how to cite usda nass quick stats

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. Providing Central Access to USDAs Open Research Data, MULTIPOLYGON (((-155.54211 19.08348, -155.68817 18.91619, -155.93665 19.05939, -155.90806 19.33888, -156.07347 19.70294, -156.02368 19.81422, -155.85008 19.97729, -155.91907 20.17395, -155.86108 20.26721, -155.78505 20.2487, -155.40214 20.07975, -155.22452 19.99302, -155.06226 19.8591, -154.80741 19.50871, -154.83147 19.45328, -155.22217 19.23972, -155.54211 19.08348)), ((-156.07926 20.64397, -156.41445 20.57241, -156.58673 20.783, -156.70167 20.8643, -156.71055 20.92676, -156.61258 21.01249, -156.25711 20.91745, -155.99566 20.76404, -156.07926 20.64397)), ((-156.75824 21.17684, -156.78933 21.06873, -157.32521 21.09777, -157.25027 21.21958, -156.75824 21.17684)), ((-157.65283 21.32217, -157.70703 21.26442, -157.7786 21.27729, -158.12667 21.31244, -158.2538 21.53919, -158.29265 21.57912, -158.0252 21.71696, -157.94161 21.65272, -157.65283 21.32217)), ((-159.34512 21.982, -159.46372 21.88299, -159.80051 22.06533, -159.74877 22.1382, -159.5962 22.23618, -159.36569 22.21494, -159.34512 21.982)), ((-94.81758 49.38905, -94.64 48.84, -94.32914 48.67074, -93.63087 48.60926, -92.61 48.45, -91.64 48.14, -90.83 48.27, -89.6 48.01, -89.272917 48.019808, -88.378114 48.302918, -87.439793 47.94, -86.461991 47.553338, -85.652363 47.220219, -84.87608 46.900083, -84.779238 46.637102, -84.543749 46.538684, -84.6049 46.4396, -84.3367 46.40877, -84.14212 46.512226, -84.091851 46.275419, -83.890765 46.116927, -83.616131 46.116927, -83.469551 45.994686, -83.592851 45.816894, -82.550925 45.347517, -82.337763 44.44, -82.137642 43.571088, -82.43 42.98, -82.9 42.43, -83.12 42.08, -83.142 41.975681, -83.02981 41.832796, -82.690089 41.675105, -82.439278 41.675105, -81.277747 42.209026, -80.247448 42.3662, -78.939362 42.863611, -78.92 42.965, -79.01 43.27, -79.171674 43.466339, -78.72028 43.625089, -77.737885 43.629056, -76.820034 43.628784, -76.5 44.018459, -76.375 44.09631, -75.31821 44.81645, -74.867 45.00048, -73.34783 45.00738, 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-76.30162 37.917945, -76.25874 36.9664, -75.9718 36.89726, -75.86804 36.55125, -75.72749 35.55074, -76.36318 34.80854, -77.397635 34.51201, -78.05496 33.92547, -78.55435 33.86133, -79.06067 33.49395, -79.20357 33.15839, -80.301325 32.509355, -80.86498 32.0333, -81.33629 31.44049, -81.49042 30.72999, -81.31371 30.03552, -80.98 29.18, -80.535585 28.47213, -80.53 28.04, -80.056539 26.88, -80.088015 26.205765, -80.13156 25.816775, -80.38103 25.20616, -80.68 25.08, -81.17213 25.20126, -81.33 25.64, -81.71 25.87, -82.24 26.73, -82.70515 27.49504, -82.85526 27.88624, -82.65 28.55, -82.93 29.1, -83.70959 29.93656, -84.1 30.09, -85.10882 29.63615, -85.28784 29.68612, -85.7731 30.15261, -86.4 30.4, -87.53036 30.27433, -88.41782 30.3849, -89.18049 30.31598, -89.593831 30.159994, -89.413735 29.89419, -89.43 29.48864, -89.21767 29.29108, -89.40823 29.15961, -89.77928 29.30714, -90.15463 29.11743, -90.880225 29.148535, -91.626785 29.677, -92.49906 29.5523, -93.22637 29.78375, -93.84842 29.71363, -94.69 29.48, -95.60026 28.73863, -96.59404 28.30748, -97.14 27.83, -97.37 27.38, -97.38 26.69, -97.33 26.21, -97.14 25.87, -97.53 25.84, -98.24 26.06, -99.02 26.37, -99.3 26.84, -99.52 27.54, -100.11 28.11, -100.45584 28.69612, -100.9576 29.38071, -101.6624 29.7793, -102.48 29.76, -103.11 28.97, -103.94 29.27, -104.45697 29.57196, -104.70575 30.12173, -105.03737 30.64402, -105.63159 31.08383, -106.1429 31.39995, -106.50759 31.75452, -108.24 31.754854, -108.24194 31.34222, -109.035 31.34194, -111.02361 31.33472, -113.30498 32.03914, -114.815 32.52528, -114.72139 32.72083, -115.99135 32.61239, -117.12776 32.53534, -117.295938 33.046225, -117.944 33.621236, -118.410602 33.740909, -118.519895 34.027782, -119.081 34.078, -119.438841 