{"version":"https://jsonfeed.org/version/1","title":"rOpenSci - open tools for open science","home_page_url":"https://ropensci.org/rbloggers/index.xml","feed_url":"https://ropensci.org/rbloggers/index.xml/index.json","description":"Open Tools and R Packages for Open Science","items":[{"id":"https://ropensci.org/blog/2026/09/29/celebrating-ropensci/","title":"Celebrating the rOpenSci Community","content_text":"\u003cp\u003erOpenSci turns 15 and I\u0026rsquo;ve been a part of this community for a good chunk of that time. As I reflected on those years, a lot of great memories came to mind, and I realized some of them taught me some lessons that I would love to share.\u003c/p\u003e\n\u003ch2 id=\"stretch-your-comfort-zone\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#stretch-your-comfort-zone\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nStretch your comfort zone\n\u003c/h2\u003e\u003cp\u003eEarly in 2018 I came across \u003ca href=\"/blog/2018/02/08/unconf2018/\"\u003ethis post\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003e\u003cstrong\u003eApply to attend rOpenSci unconf 2018!\u003c/strong\u003e\u003cbr\u003e\nWe\u0026rsquo;re organizing unconf18 to bring together scientists, developers, and open data enthusiasts from academia, industry, government, and non-profits to get together for a couple of days to hack on various projects and generally enrich our community.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp\u003eIn hindsight I was a good fit. I had recently transitioned from academia to my first job as a research software engineer. And yet, did I think I was a solid candidate? Oh no, I had lots of doubts.\u003c/p\u003e\n\u003cp\u003eBut I know the greatest things often happen a little stretch outside your comfort zone. So I applied anyway, got invited, and spent two days collaborating with \u003ca href=\"https://unconf18.ropensci.org/#participants\"\u003ean incredible bunch of people\u003c/a\u003e. Some of them were already rockstars, many others eventually became influential in their own niche, and all of them had this great attitude that at the time I lacked words to describe. I now do: they were respectful and kind.\u003c/p\u003e\n\u003ch2 id=\"be-respectful-and-kind\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#be-respectful-and-kind\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nBe respectful and kind\n\u003c/h2\u003e\u003cp\u003eIn 2022 \u003ca href=\"/blog/2022/09/22/launch-champions-program/\"\u003erOpenSci launched the first cohort of the rOpenSci Champions Program\u003c/a\u003e. By then I already had a few years of experience as an associate editor of \u003ca href=\"/software-review/\"\u003erOpenSci software peer-review\u003c/a\u003e, and \u003ca href=\"/author/yanina-bellini-saibene/\"\u003eYani\u003c/a\u003e invited me to talk to our champions about the process.\u003c/p\u003e\n\u003cp\u003eAs I prepared \u003ca href=\"https://ropensci-training.github.io/software-review/en/\"\u003ethat talk\u003c/a\u003e and discussed some ideas with Yani, she made me realize how much the rOpenSci community cares about the way we communicate with one another\u003csup id=\"fnref:1\"\u003e\u003ca href=\"#fn:1\" class=\"footnote-ref\" role=\"doc-noteref\"\u003e1\u003c/a\u003e\u003c/sup\u003e. So much so that our guides for \u003ca href=\"https://devguide.ropensci.org/softwarereview_reviewer.html\"\u003ereviewers\u003c/a\u003e and \u003ca href=\"https://devguide.ropensci.org/softwarereview_editor.html\"\u003eeditors\u003c/a\u003e open with this message:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003erOpenSci\u0026rsquo;s community is our best asset. We aim for reviews to be open, non-adversarial, and focused on improving software quality. Be respectful and kind! See our reviewers\u0026rsquo; guide and \u003ca href=\"/code-of-conduct/\"\u003ecode of conduct\u003c/a\u003e for more.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp\u003eComing from such a deeply technical guide, that opening might surprise you. But it makes sense to me now; broken code is way easier to fix than broken human relationships.\u003c/p\u003e\n\u003ch2 id=\"contribute-in-your-own-way\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#contribute-in-your-own-way\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nContribute in your own way\n\u003c/h2\u003e\u003cp\u003eAt rOpenSci you can contribute in so many ways. We have a \u003ca href=\"https://contributing.ropensci.org/\"\u003ecommunity contributing guide\u003c/a\u003e but here\u0026rsquo;s a list of some of my own contributions:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eAttend \u003ca href=\"/community/\"\u003eevents\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003eHelp to welcome and onboard new members.\u003c/li\u003e\n\u003cli\u003eAsk or answer questions on Slack, or share or discuss ideas or jobs.\u003c/li\u003e\n\u003cli\u003eImprove our documentation, e.g. fix a typo.\u003c/li\u003e\n\u003cli\u003eWrite a \u003ca href=\"/blog/\"\u003eblog\u003c/a\u003e post.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/multilingual-publishing/\"\u003eTranslate\u003c/a\u003e or review some work in your native language.\u003c/li\u003e\n\u003cli\u003ePilot a new process.\u003c/li\u003e\n\u003cli\u003eAuthor, review, or edit an R package.\u003c/li\u003e\n\u003cli\u003eLead a workshop.\u003c/li\u003e\n\u003cli\u003eBuild a tool to enhance some process.\u003c/li\u003e\n\u003cli\u003eGive and get support, e.g. mentor, review grant applications or talks, advice or recommendations for jobs, help unavailable or overwhelmed people.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAs you can see, most of my contributions did not involve any code, and only a few required an invitation. Some of them are the kind of thing you could add to your CV, and the most important ones only belong in your heart.\u003c/p\u003e\n\u003ch2 id=\"attract-great-people\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#attract-great-people\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nAttract great people\n\u003c/h2\u003e\u003cp\u003eGreat communities are made of great people, and you can play an active role in growing it in the direction you want. If you know someone that would fit in and enjoy the rOpenSci community, you can try to \u003ca href=\"https://contributing.ropensci.org/\"\u003efind a way to bring them in\u003c/a\u003e. For example, I\u0026rsquo;ve encouraged and helped people to submit and review packages. Also as an editor I have the occasional privilege to nominate other editors. Using this super-power I\u0026rsquo;ve attracted two \u003ca href=\"/software-review/\"\u003eeditors\u003c/a\u003e and I now get to enjoy interacting with them quite regularly.\u003c/p\u003e\n\u003ch2 id=\"keep-the-human-in-your-human-connections\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#keep-the-human-in-your-human-connections\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nKeep the human in your human connections\n\u003c/h2\u003e\u003cp\u003eAI is changing the way we contribute to open source software. But we don\u0026rsquo;t know much about its effect on the open communities around that software. Earlier this year rOpenSci published a \u003ca href=\"/blog/2026/02/26/ropensci-ai-policy/\"\u003epreliminary set of policies\u003c/a\u003e, and you may want to watch rOpenSci\u0026rsquo;s \u003ca href=\"/news/\"\u003enewsletter\u003c/a\u003e and this \u003ca href=\"https://openscapes.org/events/2026-10-01-community-call-open-communities-ai/\"\u003eOpenscapes community call\u003c/a\u003e:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003e\u003cstrong\u003eOpen Communities in the Age of AI\u003c/strong\u003e\u003cbr\u003e\n{Open communities} help us connect on a human level around science and data and the things that we are passionate about. They change careers, they change lives. (\u0026hellip;) But now, people are not necessarily finding their communities and getting the benefit of those communities in the way that they used to, because they\u0026rsquo;re more easily able to get help and answers by using AI. (\u0026hellip;) These connections and communities are more important than ever, as we need to find ways to support each other and ourselves as AI rapidly changes the landscape right under our feet.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp\u003ePersonally, over the past year I\u0026rsquo;ve used AI heavily and learned several lessons. The most relevant here is that I don\u0026rsquo;t want AI to impersonate me or the other person in a \u003ca href=\"https://contributing.ropensci.org/motivations.html#connect\"\u003ehuman-to-human connection\u003c/a\u003e. The \u003ca href=\"https://contributing.ropensci.org/intro.html#humans\"\u003ehumans of rOpenSci\u003c/a\u003e are real and wonderful people. Here are some that I\u0026rsquo;ve recently met in person:\u003c/p\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdiv class=\"col-md-6\"\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/29/celebrating-ropensci/2024_boston_zci_yani-noam-mauro.JPG\"\n\t\t\talt=\"Noam Ross, Yanina Bellini Saibene, and Mauro Lepore at the 2024 CZI meeting in Boston, USA\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003e\u003ca href='https://www.linkedin.com/in/noamross/'\u003eNoam Ross\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/yabellini/'\u003eYanina Bellini Saibene\u003c/a\u003e and \u003ca href='https://www.linkedin.com/in/mauro-lepore/'\u003eme\u003c/a\u003e at the 2024 \u003ca href='https://chanzuckerberg.com/'\u003eCZI\u003c/a\u003e meeting in Boston, USA.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003c/div\u003e\n\u003cdiv class=\"col-md-6\"\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/29/celebrating-ropensci/2024_seattle_posit-conf_monica-stefanie-sean-julia-mauro-kelly.png\"\n\t\t\talt=\"Monica Gerber, Stefanie Butland, Sean Kross, Julia Stewart Lowndes, Kelly O\u0026#39;Briant, and Mauro Lepore at the 2024 Posit conference in Seattle, USA\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003e\u003ca href='https://www.linkedin.com/in/monica-gerber/'\u003eMonica Gerber\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/stefaniebutland/'\u003eStefanie Butland\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/seankross/'\u003eSean Kross\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/julia-stewart-lowndes/'\u003eJulia Stewart Lowndes\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/kellyobriant/'\u003eKelly O\u0026rsquo;Briant\u003c/a\u003e and me at the 2024 Posit conference in Seattle, USA.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdiv class=\"col-md-6\"\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/29/celebrating-ropensci/2025_atlanta_posit-conf_luis-diana-mauro.jpg\"\n\t\t\talt=\"Luis D. Verde Arregoitia, Diana Garcia Cortes, and Mauro Lepore at the Georgia Aquarium after the 2025 Posit conference in Atlanta, USA\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003e\u003ca href='https://www.linkedin.com/in/luis-d-verde-arregoitia-a20339209/'\u003eLuis D. Verde Arregoitia\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/ddiannae/'\u003eDiana Garcia Cortes\u003c/a\u003e and me at the Georgia Aquarium after the 2025 Posit conference in Atlanta, USA.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003c/div\u003e\n\u003cdiv class=\"col-md-6\"\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/29/celebrating-ropensci/2025_san-jose_costa-rica_ronny.jpg\"\n\t\t\talt=\"Ronny A. Hernández Mora and Mauro Lepore at Ronny\u0026#39;s family gathering near San José, Costa Rica in 2025\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003e\u003ca href='https://www.linkedin.com/in/ronny-hernandez-mora/'\u003eRonny A. Hernández Mora\u003c/a\u003e and me at Ronny\u0026rsquo;s family gathering near San José, Costa Rica in 2025.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdiv class=\"col-md-6\"\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/29/celebrating-ropensci/2025_sao-pablo_brasil_bea-mauro.jpg\"\n\t\t\talt=\"Beatriz Milz and Mauro Lepore after coffee and pastries in São Paulo, Brazil in 2025\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003e\u003ca href='https://www.linkedin.com/in/beatrizmilz/'\u003eBeatriz Milz\u003c/a\u003e and me after coffee and pastries in São Paulo, Brazil in 2025.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eThanks for joining me in celebrating rOpenSci. And if, like me, you \u003ca href=\"https://contributing.ropensci.org/intro.html#community\"\u003eself-identify with our community\u003c/a\u003e, then happy birthday to you!\u003c/p\u003e\n\u003cdiv class=\"footnotes\" role=\"doc-endnotes\"\u003e\n\u003chr\u003e\n\u003col\u003e\n\u003cli id=\"fn:1\"\u003e\n\u003cp\u003eTwo books I like are \u003ca href=\"https://openlibrary.org/books/OL31981288M/How_to_Win_Friends_and_Influence_People\"\u003eHow to Win Friends and Influence People\u003c/a\u003e and \u003ca href=\"https://openlibrary.org/works/OL282391W/Crucial_Conversations\"\u003eCrucial Conversations (Third Edition): Tools for Talking When Stakes Are High\u003c/a\u003e.\u0026#160;\u003ca href=\"#fnref:1\" class=\"footnote-backref\" role=\"doc-backlink\"\u003e\u0026#x21a9;\u0026#xfe0e;\u003c/a\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003c/div\u003e\n","url":"https://ropensci.org/blog/2026/09/29/celebrating-ropensci/","date_published":"2026-09-29T00:00:00+00:00"},{"id":"https://ropensci.org/blog/2026/09/28/news-september-2026/","title":"rOpenSci News Digest, September 2026","content_text":"\u003c!-- Before sending DELETE THE INDEX_CACHE and re-knit! --\u003e\n\u003cp\u003eDear rOpenSci friends, it\u0026rsquo;s time for our monthly news roundup! \u003c!-- blabla --\u003e You can read this post \u003ca href=\"/blog/2026/09/28/news-september-2026\"\u003eon our blog\u003c/a\u003e. Now let\u0026rsquo;s dive into the activity at and around rOpenSci!\u003c/p\u003e\n\u003ch2 id=\"ropensci-hq\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#ropensci-hq\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nrOpenSci HQ\n\u003c/h2\u003e\u003ch3 id=\"yani-and-mark-at-open-communities-in-the-age-of-ai\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#yani-and-mark-at-open-communities-in-the-age-of-ai\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nYani and Mark at \u0026ldquo;Open Communities in the age of AI\u0026rdquo;\n\u003c/h3\u003e\u003cp\u003erOpenSci community manager \u003ca href=\"/author/yanina-bellini-saibene\"\u003eYani\u003c/a\u003e and software-review lead \u003ca href=\"/author/mark-padgham\"\u003eMark\u003c/a\u003e will participate in the upcoming Openscapes community call on October 1st (this Thursday!) at 9:30AM PT (16:30 UTC) entitled \u003cem\u003e\u0026ldquo;Open Communities in the Age of AI\u0026rdquo;\u003c/em\u003e, together with Mara Averick, Senior Developer Advocate at Quansight and Hadley Wickham, Chief Scientist at Posit.\u003c/p\u003e\n\u003cp\u003e\u003ca href=\"https://openscapes.org/events/2026-10-01-community-call-open-communities-ai/\"\u003eEvent page\u003c/a\u003e, including link for free registration.\u003c/p\u003e\n\u003ch3 id=\"champions-program-update\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#champions-program-update\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nChampions Program update\n\u003c/h3\u003e\u003cp\u003eOur current 2026\u0026ndash;2027 cohort has completed the training phase and is now focused on developing their individual projects with the support of their mentors, as well as on their outreach activities.\u003c/p\u003e\n\u003cp\u003eMeanwhile, the 2025\u0026ndash;2026 cohort will wrap up their journey with a closing community call, \u003ca href=\"/commcalls/mas-alla-del-codigo-2026/\"\u003e\u003cstrong\u003eMás Allá del Código: muestra abierta de los proyectos de nuestros campeon(a|e)s (Beyond the Code: an open showcase of our Champions\u0026rsquo; Projects)\u003c/strong\u003e\u003c/a\u003e. At the call, the Champions will present their final projects, from creating, improving, and reviewing R packages to the outreach work that brought those projects to their communities. They\u0026rsquo;ll also share what their projects led to, including scholarships, new collaborations, and professional growth. The event is in Spanish. The call will take place on \u003ca href=\"/commcalls/mas-alla-del-codigo-2026/\"\u003eMonday, October 12 at 15:00 UTC\u003c/a\u003e. Come get inspired, ask your questions live, and help us celebrate our growing open-source community!