys conducted each year covering virtually every aspect of U.S. agriculture, the Census of Agriculture conducted every five years providing state- and county-level aggregates. 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. Create an instance called stats of the c_usda_quick_stats class. You can read more about the available NASS Quick Stats API parameters and their definitions by checking out the help page on this topic. 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. County level data are also available via Quick Stats. National Agricultural Statistics Service (NASS) Quickstats can be found on their website. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. 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). by operation acreage in Oregon in 2012. It allows you to customize your query by commodity, location, or time period. Finally, format will be set to csv, which is a data file format type that works well in Tableau Public. We also recommend that you download RStudio from the RStudio website. # fix Value column time you begin an R session. downloading the data via an R 2020. This number versus character representation is important because R cannot add, subtract, multiply, or divide characters. 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. 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. 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 as an output file compatible for updating databases and spreadsheets, or save a link for future use. 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. nassqs_parse function that will process a request object Do this by right-clicking on the file name in Solution Explorer and then clicking [Set as Startup File] from the popup menu. After you run this code, the output is not something you can see. 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. The CoA is collected every five years and includes demographics data on farms and ranches (CoA, 2020). Once you know North Carolina has data available, you can make an API query specific to sweetpotatoes in North Carolina. provide an api key. The <- character combination means the same as the = (that is, equals) character, and R will recognize this. 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". 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. Its easiest if you separate this search into two steps. NASS_API_KEY <- "ADD YOUR NASS API KEY HERE" Parameters need not be specified in a list and need not be Many coders who use R also download and install RStudio along with it. In some cases you may wish to collect 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. 2022. Source: National Weather Service, www.nws.noaa.gov Drought Monitor, Valid February 21, 2023. Before you get started with the Quick Stats API, become familiar with its Terms of Service and Usage. # filter out census data, to keep survey data only A function in R will take an input (or many inputs) and give an output. By setting prodn_practice_desc = "ALL PRODUCTION PRACTICES", you will get results for all production practices rather than those that specifically use irrigation, for example. You can use many software programs to programmatically access the NASS survey data. The Comprehensive R Archive Network website, Working for Peanuts: Acquiring, Analyzing, and Visualizing Publicly Available Data. nassqs_params() provides the parameter names, Coding is a lot easier when you use variables because it means you dont have to remember the specific string of letters and numbers that defines your unique NASS Quick Stats API key. It allows you to customize your query by commodity, location, or time period. For this reason, it is important to pay attention to the coding language you are using. Moreover, some data is collected only at specific Why Is it Beneficial to Access NASS Data Programmatically? Note: You need to define the different NASS Quick Stats API parameters exactly as they are entered in the NASS Quick Stats API. In addition, you wont be able 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). the .gov website. NASS administers, manages, analyzes, and shares timely, accurate, and useful statistics in service to United States agriculture (NASS 2020). You can think of a coding language as a natural language like English, Spanish, or Japanese. Note that the value PASTE_YOUR_API_KEY_HERE must be replaced with your personal API key. commitment to diversity. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. many different sets of data, and in others your queries may be larger What R Tools Are Available for Getting NASS Data? Also note that I wrote this program on a Windows PC, which uses back slashes (\) in file names and folder names. Once in the tool please make your selection based on the program, sector, group, and commodity. The .gov means its official. Data request is limited to 50,000 records per the API. 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. Suggest a dataset here. Many people around the world use R for data analysis, data visualization, and much more. Have a specific question for one of our subject experts? Accessed 2023-03-04. As an example, you cannot run a non-R script using the R software program. After running these lines of code, you will get a raw data output that has over 1500 rows and close to 40 columns. do. You can get an API Key here. You can also export the plots from RStudio by going to the toolbar > Plots > Save as Image. Agricultural Resource Management Survey (ARMS). geographies. Have a specific question for one of our subject experts? 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. head(nc_sweetpotato_data, n = 3). like: The ability of rnassqs to iterate over lists of nc_sweetpotato_data_survey <- filter(nc_sweetpotato_data_sel, source_desc == "SURVEY" & county_name != "OTHER (COMBINED) COUNTIES") Now that youve cleaned and plotted the data, you can save them for future use or to share with others. You can verify your report was received by checking the Submitted date under the Status column of the My Surveys tab. It allows you to customize your query by commodity, location, or time period. The name in parentheses is the name for the same value used in the Quick Stats query tool. Ward, J. K., T. W. Griffin, D. L. Jordan, and G. T. Roberson. Feel free to download it and modify it in the Tableaue Public Desktop application to learn how to create and publish Tableau visualizations. 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.