Jekyll2023-09-14T10:43:52+00:00https://geographicdata.science/feed.xmlGeographic Data Science with PythonThis book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.
Sergio J. Rey, Dani Arribas-Bel & Levi J. WolfOverview2023-09-13T00:00:00+00:002023-09-13T00:00:00+00:00https://geographicdata.science/bookupdate/2023/09/13/dab_overview<p>Today, Dani gave an overview of the book to the <a href="2023-06-16-liftoff.md">Geographic Data Science Lab</a>, including the motivation for writing it, its contents, and even a live demo. You can watch the talk/demo at:</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/2Qxaf0xQJiY?si=fxooRASYmkCDk297" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe>
<p>Part of the entertainment of this video is watching Dani running the book, live on Teams, from his iPad, and through Jupyter Lab <em>and</em> Rstudio. It is (mostly) a success. If you too would like to run the book on your own machine, as Dani does in the video, here’re some tips.</p>
<p>The trick to getting it all to work is <a href="https://docker.com">Docker</a>. As we argue in <a href="https://geographicdata.science/book/notebooks/02_geospatial_computational_environment.html">Chapter 2</a>, building transferrable platforms that can support open science is non-trivial, but critical. To that end (and leveraging Dani’s <a href="https://darribas.org/gds_env/">GDSenv</a>, our book can run on the GDS Docker image, <a href="https://github.com/darribas/gds_env/releases/tag/v9.0"><code class="language-plaintext highlighter-rouge">v9.0</code></a>. This is the platform you use, for example, when you run our book on Binder, and you can also run it locally on your machine, without the need of internet connectivity. To learn how to run the book on your own machine, we’ve got you covered: Chapter 2 has a <a href="https://geographicdata.science/book/notebooks/02_geospatial_computational_environment.html#running-the-book-in-a-container">section</a> exactly on that!</p>
<p><strong>NOTE</strong> - The only update you will need to apply form the chapter is the
version of the container you will use. We currently specify version <code class="language-plaintext highlighter-rouge">7.0</code>, but
the officially supported image is now <code class="language-plaintext highlighter-rouge">9.0</code>.</p>
<p>At the <a href="https://youtu.be/2Qxaf0xQJiY?feature=shared&t=2023">end of the talk</a>, Dani also runs the book from RStudio (!). This is also supported through Docker and a small toy project of Dani, <a href="https://github.com/GDSL-UL/gdsr"><code class="language-plaintext highlighter-rouge">gdsrpy</code></a>. This container runs on top of the fantastic <a href="https://rocker-project.org/">Rocker</a> project, so you can use those instructions to get it up and running.</p>
<p>In short, you need to download the image:</p>
<blockquote>
<p><code class="language-plaintext highlighter-rouge">docker pull darribas/gdsrpy:2.0</code></p>
</blockquote>
<p>And run it from your machine:</p>
<blockquote>
<p><code class="language-plaintext highlighter-rouge">docker run --rm -ti -e PASSWORD=<your password> -v /folder/to/mount:/home/rstudio/work -p 8787:8787 gdsrpy:2.0</code></p>
</blockquote>
<p>Ideally, you want <code class="language-plaintext highlighter-rouge">/folder/to/mount/</code> to contain a copy of the book, which you
can download from <a href="https://github.com/gdsbook/book/archive/refs/heads/master.zip">here</a> thanks to Github.</p>
<p>Happy hacking!</p>Dani Arribas-BelToday, Dani gave an overview of the book to the Geographic Data Science Lab, including the motivation for writing it, its contents, and even a live demo. You can watch the talk/demo at:Liftoff2023-06-16T00:00:00+00:002023-06-16T00:00:00+00:00https://geographicdata.science/bookupdate/2023/06/16/liftoff<p>Today is the big day. In 2018 (!), we started conversations to turn learning resources we had been developing for a while
into a paper copy book you could buy if you wanted, and always use for free on
