You can see a full list of NASS parameters that are available and their exact names by running the following line of code. commitment to diversity. Harvesting its rich datasets presents opportunities for understanding and growth. 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 provide an api key. method is that you dont have to think about the API key for the rest of If you use Visual Studio, you can install them through the IDEs menu by following these instructions from Microsoft. Source: National Weather Service, www.nws.noaa.gov Drought Monitor, Valid February 21, 2023. Providing Central Access to USDAs Open Research Data. This article will show you how to use Python to retrieve agricultural data with the NASS Quick Stats API. The author. Generally the best way to deal with large queries is to make multiple An application program interface, or API for short, helps coders access one software program from another. That file will then be imported into Tableau Public to display visualizations about the data. It accepts a combination of what, where, and when parameters to search for and retrieve the data of interest. The next thing you might want to do is plot the results. Quick Stats System Updates provides notification of upcoming modifications. Downloading data via United States Department of Agriculture. Corn stocks down, soybean stocks down from year earlier lock ( 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. system environmental variable when you start a new R The primary benefit of rnassqs is that users need not download data through repeated . to quickly and easily download new data. For example, in the list of API parameters shown above, the parameter source_desc equates to Program in the Quick Stats query tool. An official website of the General Services Administration. 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. Instructions for how to use Tableau Public are beyond the scope of this tutorial. into a data.frame, list, or raw text. Plus, in manually selecting and downloading data using the Quick Stats website, you could introduce human error by accidentally clicking the wrong buttons and selecting data that you do not actually want. reference_period_desc "Period" - The specic time frame, within a freq_desc. You can change the value of the path name as you would like as well. I built the queries simply by selecting one or more items from each of a series of dynamic dropdown menus. First, obtain an API key from the Quick Stats service: https://quickstats.nass.usda.gov/api. 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). The types of agricultural data stored in the FDA Quick Stats database. USDA National Agricultural Statistics Service. The National Agricultural Statistics Service (NASS) is part of the United States Department of Agriculture. 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 USDA-NASS Quick Stats API has a graphic interface here: https://quickstats.nass.usda.gov. This is less easy because you have to enter (or copy-paste) the key each While there are three types of API queries, this tutorial focuses on what may be the most flexible, which is the GET /api/api_GET query. 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. Access Quick Stats (searchable database) The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. Once you know North Carolina has data available, you can make an API query specific to sweetpotatoes in North Carolina. 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. You can also write the two steps above as one step, which is shown below. Griffin, T. W., and J. K. Ward. https://data.nal.usda.gov/dataset/nass-quick-stats. Find more information at the following NC State Extension websites: Publication date: May 27, 2021 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}. Quick Stats Lite provides a more structured approach to get commonly requested statistics from our online database. The data found via the CDQT may also be accessed in the NASS Quick Stats database. replicate your results to ensure they have the same data that you Say you want to plot the acres of sweetpotatoes harvested by year for each county in North Carolina. than the API restriction of 50,000 records. "rnassqs: An 'R' package to access agricultural data via the USDA National Agricultural Statistics Service (USDA-NASS) 'Quick Stats' API." The Journal of Open Source Software. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. A&T State University. In the example shown below, I selected census table 1 Historical Highlights for the state of Minnesota from the 2017 Census of Agriculture. As mentioned in Section 1, you can visit the NASS Quick Stats website, click through the options, and download the data. 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. Here, code refers to the individual characters (that is, ASCII characters) of the coding language. 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. = 2012, but you may also want to query ranges of values. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. The USDA Economics, Statistics and Market Information System (ESMIS) contains over 2,100 publications from five agencies of the . However, ERS has no copies of the original reports. Before using the API, you will need to request a free API key that your program will include with every call using the API. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. head(nc_sweetpotato_data, n = 3). .Renviron, you can enter it in the console in a session. Tableau Public is a free version of the commercial Tableau data visualization tool. An official website of the United States government. If you need to access the underlying request To use a baking analogy, you can think of the script as a recipe for your favorite dessert. A locked padlock those queries, append one of the following to the field youd like to 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). 2017 Census of Agriculture. Need Help? the .gov website. Sys.setenv(NASSQS_TOKEN = . The census takes place once every five years, with the next one to be completed in 2022. 2022. In fact, you can use the API to retrieve the same data available through the Quick Stats search tool and the Census Data Query Tool, both of which are described above. Many coders who use R also download and install RStudio along with it. 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. USDA National Agricultural Statistics Service Information. or the like) in lapply. Skip to 6. Official websites use .govA 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. All sampled operations are mailed a questionnaire and given adequate time to respond by To install packages, use the code below. NASS makes it easy for anyone to retrieve most of the data it captures through its Quick Stats database search web page. 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. 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. Cooperative Extension is based at North Carolina's two land-grant institutions, The .gov means its official. Have a specific question for one of our subject experts? capitalized. An official website of the United States government. example, you can retrieve yields and acres with. rnassqs is a package to access the QuickStats API from 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. This tool helps users obtain statistics on the database. Moreover, some data is collected only at specific First, you will define each of the specifics of your query as nc_sweetpotato_params. organization in the United States. Lets say you are going to use the rnassqs package, as mentioned in Section 6. A Medium publication sharing concepts, ideas and codes. An open-standard file format that uses human-readable text to transmit data objects consisting of attribute-value pairs and array data types. NASS conducts hundreds of surveys every year and prepares reports covering virtually every aspect of U.S. agriculture. This image shows how working with the NASS Quick Stats API is analogous to ordering food at a restaurant. 