\u003c/p\u003e\n\u003ch2 id=\"were-still-celebrating-our-15th-anniversary-tada\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#were-still-celebrating-our-15th-anniversary-tada\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nWe\u0026rsquo;re still celebrating our 15th anniversary! \u0026#x1f389;\n\u003c/h2\u003e\u003cp\u003eIn July, we started to share stories from members of our community about their experiences with rOpenSci. Our second story features \u003ca href=\"/author/yi-chin-sunny-tseng/\"\u003eYi-Chin Sunny Tseng\u003c/a\u003e and her connection with rOpenSci. Read it on our blog: \u003ca href=\"/blog/2026/09/15/birthday-post-sunny/\"\u003eHappy Birthday rOpenSci \u0026mdash; My Journey from First-Time Developer to Current Opportunities\u003c/a\u003e Stay tuned for more stories from our community as we continue celebrating 15 years of rOpenSci!\u003c/p\u003e\n\u003ch2 id=\"ropensci-at-latinr-2026-in-medellín-colombia-see-you-there\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#ropensci-at-latinr-2026-in-medell%c3%adn-colombia-see-you-there\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nrOpenSci at LatinR 2026 in Medellín, Colombia. See you there!\n\u003c/h2\u003e\u003cp\u003e\u003ca href=\"https://www.eventbrite.com.ar/e/1998690018649\"\u003eRegistration for LatinR 2026 (November 11\u0026ndash;13, Universidad de Antioquia, Medellín) is now open\u003c/a\u003e, and rOpenSci will have a strong presence.\u003c/p\u003e\n\u003cp\u003e\u003ca href=\"/author/jeroen-ooms\"\u003eJeroen\u003c/a\u003e will give a talk on R-Universe. \u003ca href=\"/author/yanina-bellini-saibene\"\u003eYani\u003c/a\u003e will lead a workshop on R package development and give a talk on the Champions Program\u0026rsquo;s open curriculum. \u003ca href=\"/author/nic-crane\"\u003eNic Crane\u003c/a\u003e is one of the conference\u0026rsquo;s keynote speakers. \u003ca href=\"/author/evelia-lorena-coss-navarrete/\"\u003eEvelia Lorena Coss Navarrete\u003c/a\u003e, one of our Champions, will talk about the package she developed during the program. Several other rOpenSci folks \u0026mdash; \u003ca href=\"/author/evelia-lorena-coss-navarrete/\"\u003eNatalia Da Silva\u003c/a\u003e, \u003ca href=\"/author/luis-d.-verde-arregoitia/\"\u003eLuis Verde\u003c/a\u003e, and \u003ca href=\"/author/francisco-cardozo/\"\u003eFrancisco Cardozo\u003c/a\u003e, among others \u0026mdash; will also be there. Jeroen, Francisco, and Yani will take part in the hackathon during the conference.\u003c/p\u003e\n\u003cp\u003eJoin us in Medellín!\u003c/p\u003e\n\u003ch3 id=\"coworking\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#coworking\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCoworking\n\u003c/h3\u003e\u003cp\u003eRead \u003ca href=\"/blog/2023/06/21/coworking/\"\u003eall about coworking\u003c/a\u003e!\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eTuesday October 6th, 09:00 Americas Pacific (16:00 UTC) \u003ca href=\"/events/coworking-2026-10/\"\u003e\u0026ldquo;Writing Tests \u0026amp; Testing in R\u0026rdquo;\u003c/a\u003e, with \u003ca href=\"/author/yanina-bellini-saibene\"\u003eYanina Bellini Saibene\u003c/a\u003e and co-host \u003ca href=\"/author/olivier-leroy/\"\u003eOlivier Leroy\u003c/a\u003e.\n\u003cul\u003e\n\u003cli\u003eExplore how to write tests for R and add some tests to your work or packages\u003c/li\u003e\n\u003cli\u003eMeet co-host, Olivier Leroy, and chat about testing\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003eTuesday November 3rd, 09:00 Australia Western (01:00 UTC) \u003ca href=\"/events/coworking-2026-11/\"\u003e\u0026ldquo;Climate Science in R\u0026rdquo;\u003c/a\u003e, with \u003ca href=\"/author/steffi-lazerte\"\u003eSteffi LaZerte\u003c/a\u003e and co-host \u003ca href=\"/author/elio-campitelli/\"\u003eElio Campitelli\u003c/a\u003e.\n\u003cul\u003e\n\u003cli\u003eExplore how R is used to study the climate\u003c/li\u003e\n\u003cli\u003eMeet co-host, Elio Campitelli, and discuss Climate Science in R\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003eTuesday December 8th\u003csup\u003e*\u003c/sup\u003e, 14:00 Europe Central (12:00 UTC) \u003ca href=\"/events/coworking-2026-12/\"\u003e\u0026ldquo;Code Linting in R\u0026rdquo;\u003c/a\u003e, with \u003ca href=\"/author/steffi-lazerte\"\u003eSteffi LaZerte\u003c/a\u003e and co-host \u003ca href=\"/author/etienne-bacher/\"\u003eEtienne Bacher\u003c/a\u003e.\n\u003cul\u003e\n\u003cli\u003eRead up on Code Linting and apply some linters to your R code\u003c/li\u003e\n\u003cli\u003eMeet co-host, Etienne Bacher, and discuss code linting in general, or flir and Jarl in particular\u003cbr\u003e\n* Note that December coworking is a week later than usual\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAnd remember, you can always cowork independently on work related to R, work on packages that tend to be neglected, or work on what ever you need to get done!\u003c/p\u003e\n\u003ch2 id=\"software-package\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#software-package\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nSoftware \u0026#x1f4e6;\n\u003c/h2\u003e\u003cp\u003eThe following two packages recently became a part of our software suite:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://docs.ropensci.org/ciecl\"\u003eciecl\u003c/a\u003e, developed by Rodolfo Tasso Suazo: Tools for working with the International Classification of Diseases (ICD-10 Chile official MINSAL/DEIS v2018). Includes optimized SQL search with SQLite, fuzzy matching of medical terms (Jaro-Winkler), Charlson and Elixhauser comorbidity calculation, WHO ICD-11 API integration, and hierarchical code validation. Data from Centro FIC Chile DEIS \u003ca href=\"https://deis.minsal.cl/centrofic/\"\u003ehttps://deis.minsal.cl/centrofic/\u003c/a\u003e. It has been \u003ca href=\"https://github.com/ropensci/software-review/issues/765\"\u003ereviewed\u003c/a\u003e by Maëlle Salmon and Yanina Bellini.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://docs.ropensci.org/brapiR2\"\u003ebrapiR2\u003c/a\u003e, developed by Joash Joshua Ayo: Provides pipe-friendly, stateless read access to the Breeding API (BrAPI) v2.1 specification, an open community standard for plant breeding data interchange maintained by the BrAPI project \u003ca href=\"https://brapi.org\"\u003ehttps://brapi.org\u003c/a\u003e. Wraps 32 of the 37 BrAPI v2.1 entities across all four modules, Core, Germplasm, Phenotyping, and Genotyping, covering 49 of the specifications 138 retrieval (GET and search) endpoints and returning tidy tibbles ready for analysis. Write and update endpoints are out of scope by design. Features include automatic pagination, async search handling, response caching, parallel batch fetching, and convenience functions for genomic selection workflows (e.g. dosage matrix extraction). Designed for plant breeders and bioinformaticians who need programmatic access to plant breeding databases that implement the BrAPI\u0026rsquo; v2 specification. It has been \u003ca href=\"https://github.com/ropensci/software-review/issues/792\"\u003ereviewed\u003c/a\u003e by David Waring and Jenna Hershberger.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eDiscover \u003ca href=\"/packages\"\u003emore packages\u003c/a\u003e, read more about \u003ca href=\"/software-review\"\u003eSoftware Peer Review\u003c/a\u003e.\u003c/p\u003e\n\u003ch3 id=\"new-versions\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#new-versions\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nNew versions\n\u003c/h3\u003e\u003cp\u003eThe following twenty-two packages have had an update since the last newsletter: \u003ca href=\"https://docs.ropensci.org/visdat\" title=\"Preliminary Visualisation of Data\"\u003evisdat\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/visdat/releases/tag/v0.6.1\"\u003e\u003ccode\u003ev0.6.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/nycOpenData\" title=\"A Lightweight Interface to NYC Open Data APIs\"\u003enycOpenData\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/nycOpenData/releases/tag/v0.2.3\"\u003e\u003ccode\u003ev0.2.3\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/ruODK\" title=\"An R Client for the ODK Central API\"\u003eruODK\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/ruODK/releases/tag/v1.6.0\"\u003e\u003ccode\u003ev1.6.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/stats19\" title=\"Work with Open Road Traffic Casualty Data from Great Britain\"\u003estats19\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/stats19/releases/tag/v4.1.0\"\u003e\u003ccode\u003ev4.1.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/npi\" title=\"Access the U.S. National Provider Identifier Registry API\"\u003enpi\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/npi/releases/tag/v0.3.1\"\u003e\u003ccode\u003ev0.3.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/promoutils\" title=\"Utilities for Promoting rOpenSci\"\u003epromoutils\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci-org/promoutils/releases/tag/v0.7.0\"\u003e\u003ccode\u003ev0.7.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/brapiR2\" title=\"A Tidyverse-Native Client for the BrAPI v2 (Breeding API) Specification\"\u003ebrapiR2\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/brapiR2/releases/tag/v0.2.0\"\u003e\u003ccode\u003ev0.2.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/ciecl\" title=\"International Classification of Diseases ICD-10/ICD-11 for Chile\"\u003eciecl\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/ciecl/releases/tag/v1.0.0\"\u003e\u003ccode\u003ev1.0.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/bibtex\" title=\"Bibtex Parser\"\u003ebibtex\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/bibtex/releases/tag/v0.5.3\"\u003e\u003ccode\u003ev0.5.3\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/ckanr\" title=\"Client for the Comprehensive Knowledge Archive Network (CKAN) API\"\u003eckanr\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/ckanr/releases/tag/v0.9.0\"\u003e\u003ccode\u003ev0.9.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/osmapiR\" title=\"OpenStreetMap API\"\u003eosmapiR\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/osmapiR/releases/tag/v0.2.6\"\u003e\u003ccode\u003ev0.2.6\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/distionary\" title=\"Create and Evaluate Probability Distributions\"\u003edistionary\u003c/a\u003e (\u003ca href=\"https://github.com/probaverse/distionary/releases/tag/v0.2.0\"\u003e\u003ccode\u003ev0.2.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/GLMMcosinor\" title=\"Fit a Cosinor Model Using a Generalized Mixed Modeling Framework\"\u003eGLMMcosinor\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/GLMMcosinor/releases/tag/v0.2.2\"\u003e\u003ccode\u003ev0.2.2\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/reviser\" title=\"Analyzing Revisions in Real-Time Time Series Vintages\"\u003ereviser\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/reviser/releases/tag/v0.3.1\"\u003e\u003ccode\u003ev0.3.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/autotest\" title=\"Automatic Package Testing\"\u003eautotest\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci-review-tools/autotest/releases/tag/v0.2\"\u003e\u003ccode\u003ev0.2\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/occCite\" title=\"Querying and Managing Large Biodiversity Occurrence Datasets\"\u003eoccCite\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/occCite/releases/tag/v0.6.3\"\u003e\u003ccode\u003ev0.6.3\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/readODS\" title=\"Read and Write ODS Files\"\u003ereadODS\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/readODS/releases/tag/v2.3.6\"\u003e\u003ccode\u003ev2.3.6\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/osmdata\" title=\"Import OpenStreetMap Data as Simple Features or Spatial Objects\"\u003eosmdata\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/osmdata/releases/tag/v0.4.1\"\u003e\u003ccode\u003ev0.4.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/goodpractice\" title=\"Advice on R Package Building\"\u003egoodpractice\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci-review-tools/goodpractice/releases/tag/v1.2.0\"\u003e\u003ccode\u003ev1.2.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/galamm\" title=\"Generalized Additive Latent and Mixed Models\"\u003egalamm\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/galamm/releases/tag/v0.4.1\"\u003e\u003ccode\u003ev0.4.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/RAMEN\" title=\"Regional Association of Methylome variability with the Exposome and geNome\"\u003eRAMEN\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/RAMEN/releases/tag/v2.1.2\"\u003e\u003ccode\u003ev2.1.2\u003c/code\u003e\u003c/a\u003e), and \u003ca href=\"https://docs.ropensci.org/EDIutils\" title=\"An API Client for the Environmental Data Initiative Repository\"\u003eEDIutils\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/EDIutils/releases/tag/v3.0.1\"\u003e\u003ccode\u003ev3.0.1\u003c/code\u003e\u003c/a\u003e).\u003c/p\u003e\n\u003ch2 id=\"software-peer-review\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#software-peer-review\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nSoftware Peer Review\n\u003c/h2\u003e\u003cp\u003eThere are seventeen recently closed and active submissions and 4 submissions on hold. Issues are at different stages:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eTwo at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%226/approved%22\"\u003e\u0026lsquo;6/approved\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/792\"\u003ebrapiR2\u003c/a\u003e, A Tidyverse-Native Client for the BrAPI v2 (Breeding API) Specification. Submitted by \u003ca href=\"https://orcid.org/0009-0007-1642-0172\"\u003eJoash Joshua Ayo\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/765\"\u003eciecl\u003c/a\u003e, International Classification of Diseases ICD-10/ICD-11 for Chile. Submitted by \u003ca href=\"https://github.com/Rodotasso\"\u003eRodolfo Tasso\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eThree at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%225/awaiting-reviewer(s)-response%22\"\u003e\u0026lsquo;5/awaiting-reviewer(s)-response\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/787\"\u003eibger\u003c/a\u003e, Access the IBGE Aggregate Data API from R. Submitted by \u003ca href=\"https://castlab.org\"\u003eAndre Leite Wanderley\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/744\"\u003eRAQSAPI\u003c/a\u003e, A Simple Interface to the US EPA Air Quality System Data Mart API. Submitted by \u003ca href=\"https://github.com/mccroweyclinton-EPA\"\u003emccroweyclinton-EPA\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/717\"\u003ecoevolve\u003c/a\u003e, Fit Bayesian Generalized Dynamic Phylogenetic Models using Stan. Submitted by \u003ca href=\"https://scottclaessens.github.io/\"\u003eScott Claessens\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eOne at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%224/review(s)-in-awaiting-changes%22\"\u003e\u0026lsquo;4/review(s)-in-awaiting-changes\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/718\"\u003ercrisp\u003c/a\u003e, Automate the Delineation of Urban River Spaces. Submitted by \u003ca href=\"https://github.com/cforgaci\"\u003eClaudiu Forgaci\u003c/a\u003e. (Stats).