the web. CRC agreed and, in 2019, our contract was signed. Initially planned
to be finnished much earlier, the world had different plans for us all…
As we say in Spain, late is better than never. As our CRC agent let us know
this morning, the book is officially published worldwide:</p>
<p><img src="/assets/fig/congrats.png" height="250" /></p>
<p>Last week, we also received our own copies:</p>
<p><img src="/assets/fig/book.png" height="400" /></p>
<p>In preparation for this day, earlier in the spring, we <a href="https://github.com/gdsbook/book/releases/tag/v1.0">tagged</a> the repository
with the version that is closest to what you can buy in print:</p>
<p><a href="https://github.com/gdsbook/book/releases/tag/v1.0"><img src="/assets/fig/tag.png" height="300" /></a></p>
<p>So, it’s out there. In the wild. If you want to know a bit more about the
ideas behind writing the book, you can check out our <a href="2019-08-29-project-launch">earlier
post</a>. And remember, today is the day where you can
start <em>buying</em> the book if you want to show support for the project, but the
content is (and always will be) openly available and updated, to the best of
our abilities, at:</p>
<blockquote>
<p><a href="https://geographicdata.science/book">geographicdata.science/book</a></p>
</blockquote>
<p>Happy hacking!</p>
<p>Serge, Levi and Dani.</p>
<p>Ps. If you want to order your own copy, official page is:</p>
<blockquote>
<p><a href="https://www.routledge.com/Geographic-Data-Science-with-Python/Rey-Arribas-Bel-Wolf/p/book/9781032445953">https://www.routledge.com/Geographic-Data-Science-with-Python/Rey-Arribas-Bel-Wolf/p/book/9781032445953</a></p>
</blockquote>Dani Arribas-BelToday is the big day. In 2018 (!), we started conversations to turn learning resources we had been developing for a while into a paper copy book you could buy if you wanted, and always use for free on the web. CRC agreed and, in 2019, our contract was signed. Initially planned to be finnished much earlier, the world had different plans for us all… As we say in Spain, late is better than never. As our CRC agent let us know this morning, the book is officially published worldwide:CARTO Spatial Data Science Bootcamp2023-02-23T00:00:00+00:002023-02-23T00:00:00+00:00https://geographicdata.science/talk/2023/02/23/carto_bootcamp<p>On February 23rd’23, Levi and Dani participated at CARTO’s first <a href="https://www.eventbrite.co.uk/e/spatial-data-science-bootcamp-london-2023-tickets-464290293767">Spatial Data Science bootcamp</a> in London. This was a one-day training event with many sessions on everything from CARTO’s latest offerings to sessions on more foundational topics. Levi and Dani delivered a session that remixed Chapters 6 and 7 into one session on spatial autocorrelation. For his part, Dani used an annotated version of the book that you can find at:</p>
<blockquote>
<p><a href="https://geographicdata.science/book_annotated/notebooks/06_spatial_autocorrelation.html">https://geographicdata.science/book_annotated/notebooks/06_spatial_autocorrelation.html</a></p>
</blockquote>
<p>Levi instead took a live approach and freestyled an amazing explanation of
local indicators of spatial autocorrelation on his iPad.</p>
<p>It was a blast to participate and we look forward to future editions!</p>Dani Arribas-BelOn February 23rd’23, Levi and Dani participated at CARTO’s first Spatial Data Science bootcamp in London. This was a one-day training event with many sessions on everything from CARTO’s latest offerings to sessions on more foundational topics. Levi and Dani delivered a session that remixed Chapters 6 and 7 into one session on spatial autocorrelation. For his part, Dani used an annotated version of the book that you can find at:Regression and Spatial Feature Engineering chapters talks2022-05-03T00:00:00+00:002022-05-03T00:00:00+00:00https://geographicdata.science/talk/2022/05/03/chicago<p>On May 5th, Dani and friend of the book <a href="https://sites.google.com/site/pedroamaralen/about">Pedro Amaral</a> ran a session on embedding space in (regression) models at the University of Chicago’s Spatial Data Science Center (see original anouncement <a href="2022-04-27-chicago">here</a>). The folks at SDSC have kindly posted the talks on their YouTube channels and you can check them out now!</p>