2020. your .Renviron file and add the key. object generated by the GET call, you can use nassqs_GET to To demonstrate the use of the agricultural data obtained with the Quick Stats API, I have created a simple dashboard in Tableau Public. What Is the National Agricultural Statistics Service? example. Before sharing sensitive information, make sure you're on a federal government site. Your home for data science. Its easiest if you separate this search into two steps. You can then define this filtered data as nc_sweetpotato_data_survey. any place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, during the year. This number versus character representation is important because R cannot add, subtract, multiply, or divide characters. 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 QuickStats API offers a bewildering array of fields on which to Either 'CENSUS' or 'SURVEY'", https://quickstats.nass.usda.gov/api#param_define. Then, it will show you how to use Python to retrieve agricultural data with the NASS Quick Stats API. For example, a (D) value denotes data that are being withheld to avoid disclosing data for individual operations according to the creators of the NASS Quick Stats API. Once the The following is equivalent, A growing list of convenience functions makes querying simpler. 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. Retrieve the data from the Quick Stats server. 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. The waitstaff and restaurant use that number to keep track of your order and bill (Figure 1). 2020. 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. Next, you can define parameters of interest. United States Dept. You can think of a coding language as a natural language like English, Spanish, or Japanese. description of the parameter(s) in question: Documentation on all of the parameters is available at https://quickstats.nass.usda.gov/api#param_define. 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. Second, you will change entries in each row of the Value column so they are represented as a number, rather than a character. For Ward, J. K., T. W. Griffin, D. L. Jordan, and G. T. Roberson. The .gov means its official. Then, when you click [Run], it will start running the program with this file first. You can define the query output as nc_sweetpotato_data. by operation acreage in Oregon in 2012. To put its scale into perspective, in 2021, more than 2 million farms operated on more than 900 million acres (364 million hectares). You can then visualize the data on a map, manipulate and export the results, or save a link for future use. The site is secure. In the get_data() function of c_usd_quick_stats, create the full URL. Now you have a dataset that is easier to work with. you downloaded. Source: National Drought Mitigation Center, 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. Alternatively, you can query values Open source means that the R source code the computer code that makes R work can be viewed and edited by the public. Combined with an assert from the Running the script is similar to your pulling out the recipe and working through the steps when you want to make this dessert. You are also going to use the tidyverse package, which is called a meta-package because it is a package of packages that helps you work with your datasets easily and keep them tidy.. # fix Value column ~ 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 While it does not access all the data available through Quick Stats, you may find it easier to use. 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. to automate running your script, since it will stop and ask you to sampson_sweetpotato_data <- filter(nc_sweetpotato_data, county_name == "SAMPSON") token API key, default is to use the value stored in .Renviron . Some care After running this line of code, R will output a result. nassqs_params() provides the parameter names, 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. These collections of R scripts are known as R packages. You can also make small changes to the script to download new types of data. 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. Second, you will use the specific information you defined in nc_sweetpotato_params to make the API query. Once your R packages are loaded, you can tell R what your NASS Quick Stats API key is. value. The use of a callback function parameter, not shown in the example above, is beyond the scope of this article. NASS administers, manages, analyzes, and shares timely, accurate, and useful statistics in service to United States agriculture (NASS 2020). The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. Depending on what agency your survey is from, you will need to contact that agency to update your record. Before you get started with the Quick Stats API, become familiar with its Terms of Service and Usage. It is simple and easy to use, and provides some functions to help navigate the bewildering complexity of some Quick Stats data. 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. One of the main missions of organizations like the Comprehensive R Archive Network is to curate R packages and make sure their creators have met user-friendly documentation standards. downloading the data via an R About NASS. request. Finally, you can define your last dataset as nc_sweetpotato_data. 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. Each language has its own unique way of representing meaning, using these characters and its own grammatical rules for combining these characters. NC State University and NC How to write a Python program to query the Quick Stats database through the Quick Stats API. rnassqs package and the QuickStats database, youll be able year field with the __GE modifier attached to Potter N (2022). 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. 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. The API only returns queries that return 50,000 or less records, so There are R packages to do linear modeling (such as the lm R package), make pretty plots (such as the ggplot2 R package), and many more. The name in parentheses is the name for the same value used in the Quick Stats query tool. 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. they became available in 2008, you can iterate by doing the However, the NASS also allows programmatic access to these data via an application program interface as described in Section 2. Why Is it Beneficial to Access NASS Data Programmatically? Parameters need not be specified in a list and need not be 'OR'). N.C. nassqs does handles Federal government websites often end in .gov or .mil. 2017 Ag Atlas Maps. Including parameter names in nassqs_params will return a Also, the parameter values be replaced with specific parameter-value pairs to search for the desired data. Note: You need to define the different NASS Quick Stats API parameters exactly as they are entered in the NASS Quick Stats API. Corn stocks down, soybean stocks down from year earlier time, but as you become familiar with the variables and calls of the
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