\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eFour at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%223/reviewer(s)-assigned%22\"\u003e\u0026lsquo;3/reviewer(s)-assigned\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/799\"\u003ecamtrapReport\u003c/a\u003e, Camera-Trap Report Generator. Submitted by \u003ca href=\"https://www.wur.nl/en/persons/e-elham-ebrahimi\"\u003eElham Ebrahimi\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/785\"\u003enert\u003c/a\u003e, Curated Access to TERN Environmental Raster Data. Submitted by \u003ca href=\"https://scholar.google.com.au/citations?user=zG1uKrcAAAAJ\u0026amp;hl=en\"\u003eMax Moldovan\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/769\"\u003erfastlowess\u003c/a\u003e, High-Performance LOWESS Smoothing for R. Submitted by \u003ca href=\"https://github.com/thisisamirv\"\u003eAmir Valizadeh\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/799\"\u003ecamtrapReport\u003c/a\u003e, Camera-Trap Report Generator. Submitted by \u003ca href=\"https://www.wur.nl/en/persons/e-elham-ebrahimi\"\u003eElham Ebrahimi\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTwo at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%222/seeking-reviewer(s)%22\"\u003e\u0026lsquo;2/seeking-reviewer(s)\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/775\"\u003egrumpy\u003c/a\u003e, Read NumPy .npy and .npz Files. Submitted by \u003ca href=\"https://hugogruson.fr/\"\u003eHugo Gruson\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/774\"\u003etezr\u003c/a\u003e, Access Thesis Metadata from Turkiye\u0026rsquo;s National Thesis Center. Submitted by \u003ca href=\"https://emraher.com\"\u003eEmrah Er\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eFive at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%221/editor-checks%22\"\u003e\u0026lsquo;1/editor-checks\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/811\"\u003eocean3d\u003c/a\u003e, Three-Dimensional Marine Spatial Analysis. Submitted by \u003ca href=\"https://jmatsushiba.com\"\u003eJay Matsushiba\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/808\"\u003ecorila\u003c/a\u003e, Sparse modelling with grouped and correlated features allowing for privileged information. Submitted by \u003ca href=\"https://rauschenberger.github.io\"\u003eArmin Rauschenberger\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/805\"\u003etarpolyglot\u003c/a\u003e, Run Python, Julia, Rust, and C++ Inside targets Pipeline Steps. Submitted by \u003ca href=\"https://github.com/Pierre9344\"\u003ePierre9344\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/777\"\u003eOptSurvCutR\u003c/a\u003e, Optimal Survival Cut-Point Discovery for Time-to-Event Analysis with OptSurvCutR. Submitted by \u003ca href=\"https://github.com/paytonyau\"\u003ePayton Yau\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/766\"\u003eHydraR\u003c/a\u003e, Stateful Agentic Orchestration for Scientific Reproducibility. Submitted by \u003ca href=\"https://www.mq.edu.au/research/research-centres-groups-and-facilities/facilities/australian-proteome-analysis-facility\"\u003eIgnatius Pang\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eFind out more about \u003ca href=\"/software-review\"\u003eSoftware Peer Review\u003c/a\u003e and how to get involved.\u003c/p\u003e\n\u003ch2 id=\"on-the-blog\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#on-the-blog\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nOn the blog\n\u003c/h2\u003e\u003c!-- Do not forget to rebase your branch! --\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"/blog/2026/09/15/birthday-post-sunny\"\u003eHappy Birthday rOpenSci \u0026mdash; My Journey from First-Time Developer to Current Opportunities\u003c/a\u003e by Yi-Chin Sunny Tseng. Yi-Chin Sunny Tseng shares how the rOpenSci Champions Program helped her grow from a first-time R package developer into an open science contributor, creating tools for biodiversity research and discovering new opportunities along the way.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2 id=\"calls-for-contributions\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#calls-for-contributions\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCalls for contributions\n\u003c/h2\u003e\u003ch3 id=\"calls-for-maintainers\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#calls-for-maintainers\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCalls for maintainers\n\u003c/h3\u003e\u003cp\u003eIf you\u0026rsquo;re interested in maintaining any of the R packages below, you might enjoy reading our blog post \u003ca href=\"/blog/2023/02/07/what-does-it-mean-to-maintain-a-package/\"\u003eWhat Does It Mean to Maintain a Package?\u003c/a\u003e.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://docs.ropensci.org/charlatan\"\u003echarlatan\u003c/a\u003e, create fake data in R. \u003ca href=\"https://github.com/ropensci/charlatan/issues/150\"\u003eIssue for volunteering\u003c/a\u003e.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3 id=\"calls-for-contributions-1\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#calls-for-contributions-1\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCalls for contributions\n\u003c/h3\u003e\u003cp\u003eRefer to our \u003ca href=\"/help-wanted/\"\u003ehelp wanted page\u003c/a\u003e \u0026ndash; before opening a PR, we recommend asking in the issue whether help is still needed.\u003c/p\u003e\n\u003ch2 id=\"package-development-corner\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#package-development-corner\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nPackage development corner\n\u003c/h2\u003e\u003cp\u003eSome useful information for R package developers. \u0026#x1f440;\u003c/p\u003e\n\u003ch3 id=\"covr2gh-coverage-summary-as-github-comment\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#covr2gh-coverage-summary-as-github-comment\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\n{covr2gh}: Coverage summary as GitHub comment\n\u003c/h3\u003e\u003cp\u003eThe covr2gh package by Dragoș Moldovan-Grünfeld provides an automated way to summarise the impact of a pull request (PR) on test coverage directly within GitHub. See it in action in a PR in the \u003ca href=\"https://github.com/GSK-Biostatistics/tfrmt/pull/844#issuecomment-5424645453\"\u003etfrmt R package\u003c/a\u003e.\u003c/p\u003e\n\u003ch3 id=\"deprecation-messages-for-package-data\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#deprecation-messages-for-package-data\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nDeprecation messages for package data\n\u003c/h3\u003e\u003cp\u003eHugo Gruson wrote an \u003ca href=\"https://hugogruson.fr/posts/deprecation-pkg-data/\"\u003eexhaustive post\u003c/a\u003e about the deprecation of \u003cem\u003edata\u003c/em\u003e in an R package. The post features the \u003ca href=\"https://rdrr.io/r/base/delayedAssign.html\"\u003e\u003ccode\u003edelayedAssign()\u003c/code\u003e\u003c/a\u003e function.\u003c/p\u003e\n\u003ch3 id=\"a-refactoring-story-featuring-people\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#a-refactoring-story-featuring-people\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nA refactoring story featuring people\n\u003c/h3\u003e\u003cp\u003eAthanasia Mo Mowinckel published \u003ca href=\"https://drmowinckels.io/blog/2026/atlases-as-functions/\"\u003e\u0026ldquo;Why ggseg Atlases Became Function Calls\u0026rdquo;\u003c/a\u003e, where she explains how she made data into objects into a package in order to allow re-exporting them. She furthermore tells how she got to that conclusion by trying out different solutions and discussing with other package developers in the rOpenSci Slack workspace.\u003c/p\u003e\n\u003ch3 id=\"usethis-322\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#usethis-322\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nusethis 3.2.2\n\u003c/h3\u003e\u003cp\u003eThe usethis package was updated on CRAN. The \u003ca href=\"https://usethis.r-lib.org/news/index.html#usethis-322\"\u003echangelog\u003c/a\u003e features many quality of life improvements around Git and GitHub, and a new \u003ccode\u003euse_readme_qmd()\u003c/code\u003e function for drafting a README in the Quarto format.\u003c/p\u003e\n\u003ch2 id=\"last-words\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#last-words\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nLast words\n\u003c/h2\u003e\u003cp\u003eThanks for reading! If you want to get involved with rOpenSci, check out our \u003ca href=\"https://contributing.ropensci.org\"\u003eContributing Guide\u003c/a\u003e. This guide will help direct you to the right place, whether you want to make code contributions, non-code contributions, or contribute in other ways such as through sharing use cases. You can also support our work through \u003ca href=\"/donate\"\u003edonations\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eIf you haven\u0026rsquo;t subscribed to our newsletter yet, you can \u003ca href=\"/news/\"\u003edo so though our signup form\u003c/a\u003e. Until it\u0026rsquo;s time for our next newsletter, you can keep in touch with us through our \u003ca href=\"/\"\u003ewebsite\u003c/a\u003e, \u003ca href=\"https://hachyderm.io/@rOpenSci\"\u003eMastodon\u003c/a\u003e, or \u003ca href=\"https://www.linkedin.com/company/ropensci/\"\u003eLinkedIn\u003c/a\u003e. See you soon!\u003c/p\u003e\n","url":"https://ropensci.org/blog/2026/09/28/news-september-2026/","date_published":"2026-09-28T00:00:00+00:00"},{"id":"https://ropensci.org/blog/2026/09/15/birthday-post-sunny/","title":"Happy Birthday rOpenSci — My Journey from First-Time Developer to Current Opportunities","content_text":"\u003ch2 id=\"what-people-would-fund-me-and-mentor-me-building-my-own-r-package\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#what-people-would-fund-me-and-mentor-me-building-my-own-r-package\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nWhat? People would fund me and mentor me building my own R package?\n\u003c/h2\u003e\u003cp\u003eMy first time hearing about rOpenSci was, interestingly, at a bird conference. At an ornithological conference in 2023, I was chatting with my bird friend / colleague \u003ca href=\"/author/steffi-lazerte/\"\u003eSteffi LaZerte\u003c/a\u003e, who highly recommended that I apply for the rOpenSci Champions program given my strong interest in developing R packages.\nI mentioned my concerns and hesitation about whether I am “qualified” to make an R package, which at that time sounded like what professional developers do. She simply asked, “Can you write functions in R?” “Yes, I can.” “Then you are good to go! R packages are simply putting functions together in an organized way!”\nSo here we go, I took the motivation and sent out my application for the 2024 rOpenSci cohort. A few months later, I was selected as one of the 20 participants around the world;\nI remember the strong excitement when I received the confirmation letter from rOpenSci.\nI was probably even more excited than when I got my PhD admission!\u003c/p\u003e\n\u003ch2 id=\"bbstaiwan-r-package--a-combination-of-my-dreams\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#bbstaiwan-r-package--a-combination-of-my-dreams\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nbbsTaiwan R package – a combination of my dreams\n\u003c/h2\u003e\u003cp\u003eI have been an avid R user for a long time, and I am particularly fascinated by the open science nature that comes with it.\nMy proposed package, “\u003ca href=\"https://sunnytseng.github.io/bbsTaiwan/\"\u003ebbsTaiwan\u003c/a\u003e”, aims to solve a common issue with an open-source dataset, the Breeding Bird Survey (BBS) data of Taiwan.\nWhile the BBS dataset is publicly available online and stored in \u003ca href=\"https://www.gbif.org/\"\u003eGlobal Biodiversity Information Facility\u003c/a\u003e, it is structured in a specific machine-readable format that requires a certain amount of data wrangling to make it usable for downstream modeling and ecological inference.\n\u003ca href=\"https://sunnytseng.github.io/bbsTaiwan/\"\u003ebbsTaiwan\u003c/a\u003e is a data package as well as a wrangling toolbox, and it can be particularly useful for undergraduate and graduate students, as well as researchers who need BBS data for their dissertations.\nMost importantly, I see it as a crucial way to contribute my skills back to my beloved homeland - Taiwan. I want to use this package to show my care and love for the land.\u003c/p\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/15/birthday-post-sunny/presentation.png\"\n\t\t\talt=\"Promotional banner for bbsTaiwan, the R package that I developed for the Champions Program for retrieving and analyzing Taiwan Breeding Bird Survey data. Features the hexagonal bbsTaiwan logo with an illustrated bird beside a silhouette of Taiwan on a background of numbers, alongside a photo of a small bird perched on a person wrist with a tracking tag, the rOpenSci logo, and a grid of illustrated icons depicting scientists and researchers of various specialties.\"\u003e\n\u003c/figure\u003e\n\n\u003ch2 id=\"the-mentor-and-the-learning\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#the-mentor-and-the-learning\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nThe mentor and the learning\n\u003c/h2\u003e\u003cp\u003eI was very lucky to have \u003ca href=\"/author/eunseop-kim/\"\u003eEunseop Kim\u003c/a\u003e as my mentor during the Champions program.\nHe was extremely patient, supportive, and understanding.\nEunseop has a background in statistics and is very fluent in package development. He provided me with a lot of freedom on the project and emphasized that he would be there to support and help if I had any questions along my journey.\nI sought suggestions from him frequently in terms of package design, usability, resources, and references. He not only taught me how to make R packages, but he also showed me the importance and power of being a supportive mentor.\nBeing able to study references on how other people developed their packages improved my own philosophy of making packages as well.\u003cbr\u003e\nOne rule that still sticks with me until today is “be kind.”\nBe kind to your users, be kind to your collaborators, and be kind to your colleagues.\nIf we can put extra thought and effort into thinking from other people’s perspectives (what users might like to see and what makes a package easy to use), then it will be a tool that people genuinely enjoy using.\u003c/p\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/15/birthday-post-sunny/mentor.png\"\n\t\t\talt=\"Zoom meeting with my mentor and rOpenSci Community Manager\"\u003e\n\u003c/figure\u003e\n\n\u003ch2 id=\"ropensci-program-as-a-path-to-future-opportunities\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#ropensci-program-as-a-path-to-future-opportunities\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nrOpenSci program as a path to future opportunities\n\u003c/h2\u003e\u003cp\u003eThe rOpenSci Champions program not only opened my door to R package development, but it also provided me with invaluable opportunities.\nI was selected as an “Opportunity Scholar” for posit::conf(2024), where I connected with fellow programmers and was inspired further by the possibilities of this programming language.\nAfter the Champions program, I was presenting in the rOpenSci Community Call \u0026ldquo;\u003ca href=\"/commcalls/first-time-contributor/\"\u003eFrom Novice to Contributor: Making and Supporting First-Time Contributions to FOSS\u003c/a\u003e\u0026rdquo;, where I had a chance to share my experience and contribute back to rOpenSci.\nFurthermore, I received support from \u003ca href=\"https://nserc-crsng.canada.ca/en\"\u003eNatural Sciences and Engineering Research Council of Canada\u003c/a\u003e and the \u003ca href=\"https://r-consortium.org/all-projects/callforproposals.html\"\u003eR Consortium\u003c/a\u003e to create my second R package, \u003ca href=\"https://birdnet-team.github.io/birdnetTools/\"\u003ebirdnetTools\u003c/a\u003e, in collaboration with the Cornell Lab of Ornithology.\nIt was a dream come true!!\nNone of this would have been possible if I hadn\u0026rsquo;t participated in the rOpenSci Champions program a few years ago.\nMeanwhile, my story with rOpenSci will continue.\u003c/p\u003e\n\u003cp\u003eThank you to the community at rOpenSci. Thank you for bringing excitement, fun, and care to this world.