34.348477, -120.36778 34.44711, -120.62286 34.60855, -120.74433 35.15686, -121.71457 36.16153, -122.54747 37.55176, -122.51201 37.78339, -122.95319 38.11371, -123.7272 38.95166, -123.86517 39.76699, -124.39807 40.3132, -124.17886 41.14202, -124.2137 41.99964, -124.53284 42.76599, -124.14214 43.70838, -124.020535 44.615895, -123.89893 45.52341, -124.079635 46.86475, -124.39567 47.72017, -124.68721 48.184433, -124.566101 48.379715, -123.12 48.04, -122.58736 47.096, -122.34 47.36, -122.5 48.18, -122.84 49, -120 49, -117.03121 49, -116.04818 49, -113 49, -110.05 49, -107.05 49, -104.04826 48.99986, -100.65 49, -97.22872 49.0007, -95.15907 49, -95.15609 49.38425, -94.81758 49.38905)), ((-153.006314 57.115842, -154.00509 56.734677, -154.516403 56.992749, -154.670993 57.461196, -153.76278 57.816575, -153.228729 57.968968, -152.564791 57.901427, -152.141147 57.591059, -153.006314 57.115842)), ((-165.579164 59.909987, -166.19277 59.754441, -166.848337 59.941406, -167.455277 60.213069, -166.467792 60.38417, -165.67443 60.293607, -165.579164 59.909987)), ((-171.731657 63.782515, -171.114434 63.592191, -170.491112 63.694975, -169.682505 63.431116, -168.689439 63.297506, -168.771941 63.188598, -169.52944 62.976931, -170.290556 63.194438, -170.671386 63.375822, -171.553063 63.317789, -171.791111 63.405846, -171.731657 63.782515)), ((-155.06779 71.147776, -154.344165 70.696409, -153.900006 70.889989, -152.210006 70.829992, -152.270002 70.600006, -150.739992 70.430017, -149.720003 70.53001, -147.613362 70.214035, -145.68999 70.12001, -144.920011 69.989992, -143.589446 70.152514, -142.07251 69.851938, -140.985988 69.711998, -140.992499 66.000029, -140.99777 60.306397, -140.012998 60.276838, -139.039 60.000007, -138.34089 59.56211, -137.4525 58.905, -136.47972 59.46389, -135.47583 59.78778, -134.945 59.27056, -134.27111 58.86111, -133.355549 58.410285, -132.73042 57.69289, -131.70781 56.55212, -130.00778 55.91583, -129.979994 55.284998, -130.53611 54.802753, -131.085818 55.178906, -131.967211 55.497776, -132.250011 56.369996, -133.539181 57.178887, -134.078063 58.123068, -135.038211 58.187715, -136.628062 58.212209, -137.800006 58.499995, -139.867787 59.537762, -140.825274 59.727517, -142.574444 60.084447, -143.958881 59.99918, -145.925557 60.45861, -147.114374 60.884656, -148.224306 60.672989, -148.018066 59.978329, -148.570823 59.914173, -149.727858 59.705658, -150.608243 59.368211, -151.716393 59.155821, -151.859433 59.744984, -151.409719 60.725803, -150.346941 61.033588, -150.621111 61.284425, -151.895839 60.727198, -152.57833 60.061657, -154.019172 59.350279, -153.287511 58.864728, -154.232492 58.146374, -155.307491 57.727795, -156.308335 57.422774, -156.556097 56.979985, -158.117217 56.463608, -158.433321 55.994154, -159.603327 55.566686, -160.28972 55.643581, -161.223048 55.364735, -162.237766 55.024187, -163.069447 54.689737, -164.785569 54.404173, -164.942226 54.572225, -163.84834 55.039431, -162.870001 55.348043, -161.804175 55.894986, -160.563605 56.008055, -160.07056 56.418055, -158.684443 57.016675, -158.461097 57.216921, -157.72277 57.570001, -157.550274 58.328326, -157.041675 58.918885, -158.194731 58.615802, -158.517218 58.787781, -159.058606 58.424186, -159.711667 58.93139, -159.981289 58.572549, -160.355271 59.071123, -161.355003 58.670838, -161.968894 58.671665, -162.054987 59.266925, -161.874171 59.633621, -162.518059 59.989724, -163.818341 59.798056, -164.662218 60.267484, -165.346388 60.507496, -165.350832 61.073895, -166.121379 61.500019, -165.734452 62.074997, -164.919179 62.633076, -164.562508 63.146378, -163.753332 63.219449, -163.067224 63.059459, -162.260555 63.541936, -161.53445 63.455817, -160.772507 63.766108, -160.958335 64.222799, -161.518068 64.402788, -160.777778 64.788604, -161.391926 64.777235, -162.45305 64.559445, -162.757786 64.338605, -163.546394 64.55916, -164.96083 