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IPUMS extracts can take anywhere from a few minutes to a few hours to process, depending on their size and traffic levels in the extract engine.

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The RRR is designed to check whether your extract is ready to download and stop execution if it isn’t. Yes, technically, the script did throw an error, but it did so by design. Since I’ll be using IPUMS USA data on migration from the Puerto Rico Community Survey, I’ll fill in “ prcs_migration_analysis” for descriptive_name.Īfter filling in values, save the file, then click the RStudio “Knit” button, and awaaaaaaay it goes! All that’s left to do is sit back, relax, and – In fact, you can leave all the default values of these parameters if you want to analyze your most recent IPUMS USA extract, though I’d recommend filling in a better descriptive_name for the extract even in that case. coll ection <- 'usa' # The IPUMS data collection of your extract run # `ipums_data_collections()` for a list of supported # collections extract_num <- NULL # The extract number, or leave as `NULL` for your most # recent extract descriptive_name <- 'my_ipums_extract' # A descriptive label for your extract # used to rename your data files data_dir <- 'data' # The folder in which to save data, codebook, and.

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These steps are described in a bit more detail in the template itself, but we’ll walk through them quickly here.įirst, scroll down to the first code chunk, labeled “project-parameters”, and fill in values for the four parameters defined there, as shown below: the IPUMS collection and extract number of your submitted extract, a descriptive name for your extract, and a subfolder in which to save your data files. In just a few steps you’ll have your IPUMS data downloaded and the framework for a shareable analysis project. Now here we are, looking at a wall of instructions:īut don’t worry! We’ve tried to make this as painless as possible. In the popup menu, select “From Template” in the left sidebar, then “Rmd for Reproducible Research” from the list of templates, and click OK: To pull down the definition of your IPUMS USA extract number 10, you would use: extract_to_share New File > R Markdown: This works whether you created the extract with API functions or with the online extract system. Although you can create a new extract definition with define_extract_usa() or define_extract_cps(), you can also pull down the definition of a previously submitted extract with get_extract_info().

To share an extract using ipumsr, you first need an extract definition to work with. Note that the code examples here will only work once you’ve (1) requested beta access to the IPUMS microdata API by emailing and (2) set up your API key. Then, I’ll demonstrate two use-cases for those functions: sharing an analysis in an R Markdown document, and sharing an interactive application created with Shiny. json file and loading a saved definition from. In this post, I’ll first introduce the ipumsr functions for saving an extract definition to a.

Sharing extract definitions with ipumspy.

For more on the microdata API check out these other recent blog posts: The latest version of ipumsr contains new functions allowing users to call on the IPUMS microdata API directly from R or RStudio.

Download data and metadata directly into your project directory (this feature is a personal favorite).

Submit a new extract request based on a.

If you’re thinking that sounds like a pain, don’t worry, the brand new IPUMS microdata API makes it easier than ever to share your extract definitions with fellow IPUMS users!!! Using the microdata API, you and your collaborators can:

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In the past, if you wanted someone to use the same IPUMS data that you did, you would need to provide a list of samples and variables and instructions for your collaborator on how to navigate the online data extract system. Or maybe you’re a teacher with an exercise you’d like your students to review and replicate. Maybe you’d like a colleague to explore your findings. Decennial CensusĪmerican Community Survey/Puerto Rican Community SurveyĬopyright © Minnesota Population Center, University of Minnesota.Have you ever wanted to share a project using IPUMS data with a colleague, but then thought, “Oh wait! It is against the terms of use to redistribute my IPUMS data file!” They are particularly useful in conjunction with the translation tables in Volumes 4 and 5 to review the IPUMS data transformations. These codebooks do not apply to the completed IPUMS data, but describe the source samples.

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The following links provide PDF versions of all available original census sample codebooks used as input for the IPUMS data series.