\u003c/p\u003e\n\u003cfigure\u003e\u003cimg src=\"/blog/2026/09/15/birthday-post-sunny/IMG_7550.JPG\"\n\t\t\talt=\"A workshop about bbsTaiwan in Taiwan for university students\"\u003e\n\u003c/figure\u003e\n\n","url":"https://ropensci.org/blog/2026/09/15/birthday-post-sunny/","date_published":"2026-09-15T00:00:00+00:00"},{"id":"https://ropensci.org/blog/2026/08/28/news-august-2026/","title":"rOpenSci News Digest, August 2026","content_text":"\u003c!-- Before sending DELETE THE INDEX_CACHE and re-knit! --\u003e\n\u003cp\u003eDear rOpenSci friends, it\u0026rsquo;s time for our monthly news roundup! \u003c!-- blabla --\u003e You can read this post \u003ca href=\"/blog/2026/08/28/news-august-2026\"\u003eon our blog\u003c/a\u003e. Now let\u0026rsquo;s dive into the activity at and around rOpenSci!\u003c/p\u003e\n\u003ch2 id=\"ropensci-hq\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#ropensci-hq\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nrOpenSci HQ\n\u003c/h2\u003e\u003ch3 id=\"champions-program-update\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#champions-program-update\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nChampions Program update\n\u003c/h3\u003e\u003cp\u003eOur Champions are making great progress! 🌟 They\u0026rsquo;ve now completed the training on good open source software development practices, package development, and peer review, and are moving on to explore community building and communications. Meanwhile, mentoring is underway with monthly meetings helping Champions move their projects forward. We\u0026rsquo;re already starting to see some exciting results: first versions of packages are taking shape, and some Champions will soon be sharing their work at LatinR! Stay tuned for more updates as their projects continue to grow! 🚀\u003c/p\u003e\n\u003ch3 id=\"r-universe-updates\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#r-universe-updates\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nR-Universe updates\n\u003c/h3\u003e\u003cp\u003e\u0026#x1f4aa; R-Universe has started building and checking packages for Windows ARM64. Read more in our \u003ca href=\"/blog/2026/08/06/r-universe-winarm/\"\u003etech note\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026#x1f9ec; R-Universe is now part of the infrastructure of the \u003ca href=\"https://blog.bioconductor.org/posts/2026-06-15-new-submission-process-with-Runiverse/\"\u003eBioconductor submission process\u003c/a\u003e.\u003c/p\u003e\n\u003ch2 id=\"were-still-celebrating-our-15th-anniversary-\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#were-still-celebrating-our-15th-anniversary-\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nWe\u0026rsquo;re still celebrating our 15th anniversary! 🎉\n\u003c/h2\u003e\u003cp\u003eIn July, we started to share stories from members of our community about their experiences with rOpenSci. Our first story features \u003ca href=\"/author/eunseop-kim/\"\u003eEunseop Kim\u003c/a\u003e and his connection with rOpenSci. Read it on our blog: \u003ca href=\"/blog/2026/07/14/15yo-eunseop-kim/\"\u003eFrom Peer Review to Mentorship: My rOpenSci Story\u003c/a\u003e Stay tuned for more stories from our community as we continue celebrating 15 years of rOpenSci!\u003c/p\u003e\n\u003ch3 id=\"coworking\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#coworking\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCoworking\n\u003c/h3\u003e\u003cp\u003eRead \u003ca href=\"/blog/2023/06/21/coworking/\"\u003eall about coworking\u003c/a\u003e!\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eTuesday September 1st, 14:00 Europe Central (12:00 UTC) \u003ca href=\"/events/coworking-2026-09/\"\u003e\u0026ldquo;Getting to Know SORTEE\u0026rdquo;\u003c/a\u003e, with \u003ca href=\"/author/steffi-lazerte\"\u003eSteffi LaZerte\u003c/a\u003e and co-host \u003ca href=\"/author/ed-ivimey-cook/\"\u003eEd Ivimey-Cook\u003c/a\u003e.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eVisit \u003ca href=\"https://sortee.org/\"\u003eSORTEE\u003c/a\u003e (Society for Open, Reliable, and Transparent Ecology and Evolutionary Biology).\u003c/li\u003e\n\u003cli\u003eMeet co-host, Ed Ivimey-Cook, and learn more about SORTEE and how you might get involved.\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTuesday October 6th, 09:00 Americas Pacific (16:00 UTC) \u003ca href=\"/events/\"\u003e\u0026ldquo;Writing Tests \u0026amp; Testing in R\u0026rdquo;\u003c/a\u003e, with \u003ca href=\"/author/yanina-bellini-saibene\"\u003eYanina Bellini Saibene\u003c/a\u003e and co-host Olivier Leroy.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eExplore how to write tests for R and add some tests to your work or packages\u003c/li\u003e\n\u003cli\u003eMeet co-host, Olivier Leroy, and chat about testing\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTuesday November 3rd, 09:00 Australia Western (01:00 UTC) \u003ca href=\"/events/\"\u003eTBA\u003c/a\u003e, with \u003ca href=\"/author/steffi-lazerte\"\u003eSteffi LaZerte\u003c/a\u003e and co-host TBA.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTuesday December 8th, 14:00 Europe Central (12:00 UTC) \u003ca href=\"/events/\"\u003e\u0026ldquo;Code Linting in R\u0026rdquo;\u003c/a\u003e, with \u003ca href=\"/author/steffi-lazerte\"\u003eSteffi LaZerte\u003c/a\u003e and co-host \u003ca href=\"/author/etienne-bacher/\"\u003eEtienne Bacher\u003c/a\u003e.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRead up on Code Linting and apply some linters to your R code\u003c/li\u003e\n\u003cli\u003eMeet co-host, Etienne Bacher, and discuss code linting in general, or flir and Jarl in particular * Note that December coworking is a week later than usual\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAnd remember, you can always cowork independently on work related to R, work on packages that tend to be neglected, or work on what ever you need to get done!\u003c/p\u003e\n\u003ch2 id=\"software-package\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#software-package\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nSoftware \u0026#x1f4e6;\n\u003c/h2\u003e\u003cp\u003eThe following four packages recently became a part of our software suite:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://docs.ropensci.org/lakefetch\"\u003elakefetch\u003c/a\u003e, developed by Jeremy Lynch Farrell: Calculates fetch (open water distance) and wave exposure metrics for lake sampling points. Downloads lake boundaries from OpenStreetMap, calculates directional fetch using a ray-casting approach, and optionally integrates National Hydrography Dataset (NHD) data \u003ca href=\"https://www.usgs.gov/national-hydrography\"\u003ehttps://www.usgs.gov/national-hydrography\u003c/a\u003e for hydrological context including outlet and inlet locations. Can estimate lake depth from surface area using empirical relationships, and integrate historical weather data for cumulative wave energy calculations. Includes an optional interactive shiny application for visualization. It has been \u003ca href=\"https://github.com/ropensci/software-review/issues/762\"\u003ereviewed\u003c/a\u003e by Jorrit Mesman and Kelly Hondula.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://docs.ropensci.org/galamm\"\u003egalamm\u003c/a\u003e, developed by Øystein Sørensen: Estimates generalized additive latent and mixed models using maximum marginal likelihood, as defined in Sorensen et al. (2023) \u003ca href=\"https://doi.org/10.1007/s11336-023-09910-z\"\u003ehttps://doi.org/10.1007/s11336-023-09910-z\u003c/a\u003e, which is an extension of Rabe-Hesketh and Skrondal (2004)s unifying framework for multilevel latent variable modeling \u003ca href=\"https://doi.org/10.1007/BF02295939\"\u003ehttps://doi.org/10.1007/BF02295939\u003c/a\u003e. Efficient computation is done using sparse matrix methods, Laplace approximation, and automatic differentiation. The framework includes generalized multilevel models with heteroscedastic residuals, mixed response types, factor loadings, smoothing splines, crossed random effects, and combinations thereof. Syntax for model formulation is close to lme4 (Bates et al. (2015) \u003ca href=\"https://doi.org/10.18637/jss.v067.i01\"\u003ehttps://doi.org/10.18637/jss.v067.i01\u003c/a\u003e) and PLmixed\u0026rsquo; (Rockwood and Jeon (2019) \u003ca href=\"https://doi.org/10.1080/00273171.2018.1516541\"\u003ehttps://doi.org/10.1080/00273171.2018.1516541\u003c/a\u003e). It has been \u003ca href=\"https://github.com/ropensci/software-review/issues/615\"\u003ereviewed\u003c/a\u003e by Nicholas Clark and David Lawrence Miller.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://docs.ropensci.org/EpiStrainDynamics\"\u003eEpiStrainDynamics\u003c/a\u003e, developed by Saras Windecker together with Oliver Eales, James McCaw, and Freya Shearer: EpiStrainDynamics is a statistical framework developed for inferring temporal trends of multiple pathogens from routinely collected surveillance data. It has been \u003ca href=\"https://github.com/ropensci/software-review/issues/763\"\u003ereviewed\u003c/a\u003e by Sangeeta Bhatia and Joshua Lambert.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://docs.ropensci.org/RAMEN\"\u003eRAMEN\u003c/a\u003e, developed by Erick I. Navarro-Delgado together with Keegan Korthauer and Michael S. Kobor: Using population data, RAMEN identifies which genetic (G), environmental (E), additive (G+E) or interaction (GxE) model better explains DNA methylation levels in genome-wide locations with high DNA methylation variability. It has been \u003ca href=\"https://github.com/ropensci/software-review/issues/743\"\u003ereviewed\u003c/a\u003e by Lluís Revilla Sancho and Ulduz Vafadarshamasbi.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eDiscover \u003ca href=\"/packages\"\u003emore packages\u003c/a\u003e, read more about \u003ca href=\"/software-review\"\u003eSoftware Peer Review\u003c/a\u003e.\u003c/p\u003e\n\u003ch3 id=\"new-versions\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#new-versions\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nNew versions\n\u003c/h3\u003e\u003cp\u003eThe following twenty-five packages have had an update since the last newsletter: \u003ca href=\"https://docs.ropensci.org/DataSpaceR\" title=\"Interface to the CAVD DataSpace\"\u003eDataSpaceR\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/DataSpaceR/releases/tag/v1.0.2\"\u003e\u003ccode\u003ev1.0.2\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/RAMEN\" title=\"RAMEN: Regional Association of Methylome variability with the Exposome and geNome\"\u003eRAMEN\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/RAMEN/releases/tag/v2.1.1\"\u003e\u003ccode\u003ev2.1.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/frictionless\" title=\"Read and Write Frictionless Data Packages\"\u003efrictionless\u003c/a\u003e (\u003ca href=\"https://github.com/frictionlessdata/frictionless-r/releases/tag/v1.3.0\"\u003e\u003ccode\u003ev1.3.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/cffr\" title=\"Generate Citation File Format (CFF) Metadata\"\u003ecffr\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/cffr/releases/tag/v1.4.2\"\u003e\u003ccode\u003ev1.4.2\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/nodbi\" title=\"Document NoSQL Database DBI Connector\"\u003enodbi\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/nodbi/releases/tag/v0.15.0\"\u003e\u003ccode\u003ev0.15.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/reviser\" title=\"Analyzing Revisions in Real-Time Time Series Vintages\"\u003ereviser\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/reviser/releases/tag/v0.2.0\"\u003e\u003ccode\u003ev0.2.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/writexl\" title=\"Export Data Frames to Excel xlsx Format\"\u003ewritexl\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/writexl/releases/tag/v2.0.1\"\u003e\u003ccode\u003ev2.0.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/rangr\" title=\"Mechanistic Simulation of Species Range Dynamics\"\u003erangr\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/rangr/releases/tag/v1.0.10\"\u003e\u003ccode\u003ev1.0.10\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/lightr\" title=\"Read Spectrometric Data and Metadata\"\u003elightr\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/lightr/releases/tag/v2.1.0\"\u003e\u003ccode\u003ev2.1.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/gert\" title=\"Simple Git Client for R\"\u003egert\u003c/a\u003e (\u003ca href=\"https://github.com/r-lib/gert/releases/tag/v2.4.1\"\u003e\u003ccode\u003ev2.4.1\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/c14bazAAR\" title=\"Download and Prepare C14 Dates from Different Source Databases\"\u003ec14bazAAR\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/c14bazAAR/releases/tag/5.3.0\"\u003e\u003ccode\u003e5.3.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/landscapetools\" title=\"Landscape Utility Toolbox\"\u003elandscapetools\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/landscapetools/releases/tag/v0.6.3\"\u003e\u003ccode\u003ev0.6.3\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/comtradr\" title=\"Interface with the United Nations Comtrade API\"\u003ecomtradr\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/comtradr/releases/tag/v1.0.6\"\u003e\u003ccode\u003ev1.0.6\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/lingtypology\" title=\"Linguistic Typology and Mapping\"\u003elingtypology\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/lingtypology/releases/tag/v1.1.26\"\u003e\u003ccode\u003ev1.1.26\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/textreuse\" title=\"Detect Text Reuse and Document Similarity\"\u003etextreuse\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/textreuse/releases/tag/v1.0.2\"\u003e\u003ccode\u003ev1.0.2\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/sofa\" title=\"Connector to CouchDB\"\u003esofa\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/sofa/releases/tag/v0.4.2\"\u003e\u003ccode\u003ev0.4.2\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/pkgstats\" title=\"Metrics of R Packages\"\u003epkgstats\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci-review-tools/pkgstats/releases/tag/v0.2.4\"\u003e\u003ccode\u003ev0.2.4\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/refsplitr\" title=\"author name disambiguation, author georeferencing, and mapping of coauthorship networks with Web of Science data\"\u003erefsplitr\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/refsplitr/releases/tag/v1.2.3\"\u003e\u003ccode\u003ev1.2.3\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/npi\" title=\"Access the U.S. National Provider Identifier Registry API\"\u003enpi\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/npi/releases/tag/v0.3.0\"\u003e\u003ccode\u003ev0.3.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/rerddap\" title=\"General Purpose Client for ERDDAP™ Servers\"\u003ererddap\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/rerddap/releases/tag/v1.3.0\"\u003e\u003ccode\u003ev1.3.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/stantargets\" title=\"Targets for Stan Workflows\"\u003estantargets\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/stantargets/releases/tag/0.1.3\"\u003e\u003ccode\u003e0.1.3\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/openalexR\" title=\"Getting Bibliographic Records from OpenAlex Database Using DSL API\"\u003eopenalexR\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/openalexR/releases/tag/v3.1.0\"\u003e\u003ccode\u003ev3.1.0\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/ernest\" title=\"A Toolkit for Nested Sampling\"\u003eernest\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/ernest/releases/tag/v1.2.5\"\u003e\u003ccode\u003ev1.2.5\u003c/code\u003e\u003c/a\u003e), \u003ca href=\"https://docs.ropensci.org/mregions2\" title=\"Access Data from Marineregions.org: Gazetteer \u0026amp; Data Products\"\u003emregions2\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/mregions2/releases/tag/v1.1.3\"\u003e\u003ccode\u003ev1.1.3\u003c/code\u003e\u003c/a\u003e), and \u003ca href=\"https://docs.ropensci.org/spiro\" title=\"Manage Data from Cardiopulmonary Exercise Testing\"\u003espiro\u003c/a\u003e (\u003ca href=\"https://github.com/ropensci/spiro/releases/tag/v0.2.4\"\u003e\u003ccode\u003ev0.2.4\u003c/code\u003e\u003c/a\u003e).