64.446945, -166.425288 64.686672, -166.845004 65.088896, -168.11056 65.669997, -166.705271 66.088318, -164.47471 66.57666, -163.652512 66.57666, -163.788602 66.077207, -161.677774 66.11612, -162.489715 66.735565, -163.719717 67.116395, -164.430991 67.616338, -165.390287 68.042772, -166.764441 68.358877, -166.204707 68.883031, -164.430811 68.915535, -163.168614 69.371115, -162.930566 69.858062, -161.908897 70.33333, -160.934797 70.44769, -159.039176 70.891642, -158.119723 70.824721, -156.580825 71.357764, -155.06779 71.147776))), USDA National Agricultural Statistics Service, 005:042 - Department of Agriculture - Agricultural Estimates, 005:043 - Department of Agriculture - Census of Agriculture, 005:050 - Department of Agriculture - Commodity Purchases, 005:15 - National Agricultural Statistics Service. Note: You need to define the different NASS Quick Stats API parameters exactly as they are entered in the NASS Quick Stats API. and you risk forgetting to add it to .gitignore. 2019-67021-29936 from the USDA National Institute of Food and Agriculture. 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. 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 request. To demonstrate the use of the agricultural data obtained with the Quick Stats API, I have created a simple dashboard in Tableau Public. Public domain information on the National Agricultural Statistics Service (NASS) Web pages may be freely downloaded and reproduced. # select the columns of interest One way of The <- character combination means the same as the = (that is, equals) character, and R will recognize this. .gitignore if youre using github. is needed if subsetting by geography. There are at least two good reasons to do this: Reproducibility. downloading the data via an R The information on this page (the dataset metadata) is also available in these formats: The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). There are thousands of R packages available online (CRAN 2020). However, it is requested that in any subsequent use of this work, USDA-NASS be given appropriate acknowledgment. a list of parameters is helpful. nassqs_parse function that will process a request object We summarize the specifics of these benefits in Section 5. Before using the API, you will need to request a free API key that your program will include with every call using the API. On the other hand, if that person asked you to add 1 and 2, you would know exactly what to do. (R coders say you need to load your R packages.) You can do that by running the code below (Section 7.2). Not all NASS data goes back that far, though. those queries, append one of the following to the field youd like to # filter out census data, to keep survey data only Click the arrow to access Quick Stats. This number versus character representation is important because R cannot add, subtract, multiply, or divide characters. All sampled operations are mailed a questionnaire and given adequate time to respond by The United States is blessed with fertile soil and a huge agricultural industry. Email: askusda@usda.gov It also makes it much easier for people seeking to at least two good reasons to do this: Reproducibility. Most queries will probably be for specific values such as year 2017 Census of Agriculture. Programmatic access refers to the processes of using computer code to select and download data. However, ERS has no copies of the original reports. following: Subsetting by geography works similarly, looping over the geography 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 On the site you have the ability to filter based on numerous commodity types. # check the class of Value column In the example shown below, I selected census table 1 Historical Highlights for the state of Minnesota from the 2017 Census of Agriculture. An official website of the United States government. time you begin an R session. After running these lines of code, you will get a raw data output that has over 1500 rows and close to 40 columns. Second, you will use the specific information you defined in nc_sweetpotato_params to make the API query. The API Usage page provides instructions for its use. queries subset by year if possible, and by geography if not. Figure 1. Have a specific question for one of our subject experts? Journal of Open Source Software , 4(43 . 