\u003c/p\u003e\n\u003ch2 id=\"software-peer-review\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#software-peer-review\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nSoftware Peer Review\n\u003c/h2\u003e\u003cp\u003eThere are eighteen recently closed and active submissions and 5 submissions on hold. Issues are at different stages:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eFive at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%226/approved%22\"\u003e\u0026lsquo;6/approved\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/763\"\u003eEpiStrainDynamics\u003c/a\u003e, Infer temporal trends of multiple pathogens. Submitted by \u003ca href=\"https://www.smwindecker.com\"\u003eSaras Windecker\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/762\"\u003elakefetch\u003c/a\u003e, Calculate Fetch and Wave Exposure for Lake Sampling Points. Submitted by \u003ca href=\"https://github.com/jeremylfarrell\"\u003ejeremylfarrell\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/743\"\u003eRAMEN\u003c/a\u003e, RAMEN: Regional Association of Methylome variability with the Exposome and geNome. Submitted by \u003ca href=\"https://erick-navarrodelgado.netlify.app\"\u003eErick Navarro-Delgado\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/704\"\u003epriorsense\u003c/a\u003e, Prior Diagnostics and Sensitivity Analysis. Submitted by \u003ca href=\"https://github.com/n-kall\"\u003eNoa Kallioinen\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/615\"\u003egalamm\u003c/a\u003e, Generalized Additive Latent and Mixed Models. Submitted by \u003ca href=\"https://osorensen.no\"\u003eØystein Sørensen\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTwo at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%225/awaiting-reviewer(s)-response%22\"\u003e\u0026lsquo;5/awaiting-reviewer(s)-response\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/744\"\u003eRAQSAPI\u003c/a\u003e, A Simple Interface to the US EPA Air Quality System Data Mart API. Submitted by \u003ca href=\"https://github.com/mccroweyclinton-EPA\"\u003emccroweyclinton-EPA\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/765\"\u003eciecl\u003c/a\u003e, International Classification of Diseases ICD-10/ICD-11 for Chile. Submitted by \u003ca href=\"https://github.com/Rodotasso\"\u003eRodolfo Tasso\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTwo at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%224/review(s)-in-awaiting-changes%22\"\u003e\u0026lsquo;4/review(s)-in-awaiting-changes\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/718\"\u003ercrisp\u003c/a\u003e, Automate the Delineation of Urban River Spaces. Submitted by \u003ca href=\"https://github.com/cforgaci\"\u003eClaudiu Forgaci\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/717\"\u003ecoevolve\u003c/a\u003e, Fit Bayesian Generalized Dynamic Phylogenetic Models using Stan. Submitted by \u003ca href=\"https://scottclaessens.github.io/\"\u003eScott Claessens\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTwo at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%223/reviewer(s)-assigned%22\"\u003e\u0026lsquo;3/reviewer(s)-assigned\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/792\"\u003ebrapiR2\u003c/a\u003e, A Tidyverse-Native Client for the BrAPI v2 (Breeding API) Specification. Submitted by \u003ca href=\"https://orcid.org/0009-0007-1642-0172\"\u003eAyo\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/787\"\u003eibger\u003c/a\u003e, Access the IBGE Aggregate Data API from R. Submitted by \u003ca href=\"https://castlab.org\"\u003eAndre Leite Wanderley\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eThree at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%222/seeking-reviewer(s)%22\"\u003e\u0026lsquo;2/seeking-reviewer(s)\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/775\"\u003egrumpy\u003c/a\u003e, Read NumPy .npy and .npz Files. Submitted by \u003ca href=\"https://hugogruson.fr/\"\u003eHugo Gruson\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/774\"\u003etezr\u003c/a\u003e, Access Thesis Metadata from Turkiye\u0026rsquo;s National Thesis Center. Submitted by \u003ca href=\"https://emraher.com\"\u003eEmrah Er\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/769\"\u003erfastlowess\u003c/a\u003e, High-Performance LOWESS Smoothing for R. Submitted by \u003ca href=\"https://github.com/thisisamirv\"\u003eAmir Valizadeh\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eFour at \u003ca href=\"https://github.com/ropensci/software-review/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc+label%3A%221/editor-checks%22\"\u003e\u0026lsquo;1/editor-checks\u0026rsquo;\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/799\"\u003ecamtrapReport\u003c/a\u003e, Camera-Trap Report Generator. Submitted by \u003ca href=\"https://www.uu.nl/staff/EEbrahimi\"\u003eElham Ebrahimi\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/785\"\u003enert\u003c/a\u003e, Curated Access to TERN Environmental Raster Data. Submitted by \u003ca href=\"https://scholar.google.com.au/citations?user=zG1uKrcAAAAJ\u0026amp;hl=en\"\u003eMax Moldovan\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/777\"\u003eOptSurvCutR\u003c/a\u003e, Optimal Survival Cut-Point Discovery for Time-to-Event Analysis with OptSurvCutR. Submitted by \u003ca href=\"https://github.com/paytonyau\"\u003ePayton Yau\u003c/a\u003e. (Stats).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"https://github.com/ropensci/software-review/issues/766\"\u003eHydraR\u003c/a\u003e, Stateful Agentic Orchestration for Scientific Reproducibility. Submitted by \u003ca href=\"https://www.mq.edu.au/research/research-centres-groups-and-facilities/facilities/australian-proteome-analysis-facility\"\u003eIgnatius Pang\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eFind out more about \u003ca href=\"/software-review\"\u003eSoftware Peer Review\u003c/a\u003e and how to get involved.\u003c/p\u003e\n\u003ch2 id=\"on-the-blog\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#on-the-blog\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nOn the blog\n\u003c/h2\u003e\u003c!-- Do not forget to rebase your branch! --\u003e\n\u003ch3 id=\"software-review\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#software-review\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nSoftware Review\n\u003c/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"/blog/2026/07/14/15yo-eunseop-kim\"\u003eFrom Peer Review to Mentorship: My rOpenSci Story\u003c/a\u003e by Eunseop Kim. From submitting a package, to reviewing one, to mentoring a Champion: my path with rOpenSci.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"/blog/2026/07/02/editor-tools\"\u003eFOSS Tools for Lazy Editors\u003c/a\u003e by Steffi LaZerte. How we streamlined the editing of our blog posts using 4 open-source tools that you could adopt too.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"/blog/2026/08/06/the-journey-of-nycopendata-from-classroom-to-community\"\u003eThe Journey of {nycOpenData}: From Classroom to Community\u003c/a\u003e by Christian Martinez.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"/blog/2026/08/10/analisis-demografico-con-arcenso\"\u003eFrom Census Data to Demographic Analysis with ARcenso: A Reproducible Workflow in R\u003c/a\u003e by Andrea Gomez Vargas and Emanuel Ciardullo. How to Access and Process the 1970 and 1980 Argentine Censuses Using R. Other languages: \u003ca href='/es/blog/2026/08/10/analisis-demografico-con-arcenso' lang='es'\u003eDe datos censales a análisis demográficos con ARcenso: un flujo de trabajo reproducible en R (es)\u003c/a\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cfigure class=\"center\"\u003e\u003cimg src=\"https://ropensci.org/es/blog/2026/08/10/analisis-demografico-con-arcenso/portada-blog.es.png\"\n\t\t\talt=\"Hex logo de ARcenso sobre documentos históricos de censos argentinos de 1970 y 1980\" width=\"400\"\u003e\n\u003c/figure\u003e\n\n\u003ch3 id=\"tech-notes\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#tech-notes\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nTech Notes\n\u003c/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"/blog/2026/07/08/r-universe-apis-use-cases\"\u003eAn API for Everything There Is to Know About Packages\u003c/a\u003e by Maëlle Salmon. Use cases of the R-Universe APIs.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003ca href=\"/blog/2026/08/06/r-universe-winarm\"\u003eWindows ARM64 comes to R-universe\u003c/a\u003e by Jeroen Ooms.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2 id=\"calls-for-contributions\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#calls-for-contributions\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCalls for contributions\n\u003c/h2\u003e\u003ch3 id=\"calls-for-maintainers\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#calls-for-maintainers\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCalls for maintainers\n\u003c/h3\u003e\u003cp\u003eIf you\u0026rsquo;re interested in maintaining any of the R packages below, you might enjoy reading our blog post \u003ca href=\"/blog/2023/02/07/what-does-it-mean-to-maintain-a-package/\"\u003eWhat Does It Mean to Maintain a Package?\u003c/a\u003e.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://docs.ropensci.org/charlatan\"\u003echarlatan\u003c/a\u003e, create fake data in R. \u003ca href=\"https://github.com/ropensci/charlatan/issues/150\"\u003eIssue for volunteering\u003c/a\u003e.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3 id=\"calls-for-contributions-1\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#calls-for-contributions-1\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nCalls for contributions\n\u003c/h3\u003e\u003cp\u003eRefer to our \u003ca href=\"/help-wanted/\"\u003ehelp wanted page\u003c/a\u003e \u0026ndash; before opening a PR, we recommend asking in the issue whether help is still needed.\u003c/p\u003e\n\u003ch2 id=\"package-development-corner\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#package-development-corner\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nPackage development corner\n\u003c/h2\u003e\u003cp\u003eSome useful information for R package developers. \u0026#x1f440;\u003c/p\u003e\n\u003ch3 id=\"from-rd-files-to-quarto\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#from-rd-files-to-quarto\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nFrom Rd files to Quarto\n\u003c/h3\u003e\u003cp\u003eEdgar Ruiz from Posit released \u003ca href=\"https://opensource.posit.co/blog/2026-06-18_pkgsite-0-1-0/\"\u003epkgsite\u003c/a\u003e, a package for converting your package\u0026rsquo;s \u003ccode\u003e.Rd\u003c/code\u003e files to Quarto. It creates qmd files that you can integrate as you want in a Quarto website.\u003c/p\u003e\n\u003ch3 id=\"mutation-testing-fuzzy-testing\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#mutation-testing-fuzzy-testing\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nMutation testing, fuzzy testing\n\u003c/h3\u003e\u003cp\u003eFirst of all, a reminder in case you confuse the two concepts\u0026hellip;\u003c/p\u003e\n\u003cp\u003e👽️ Mutation testing: you run tests on mutated version of the \u003cem\u003ecode\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e🚮 Fuzzy testing: you run tests with all sorts of \u003cem\u003einputs\u003c/em\u003e to the code.\u003c/p\u003e\n\u003cp\u003eAt useR! 2026, both topics were covered:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003emutation testing in \u003ca href=\"https://docs.google.com/presentation/d/1T5iK0gRBFF869Q6eirtmYVV-5ABD4EN-WBJI5gl5EUY/edit?slide=id.g3efebd0f55a_0_99#slide=id.g3efebd0f55a_0_99\"\u003eBeyond Code Coverage: Mutation Testing in R with mutator\u003c/a\u003e by Assanali Amandykov, Pierre Donat-Bouillud.\u003c/li\u003e\n\u003cli\u003efuzzy testing in \u003ca href=\"https://events.digital-research.academy/event/109/contributions/430/attachments/187/407/slides-v2.pdf\"\u003eFuzz-testing R-based research software for robustness\u003c/a\u003e by Marco Colombo.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3 id=\"roxyreqs\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#roxyreqs\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nroxyreqs\n\u003c/h3\u003e\u003cp\u003eAlso at useR!, Moritz Lang and collaborators introduced \u003ca href=\"https://github.com/mnlang/roxyreqs\"\u003eroxyreqs\u003c/a\u003e, a package for adding roxygen2-like documentation to testthat. \u003ca href=\"https://events.digital-research.academy/event/109/contributions/471/attachments/69/201/roxyreqs-user2026.pdf\"\u003eSlides\u003c/a\u003e.\u003c/p\u003e\n\u003ch3 id=\"checktor-a-new-helper-for-cran-submissions\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#checktor-a-new-helper-for-cran-submissions\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nchecktor, a new helper for CRAN submissions\n\u003c/h3\u003e\u003cp\u003eIf you want to submit your package to CRAN, you can get help through the \u003ca href=\"https://contributor.r-project.org/cran-cookbook/\"\u003eCRAN cookbook\u003c/a\u003e, the \u003ca href=\"https://github.com/ThinkR-open/prepare-for-cran\"\u003ecollaborative list maintained by ThinkR\u003c/a\u003e and now a new package, checktor by James Balamuta! Read more in \u003ca href=\"https://blog.thecoatlessprofessor.com/programming/r/the-check-passed-the-reviewer-didnt/\"\u003eJames\u0026rsquo; post\u003c/a\u003e.\u003c/p\u003e\n\u003ch3 id=\"interesting-ai-reads\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#interesting-ai-reads\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nInteresting AI reads\n\u003c/h3\u003e\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://sfconservancy.org/llm-gen-ai/llm-backed-generative-ai-recommendations.html\"\u003eRecommendations When Using LLM-backed Generative AI Systems for FOSS Contributions\u003c/a\u003e by Software Freedom Conservancy, shared by Will Gearty.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ft.com/content/cec8df9e-b43b-4cd1-8feb-c07e804e8d33\"\u003eWho cleans up after the vibe-coding party?\u003c/a\u003e by Sam Learner in the Financial Times.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://niccrane.com/posts/ai-tooling-open-source/\"\u003eAI Tooling and Open Source\u003c/a\u003e in which Nic Crane discusses \u0026ldquo;how AI tooling affects open source, the actions maintainers have been taking to address the less positive aspects, and emerging policies that open source projects are implementing around the topic of AI-generated pull requests\u0026rdquo;.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2 id=\"last-words\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#last-words\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nLast words\n\u003c/h2\u003e\u003cp\u003eThanks for reading! If you want to get involved with rOpenSci, check out our \u003ca href=\"https://contributing.ropensci.org\"\u003eContributing Guide\u003c/a\u003e. This guide will help direct you to the right place, whether you want to make code contributions, non-code contributions, or contribute in other ways such as through sharing use cases. You can also support our work through \u003ca href=\"/donate\"\u003edonations\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eIf you haven\u0026rsquo;t subscribed to our newsletter yet, you can \u003ca href=\"/news/\"\u003edo so though our signup form\u003c/a\u003e. Until it\u0026rsquo;s time for our next newsletter, you can keep in touch with us through our \u003ca href=\"/\"\u003ewebsite\u003c/a\u003e, \u003ca href=\"https://hachyderm.io/@rOpenSci\"\u003eMastodon\u003c/a\u003e, or \u003ca href=\"https://www.linkedin.com/company/ropensci/\"\u003eLinkedIn\u003c/a\u003e. See you soon!\u003c/p\u003e\n","url":"https://ropensci.org/blog/2026/08/28/news-august-2026/","date_published":"2026-08-28T00:00:00+00:00"},{"id":"https://ropensci.org/blog/2026/08/10/analisis-demografico-con-arcenso/","title":"From Census Data to Demographic Analysis with ARcenso: A Reproducible Workflow in R","content_text":"\u003cp\u003ePopulation censuses are a key source of information for understanding the composition of populations and how they change across regions within a country. They provide essential evidence for research, the design and evaluation of public policies, and informed decision-making.\u003c/p\u003e\n\u003cp\u003eWorking with census data typically involves several preliminary steps: identifying what information is available, downloading the data, organizing it, and preparing it for analysis. When this information is scattered across multiple sources and provided in different formats, the process can become complex.\u003c/p\u003e\n\u003cbr\u003e\n\u003cfigure\u003e\u003cimg src=\"/es/blog/2026/08/10/analisis-demografico-con-arcenso/portada-blog.es.png\"\n\t\t\talt=\"Illustration of the Argentine Census featuring the ARcenso and rOpenSci logos, a hornero (the national bird), and graphic material from the 1970 and 1980 censuses.\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003eARcenso blog homepage\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003cp\u003e\u003ca href=\"https://soyandrea.github.io/arcenso/\"\u003eARcenso\u003c/a\u003e is an R package developed as part of \u003ca href=\"/es/champions/\"\u003ethe     rOpenSci Champions Program\u003c/a\u003e to facilitate access to Argentine census data and simplify its analysis.\u003c/p\u003e\n\u003cp\u003eIn this article, the ARcenso development team demonstrates how to work with the historical census data available through the package in a simple, reproducible way.\u003c/p\u003e\n\u003cp\u003eThe goal is to conduct a demographic analysis using official national data from the 1970 and 1980 censuses, combining visualisations and tables to explore the structure of the population—that is, how it is distributed by age and sex. This type of analysis helps characterise demographic changes over time, providing key information for research and the design of public policies.\u003c/p\u003e\n\u003ch2 id=\"getting-started\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#getting-started\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nGetting started\n\u003c/h2\u003e\u003cp\u003eTo run the code examples from this article on your own computer, make sure you have the following packages installed:\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# If you don\u0026#39;t have pak installed\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003einstall.packages\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;pak\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# Install ARcenso from GitHub\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epak\u003c/span\u003e\u003cspan class=\"o\"\u003e::\u003c/span\u003e\u003cspan class=\"nf\"\u003epkg_install\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;soyandrea/arcenso\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# Install the required packages from CRAN\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003einstall.packages\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;dplyr\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;tidyr\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;ggplot2\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;gt\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e))\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003cp\u003eNext, we load the packages needed to work with the census data and build indicators for the analysis:\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003elibrary\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003earcenso\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e   \u003cspan class=\"c1\"\u003e# access census data\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003elibrary\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003edplyr\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e     \u003cspan class=\"c1\"\u003e# data manipulation\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003elibrary\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003etidyr\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e     \u003cspan class=\"c1\"\u003e# data tidying and transformation\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003elibrary\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eggplot2\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e   \u003cspan class=\"c1\"\u003e# data visualisation\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003elibrary\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003egt\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e        \u003cspan class=\"c1\"\u003e# table formatting\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003ch2 id=\"accessing-census-data\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#accessing-census-data\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nAccessing census data\n\u003c/h2\u003e\u003cp\u003eNow that the required packages are installed and loaded, we can use ARcenso to access census data from the 1970 and 1980 censuses. The package allows users to retrieve information by census year, topic, and geographic area of interest, using the official geographic codes defined by the\n\u003ca href=\"https://www.indec.gob.ar/indec/web/Nivel3-Tema-2-41\"\u003e     National Institute of Statistics and Censuses (INDEC) of Argentina\u003c/a\u003e   .\u003c/p\u003e\n\u003cp\u003eThe \u003ccode\u003echeck_repository()\u003c/code\u003e function helps identify the datasets available in the package. The \u003ccode\u003etopic\u003c/code\u003e argument specifies the subject of interest (for example, population structure), while \u003ccode\u003egeo_code\u003c/code\u003e identifies the geographic area.\u003c/p\u003e\n\u003cp\u003eIf you are unsure which values are available for these arguments, you can explore the package metadata. The \u003ccode\u003egeo_metadata\u003c/code\u003e object contains the available geographic areas and their corresponding codes, while \u003ccode\u003ecensus_metadata\u003c/code\u003e provides information about the topics and tables included in the package.\u003c/p\u003e\n\u003cp\u003eIn this example, we use population structure data (\u003ccode\u003etopic = \u0026quot;estructura\u0026quot;\u003c/code\u003e) for the entire country (\u003ccode\u003egeo_code = \u0026quot;00\u0026quot;\u003c/code\u003e). As a first step, we use \u003ccode\u003echeck_repository()\u003c/code\u003e to see which datasets are available.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003echeck_repository\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003etopic\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;estructura\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003egeo_code\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;00\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003cpre tabindex=\"0\"\u003e\u003ccode\u003e# A tibble: 4 × 3\n  id_cuadro              anio titulo                                            \n  \u0026lt;chr\u0026gt;                 \u0026lt;dbl\u0026gt; \u0026lt;chr\u0026gt;                                             \n1 1970_00_estructura_01  1970 Cuadro 1. Total del país. Población total, por gr…\n2 1980_00_estructura_01  1980 Cuadro G3. Centros urbanos según tamaño y poblaci…\n3 1980_00_estructura_02  1980 Cuadro G1. Total del país. Población total según …\n4 1980_00_estructura_03  1980 Cuadro G2. Total del país. Población según sexo y…\n\u003c/code\u003e\u003c/pre\u003e\u003cp\u003eThe output of \u003ccode\u003echeck_repository()\u003c/code\u003e lists the available years for the selected combination of topic and geographic area, together with the corresponding table identifiers (IDs) and their titles. Based on this information, we select the tables \u003ccode\u003e1970_00_estructura_01\u003c/code\u003e and \u003ccode\u003e1980_00_estructura_03\u003c/code\u003e, which contain tabulations of the country\u0026rsquo;s total population by sex and age group and will be used throughout this analysis.\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003e\u003cstrong\u003eTip\u003c/strong\u003e: You can also explore the available data interactively using \u003ccode\u003earcenso_app()\u003c/code\u003e. Once you find the table you need, simply copy its ID and use it in your analysis.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cfigure\u003e\u003cimg src=\"/es/blog/2026/08/10/analisis-demografico-con-arcenso/shiny_arcenso.es.png\"\n\t\t\talt=\"Shiny ARcenso Application: View census data filtered by year, geographic scope, and topic, displaying the 1970 literacy table.\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003eInteractive census data explorer with \u003ccode\u003earcenso_app()\u003c/code\u003e\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003ch2 id=\"data-preparation\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#data-preparation\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nData preparation\n\u003c/h2\u003e\u003cp\u003eOnce the tables of interest have been identified, we use \u003ccode\u003eget_census()\u003c/code\u003e to import them directly into the R session using their table identifiers.\u003c/p\u003e\n\u003cp\u003eAs the structures of the two tables are not identical, we perform a series of transformations to harmonise the variables and create a consistent basis for comparison across censuses. In particular, we recode the age categories into five-year groups to ensure a common structure and add a column identifying the census year.\u003c/p\u003e\n\u003ch3 id=\"1970-census\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#1970-census\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\n1970 Census\n\u003c/h3\u003e\u003cp\u003eFor the 1970 census, the data are already grouped into five-year age groups, so we only need to adjust the format of some labels and keep the variables relevant to the analysis.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# Country Total\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epoblacion_1970\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"nf\"\u003eget_census\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eid\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;1970_00_estructura_01\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epob_1970\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion_1970\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003efilter\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003esexo\u003c/span\u003e \u003cspan class=\"o\"\u003e!=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Total\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003emutate\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecenso\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e1970\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003egrupo_de_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ecase_when\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003egrupo_de_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e==\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;0-4\u0026#34;\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;00-04\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003egrupo_de_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e==\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;5-9\u0026#34;\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;05-09\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"kc\"\u003eTRUE\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_de_edad\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003erename\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_de_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003eselect\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003ch3 id=\"1980-census\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#1980-census\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\n1980 Census\n\u003c/h3\u003e\u003cp\u003eIn contrast, the 1980 census table reports age as single years and includes additional information that is not relevant to this analysis. We therefore select the categories of interest and aggregate the data into five-year age groups to make them comparable with the 1970 census.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epoblacion_1980\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"nf\"\u003eget_census\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eid\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;1980_00_estructura_03\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epob_1980\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion_1980\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003efilter\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eurbano_rural\u003c/span\u003e \u003cspan class=\"o\"\u003e==\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Total\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e \u003cspan class=\"o\"\u003e!=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Total\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003eedad\u003c/span\u003e \u003cspan class=\"o\"\u003e!=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Total\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003emutate\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecenso\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e1980\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eifelse\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eedad\u003c/span\u003e \u003cspan class=\"o\"\u003e==\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;85 y más\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"m\"\u003e85\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"nf\"\u003eas.numeric\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eedad\u003c/span\u003e\u003cspan class=\"p\"\u003e)),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ecase_when\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e0\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e4\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;00-04\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e5\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e9\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;05-09\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e10\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e14\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;10-14\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e15\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e19\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;15-19\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e20\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e24\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;20-24\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e25\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e29\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;25-29\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e30\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e34\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;30-34\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e35\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e39\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;35-39\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e40\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e44\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;40-44\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e45\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e49\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;45-49\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e50\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e54\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;50-54\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e55\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e59\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;55-59\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e60\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e64\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;60-64\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e65\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e69\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;65-69\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e70\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e74\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;70-74\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e75\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e79\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;75-79\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003eedad_num\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e80\u003c/span\u003e\u003cspan class=\"o\"\u003e:\u003c/span\u003e\u003cspan class=\"m\"\u003e84\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;80-84\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"kc\"\u003eTRUE\u003c/span\u003e \u003cspan class=\"o\"\u003e~\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;85 y más\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003eselect\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003ch3 id=\"building-the-integrated-database\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#building-the-integrated-database\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nBuilding the integrated database\n\u003c/h3\u003e\u003cp\u003eOnce both tables have been processed, we combine them into a single dataset and define the final structure of the variables, preparing the data for visualisation and the analysis of demographic indicators.