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. Web Page Resources For example, if youd like data from both In some cases you may wish to collect The resulting plot is a bit busy because it shows you all 96 counties that have sweetpotato data. Here is the most recent United States Summary and State Data (PDF, 27.9 MB), a statistical summary of the Census of Agriculture. The example Python program shown in the next section will call the Quick Stats with a series of parameters. Here, tidy has a specific meaning: all observations are represented as rows, and all the data categories associated with that observation are represented as columns. They are (1) the Agriculture Resource Management Survey (ARMS) and (2) the Census of Agriculture (CoA). The USDA-NASS Quick Stats API has a graphic interface here: https://quickstats.nass.usda.gov. You will need this to make an API request later. What Is the National Agricultural Statistics Service? Public domain information on the National Agricultural Statistics Service (NASS) Web pages may be freely downloaded and reproduced. Agricultural Resource Management Survey (ARMS). If you use it, be sure to install its Python Application support. # fix Value column For docs and code examples, visit the package web page here . Then use the as.numeric( ) function to tell R each row is a number, not a character. This will create a new AG-903. 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. Please note that you will need to fill in your NASS Quick Stats API key surrounded by quotation marks. First, you will define each of the specifics of your query as nc_sweetpotato_params. Statistics Service, Washington, D.C. URL: https://quickstats.nass.usda.gov [accessed Feb 2023] . 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. 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. multiple variables, geographies, or time frames without having to Ward, J. K., T. W. Griffin, D. L. Jordan, and G. T. Roberson. It is simple and easy to use, and provides some functions to help navigate the bewildering complexity of some Quick Stats data. 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. The use of a callback function parameter, not shown in the example above, is beyond the scope of this article. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). Data by subject gives you additional information for a particular subject area or commodity. That is an average of nearly 450 acres per farm operation. nc_sweetpotato_data_raw <- nassqs(nc_sweetpotato_params). 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 modify: In the above parameter list, year__GE is the Federal government websites often end in .gov or .mil. You can think of a coding language as a natural language like English, Spanish, or Japanese. Now you have a dataset that is easier to work with. 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. You can register for a NASS Quick Stats API key at the Quick Stats API website (click on Request API Key). 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? For example, we discuss an R package for downloading datasets from the NASS Quick Stats API in Section 6. Healy. function, which uses httr::GET to make an HTTP GET request In this publication, the word variable refers to whatever is on the left side of the <- character combination.

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