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# We combine both geographic areas and prepare the variables for use\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003ebind_rows\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epob_1970\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epob_1980\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003emutate\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eas.numeric\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esexo\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003efactor\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003elevels\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;Varones\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Mujeres\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003efactor\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003elevels\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;00-04\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;05-09\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;10-14\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;15-19\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;20-24\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;25-29\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;30-34\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;35-39\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;40-44\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;45-49\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;50-54\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;55-59\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;60-64\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;65-69\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;70-74\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;75-79\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;80-84\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e        \u003cspan class=\"s\"\u003e\u0026#34;85 y más\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003ch2 id=\"population-structure\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#population-structure\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nPopulation structure\n\u003c/h2\u003e\u003cp\u003eNow that we have a dataset combining both censuses, with population totals organised by census year, sex, and age group, we can consistently compare the population composition across the two census years.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003ehead\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"c1\"\u003e# A tibble: 6 × 4\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003ecenso\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e    \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"o\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"n\"\u003edbl\u003c/span\u003e\u003cspan class=\"o\"\u003e\u0026gt;\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"n\"\u003efct\u003c/span\u003e\u003cspan class=\"o\"\u003e\u0026gt;\u003c/span\u003e   \u003cspan class=\"o\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"n\"\u003efct\u003c/span\u003e\u003cspan class=\"o\"\u003e\u0026gt;\u003c/span\u003e          \u003cspan class=\"o\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"n\"\u003edbl\u003c/span\u003e\u003cspan class=\"o\"\u003e\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"m\"\u003e1\u003c/span\u003e  \u003cspan class=\"m\"\u003e1970\u003c/span\u003e \u003cspan class=\"n\"\u003eVarones\u003c/span\u003e \u003cspan class=\"m\"\u003e00-04\u003c/span\u003e        \u003cspan class=\"m\"\u003e1196950\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"m\"\u003e2\u003c/span\u003e  \u003cspan class=\"m\"\u003e1970\u003c/span\u003e \u003cspan class=\"n\"\u003eMujeres\u003c/span\u003e \u003cspan class=\"m\"\u003e00-04\u003c/span\u003e        \u003cspan class=\"m\"\u003e1158350\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"m\"\u003e3\u003c/span\u003e  \u003cspan class=\"m\"\u003e1970\u003c/span\u003e \u003cspan class=\"n\"\u003eVarones\u003c/span\u003e \u003cspan class=\"m\"\u003e05-09\u003c/span\u003e        \u003cspan class=\"m\"\u003e1163050\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"m\"\u003e4\u003c/span\u003e  \u003cspan class=\"m\"\u003e1970\u003c/span\u003e \u003cspan class=\"n\"\u003eMujeres\u003c/span\u003e \u003cspan class=\"m\"\u003e05-09\u003c/span\u003e        \u003cspan class=\"m\"\u003e1133950\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"m\"\u003e5\u003c/span\u003e  \u003cspan class=\"m\"\u003e1970\u003c/span\u003e \u003cspan class=\"n\"\u003eVarones\u003c/span\u003e \u003cspan class=\"m\"\u003e10-14\u003c/span\u003e        \u003cspan class=\"m\"\u003e1114300\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"m\"\u003e6\u003c/span\u003e  \u003cspan class=\"m\"\u003e1970\u003c/span\u003e \u003cspan class=\"n\"\u003eMujeres\u003c/span\u003e \u003cspan class=\"m\"\u003e10-14\u003c/span\u003e        \u003cspan class=\"m\"\u003e1086850\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003cp\u003eOrganising the population by sex and five-year age groups allows us to analyse its structure using a variety of visualisations. In this case, we use a population pyramid, which makes it easier to interpret both dimensions together.\u003c/p\u003e\n\u003ch3 id=\"population-pyramid\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#population-pyramid\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nPopulation pyramid\n\u003c/h3\u003e\u003cp\u003eA population pyramid displays the distribution of the population by age and sex simultaneously, typically showing males on the left and females on the right. By representing the proportion of people in each five-year age group, it provides a clear visual summary of the population structure.\u003c/p\u003e\n\u003cp\u003eIn this case, we calculated the relative distribution of the population within each census, allowing us to compare the population structure between 1970 and 1980 regardless of total population size. The shape of the pyramid also allows us to identify broad demographic patterns, such as a higher concentration of younger age groups or a relatively older population profile.\u003c/p\u003e\n\u003cp\u003eWe then calculated the relative distribution of the population in each census and constructed a population pyramid to compare the population structure of the two censuses.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# Dataset for the Population Pyramid\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epiramide\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egroup_by\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003emutate\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epoblacion_rel\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eif_else\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003esexo\u003c/span\u003e \u003cspan class=\"o\"\u003e==\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Varones\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"o\"\u003e-\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e/\u003c/span\u003e \u003cspan class=\"nf\"\u003esum\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e/\u003c/span\u003e \u003cspan class=\"nf\"\u003esum\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003eungroup\u003c/span\u003e\u003cspan class=\"p\"\u003e()\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"c1\"\u003e# Comparison Pyramid\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003epiramide\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003eggplot\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion_rel\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003ey\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003efill\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e))\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egeom_col\u003c/span\u003e\u003cspan class=\"p\"\u003e()\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003efacet_wrap\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"o\"\u003e~\u003c/span\u003e\u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003encol\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e2\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003escale_fill_manual\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003evalues\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;#00f59b\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;#7014f2\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e))\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003escale_x_continuous\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003elabels\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"kr\"\u003efunction\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"nf\"\u003epaste0\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"nf\"\u003eabs\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"nf\"\u003eround\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e*\u003c/span\u003e \u003cspan class=\"m\"\u003e100\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"m\"\u003e1\u003c/span\u003e\u003cspan class=\"p\"\u003e)),\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;%\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003elimits\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e-0.15\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"m\"\u003e0.15\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ebreaks\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eseq\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"m\"\u003e-0.15\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"m\"\u003e0.15\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003eby\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e0.05\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003elabs\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003etitle\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Gráfico 1. Estructura de la población por sexo y grupo quinquenal de edad.\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esubtitle\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Argentina. Años 1970 y 1980\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Porcentaje\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ey\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Grupo quinquenal de edad\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecaption\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Fuente: INDEC, Censo Nacional de Población 1970 y 1980. Procesado con ARcenso.\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003efill\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Sexo\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003etheme_bw\u003c/span\u003e\u003cspan class=\"p\"\u003e()\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003etheme\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003elegend.position\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;bottom\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003estrip.text\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eelement_text\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eface\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;bold\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003esize\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e12\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003cfigure\u003e\u003cimg src=\"/es/blog/2026/08/10/analisis-demografico-con-arcenso/piramide_poblacional_1.es.png\"\n\t\t\talt=\"Population pyramids comparing the distribution by age and sex in Argentina between 1970 and 1980. A narrower base is observed in 1980, along with a slight relative increase in the adult and older adult populations, with differences between men and women.\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003eFigure 1. Population structure by sex and five-year age group. Argentina. Year 1970 and 1980. Source: INDEC, Censo Nacional de Población 1970 y 1980. Processed with ARcenso.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003cp\u003eBoth censuses show a young population structure, with a high concentration of people in the younger age groups. However, by 1980, a slight shift towards the adult age groups is already apparent, suggesting the early stages of population aging.\u003c/p\u003e\n\u003ch2 id=\"construction-of-demographic-indicators\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#construction-of-demographic-indicators\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nConstruction of demographic indicators\n\u003c/h2\u003e\u003cp\u003eWhile the population pyramid provides an overall view of the population structure, demographic indicators offer summary measures that allow these patterns to be quantified and compared more precisely. In this section, we calculate two commonly used indicators to complement the visual analysis.\u003c/p\u003e\n\u003ch3 id=\"aging-index\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#aging-index\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nAging index\n\u003c/h3\u003e\u003cp\u003eThe aging index compares the number of older adults (aged 65 years and over) with the number of children (aged 0–14 years). It provides a simple way to see whether the population is weighted more toward younger age groups or older age groups.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003eenvejecimiento\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egroup_by\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003esummarise\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epoblacion_0a14\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003esum\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion[\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;00-04\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;05-09\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;10-14\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003e]\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epoblacion_65ymas\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003esum\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion[\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;65-69\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;70-74\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;75-79\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;80-84\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;85 y más\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003e]\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003eindice\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eround\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion_65ymas\u003c/span\u003e \u003cspan class=\"o\"\u003e/\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion_0a14\u003c/span\u003e \u003cspan class=\"o\"\u003e*\u003c/span\u003e \u003cspan class=\"m\"\u003e100\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"m\"\u003e0\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"nf\"\u003egt\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eenvejecimiento\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003etab_header\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003etitle\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Comparación del índice de envejecimiento\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esubtitle\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Argentina. Años 1970 y 1980\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003etab_spanner\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003elabel\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Población\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecolumns\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion_0a14\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion_65ymas\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003efmt_number\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecolumns\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion_0a14\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion_65ymas\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003edecimals\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e0\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esep_mark\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;.\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003ecols_label\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epoblacion_0a14\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;0 a 14 años\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003epoblacion_65ymas\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;65 años y más\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003eindice\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Indice\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003etab_source_note\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esource_note\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003emd\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e      \u003cspan class=\"s\"\u003e\u0026#34;**Fuente:** elaboración propia en base a datos de INDEC (Censos Nacionales de Población 1970 y 1980).\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003ctable\u003e\n  \u003cthead\u003e\n    \u003ctr class=\"gt_heading\"\u003e\n      \u003ctd colspan=\"4\" class=\"gt_heading gt_title gt_font_normal\" style\u003eAging Index Comparison\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr class=\"gt_heading\"\u003e\n      \u003ctd colspan=\"4\" class=\"gt_heading gt_subtitle gt_font_normal gt_bottom_border\" style\u003eArgentina. 1970s and 1980s\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr class=\"gt_col_headings gt_spanner_row\"\u003e\n      \u003cth class=\"gt_col_heading gt_columns_bottom_border gt_right\" rowspan=\"2\" colspan=\"1\" scope=\"col\" id=\"censo\"\u003eCensus\u003c/th\u003e\n      \u003cth class=\"gt_center gt_columns_top_border gt_column_spanner_outer\" rowspan=\"1\" colspan=\"2\" scope=\"colgroup\" id=\"Population\"\u003e\n        \u003cdiv class=\"gt_column_spanner\"\u003ePopulation\u003c/div\u003e\n      \u003c/th\u003e\n      \u003cth class=\"gt_col_heading gt_columns_bottom_border gt_right\" rowspan=\"2\" colspan=\"1\" scope=\"col\" id=\"index\"\u003eIndex\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr class=\"gt_col_headings\"\u003e\n      \u003cth class=\"gt_col_heading gt_columns_bottom_border gt_right\" rowspan=\"1\" colspan=\"1\" scope=\"col\" id=\"population_0to14\"\u003eAges 0 to 14\u003c/th\u003e\n      \u003cth class=\"gt_col_heading gt_columns_bottom_border gt_right\" rowspan=\"1\" colspan=\"1\" scope=\"col\" id=\"population_65andover\"\u003e65 years and older\u003c/th\u003e\n    \u003c/tr\u003e\n  \u003c/thead\u003e\n  \u003ctbody class=\"gt_table_body\"\u003e\n    \u003ctr\u003e\u003ctd headers=\"census\" class=\"gt_row gt_right\"\u003e1970\u003c/td\u003e\n\u003ctd headers=\"population_0to14\" class=\"gt_row gt_right\"\u003e6,853,450\u003c/td\u003e\n\u003ctd headers=\"population_65andover\" class=\"gt_row gt_right\"\u003e1,631,400\u003c/td\u003e\n\u003ctd headers=\"index\" class=\"gt_row gt_right\"\u003e24\u003c/td\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003ctd headers=\"census\" class=\"gt_row gt_right\"\u003e1980\u003c/td\u003e\n\u003ctd headers=\"population_0to14\" class=\"gt_row gt_right\"\u003e8,480,768\u003c/td\u003e\n\u003ctd headers=\"population_65_and_over\" class=\"gt_row gt_right\"\u003e2,290,564\u003c/td\u003e\n\u003ctd headers=\"index\" class=\"gt_row gt_right\"\u003e27\u003c/td\u003e\u003c/tr\u003e\n  \u003c/tbody\u003e\n  \u003ctfoot\u003e\n    \u003ctr class=\"gt_sourcenotes\"\u003e\n      \u003ctd class=\"gt_sourcenote\" colspan=\"4\"\u003e\u003cspan class='gt_from_md'\u003e\u003cstrong\u003eSource:\u003c/strong\u003e Author’s own calculations based on INDEC data (1970 and 1980 National Population Censuses).\u003c/span\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003eThe increase in the aging index reflects a change in the population age structure between 1970 and 1980, indicating a larger relative share of people aged 65 years and over compared with the younger population. This suggests a gradual aging of the population.\u003c/p\u003e\n\u003ch3 id=\"female-to-male-ratio\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#female-to-male-ratio\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nFemale-to-Male ratio\n\u003c/h3\u003e\u003cp\u003eThis indicator shows how many women there are for every 100 men in a specific population group. Here, we calculate it for people aged 60 years and over, where differences between women and men tend to become more pronounced.\u003c/p\u003e\n\u003cdiv class=\"highlight\"\u003e\u003cpre tabindex=\"0\" class=\"chroma\"\u003e\u003ccode class=\"language-r\" data-lang=\"r\"\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003efeminidad\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003efilter\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e \u003cspan class=\"o\"\u003e%in%\u003c/span\u003e \u003cspan class=\"nf\"\u003ec\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"s\"\u003e\u0026#34;60-64\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;65-69\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;70-74\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;75-79\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;80-84\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;85 y más\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egroup_by\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003esummarise\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003esum\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e \u003cspan class=\"n\"\u003e.groups\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;drop\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003epivot_wider\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003enames_from\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003esexo\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003evalues_from\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003epoblacion\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003emutate\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003eindice_feminidad\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"nf\"\u003eround\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003eMujeres\u003c/span\u003e \u003cspan class=\"o\"\u003e/\u003c/span\u003e \u003cspan class=\"n\"\u003eVarones\u003c/span\u003e \u003cspan class=\"o\"\u003e*\u003c/span\u003e \u003cspan class=\"m\"\u003e100\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"m\"\u003e0\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003eselect\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"o\"\u003e-\u003c/span\u003e\u003cspan class=\"n\"\u003eVarones\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"o\"\u003e-\u003c/span\u003e\u003cspan class=\"n\"\u003eMujeres\u003c/span\u003e\u003cspan class=\"p\"\u003e)\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003efeminidad_plot\u003c/span\u003e \u003cspan class=\"o\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"n\"\u003efeminidad\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003epivot_wider\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003enames_from\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003evalues_from\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003eindice_feminidad\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003enames_prefix\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;censo_\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e|\u0026gt;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003eggplot\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ey\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e))\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egeom_segment\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1970\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003exend\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1980\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003eyend\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003egrupo_edad\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecolor\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;grey85\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003elinewidth\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e1\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egeom_point\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1970\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecolor\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;#ff0f7b\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esize\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e3\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egeom_point\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1980\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecolor\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;#f89b29\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esize\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e3\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egeom_text\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1970\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003elabel\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1970\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ehjust\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e1.4\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esize\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e3\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003egeom_text\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"nf\"\u003eaes\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1980\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e \u003cspan class=\"n\"\u003elabel\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"n\"\u003ecenso_1980\u003c/span\u003e\u003cspan class=\"p\"\u003e),\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ehjust\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e-0.4\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esize\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"m\"\u003e3\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003elabs\u003c/span\u003e\u003cspan class=\"p\"\u003e(\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ex\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Mujeres por cada 100 varones\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ey\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Grupo de edad\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003etitle\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Cambio en el índice de feminidad de la población de 60 años y más\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003esubtitle\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Argentina, Años 1970 y 1980\u0026#34;\u003c/span\u003e\u003cspan class=\"p\"\u003e,\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e    \u003cspan class=\"n\"\u003ecaption\u003c/span\u003e \u003cspan class=\"o\"\u003e=\u003c/span\u003e \u003cspan class=\"s\"\u003e\u0026#34;Fuente: INDEC, Censo Nacional de Población 1970 y 1980. Procesado con ARcenso.\u0026#34;\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"p\"\u003e)\u003c/span\u003e \u003cspan class=\"o\"\u003e+\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e  \u003cspan class=\"nf\"\u003etheme_minimal\u003c/span\u003e\u003cspan class=\"p\"\u003e()\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\n\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"line\"\u003e\u003cspan class=\"cl\"\u003e\u003cspan class=\"n\"\u003efeminidad_plot\u003c/span\u003e\n\u003c/span\u003e\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\u003cfigure\u003e\u003cimg src=\"/es/blog/2026/08/10/analisis-demografico-con-arcenso/indice_feminidad.es.png\"\n\t\t\talt=\"Graph comparing the sex ratio (women per 100 men) in the population aged 60 and older between 1970 and 1980, by five-year age groups. An increase in the ratio is observed across all age groups, with higher values among older age groups, indicating a relatively higher proportion of women.\"\u003e\u003cfigcaption\u003e\n\t\t\t\u003cp\u003eChange in the female-to-male ratio among the population aged 60 and older. Argentina. Year 1970 and 1980. Source: INDEC, Censo Nacional de Población 1970 y 1980. Processed with ARcenso.\u003c/p\u003e\n\t\t\u003c/figcaption\u003e\n\u003c/figure\u003e\n\n\u003cp\u003eThe female-to-male ratio shows a higher proportion of women in the older age groups. This difference becomes more pronounced between 1970 and 1980 across all the age groups analysed, reflecting patterns of higher female life expectancy.\u003c/p\u003e\n\u003ch2 id=\"what-does-this-analysis-tell-us\"\u003e\n\n\u003ca class=\"anchor d-print-none\" href=\"#what-does-this-analysis-tell-us\"\u003e\n  \u003csmall\u003e\u0026#x1F517;\u003c/small\u003e\n\u003c/a\u003e\n\nWhat does this analysis tell us?\n\u003c/h2\u003e\u003cp\u003eIn demographic analysis, the most time-consuming part is often not calculating indicators or creating visualisations, but the work that comes beforehand: identifying the available data for each census, understanding how it is organised, and building a consistent framework that enables comparisons across census years.\u003c/p\u003e\n\u003cp\u003eIn this example, that process involved locating the relevant tables, understanding the structural differences between the 1970 and 1980 censuses, and harmonising the variables based on the available information to create a comparable dataset. This is precisely what ARcenso is designed to simplify. The \u003ccode\u003echeck_repository()\u003c/code\u003e function helps identify the available tables, \u003ccode\u003eget_census()\u003c/code\u003e imports the data into R in a structured format, and \u003ccode\u003earcenso_app()\u003c/code\u003e provides an interactive way to explore the repository.\u003c/p\u003e\n\u003cp\u003eOnce the data have been organised, the analysis becomes more accessible, reproducible, and easier to extend to new questions.\u003c/p\u003e\n\u003cp\u003eARcenso is still a work in progress. Future developments will incorporate additional census years and continue expanding the package\u0026rsquo;s analytical capabilities. The package was created to make Argentine census data easier to discover, access, and analyse, while building on the collaborative efforts of the open-source community.\u003c/p\u003e\n\u003cp\u003eIf you would like to explore further,check out the \u003ca href=\"https://soyandrea.github.io/arcenso/articles/indicadores_demograficos.html\"\u003e\u003cem\u003evignettes\u003c/em\u003e\u003c/a\u003e in the package, which include additional examples to work with census data.\u003c/p\u003e\n","url":"https://ropensci.org/blog/2026/08/10/analisis-demografico-con-arcenso/","date_published":"2026-08-10T00:00:00+00:00"}]}