<h2 id="spatial-regression-ch-11">Spatial regression (Ch. 11)</h2>
<iframe width="560" height="315" src="https://www.youtube.com/embed/0zi8D7Il18g" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>
<h2 id="spatial-feature-engineering-ch-12">Spatial Feature Engineering (Ch. 12)</h2>
<iframe width="560" height="315" src="https://www.youtube.com/embed/I-CAKCW8Wv0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>Dani Arribas-BelOn May 5th, Dani and friend of the book Pedro Amaral ran a session on embedding space in (regression) models at the University of Chicago’s Spatial Data Science Center (see original anouncement here). The folks at SDSC have kindly posted the talks on their YouTube channels and you can check them out now!Super-Charging your (Regression) Model with Space and Geography2022-04-27T00:00:00+00:002022-04-27T00:00:00+00:00https://geographicdata.science/talk/2022/04/27/chicago<p>On May 5th, Dani and friend of the book <a href="https://sites.google.com/site/pedroamaralen/about">Pedro Amaral</a> will run a session on embedding space in (regression) models.</p>
<p><img src="https://pbs.twimg.com/media/FRRhM4CXoAMw4ZK?format=png&name=small" alt="" /></p>
<p>The session will be based on the “Geographic Data Science with Python” book
and will discuss mainly two of its chapters: <a href="https://geographicdata.science/book/notebooks/11_regression.html">Chapter 11, Spatial
Regression</a>, and <a href="https://geographicdata.science/book/notebooks/12_feature_engineering.html">Chapter 12, Spatial Feature Engineering</a>. You can tag along just to listen or, if you want, you can also follow along running the code on your own machine. Thanks to <a href="https://mybinder.org/">Binder</a>, this is a click away on your browser!</p>
<p><strong>BONUS</strong> – The session will be <em>hybrid</em>, so you can join remotely.</p>
<p>Here’re the coordinates of the event:</p>
<p><img src="https://pbs.twimg.com/media/FRRkeQrWUAIMbfe?format=png&name=900x900" alt="" /></p>
<p>And more information is available <a href="https://spatial.uchicago.edu/content/csds-study-group-presentations-2022#pysal">here</a> on the SDS’s website.</p>Dani Arribas-BelOn May 5th, Dani and friend of the book Pedro Amaral will run a session on embedding space in (regression) models.Community call: give us your best bug!2022-04-19T00:00:00+00:002022-04-19T00:00:00+00:00https://geographicdata.science/announcement/2022/04/19/community_call<p>It’s been a few months and, arguably, a few (pandemic) bumps along the road since
<a href="/authors">we</a> <a href="https://geographicdata.science/2019/08/24/hello-world.html">announced</a> this project back
in August’19. The <strong>good news</strong> is we’re almost done! We have submitted a first full
draft to CRC and are putting the very final touches before sending over to production.</p>
<p>The <strong>even better news</strong> is you can still help us make this book a more awesome and neatly
crafted one. Now the bulk of our writing is done, we need as many eyes as we can muster to
squash perky typos, catch any error we may have made, and make the book read as clearly as
possible for someone who’s not spent a substantial amount of intimate time among its pages
over the last three years. We are putting out a community call to see if we can get a hand
from folks.</p>
<p>Here’s how you can help. <em>Geographic Data Science with Python</em> has been open for you to read, study, and run since <a href="https://geographicdata.science/2019/08/29/project-launch.html">Day 1</a>. That means our entire process of writing, deliberation, and progress has been out for everyone to see. This has not been the most useful for most people, beyond a few curious minds who enjoy seeing things coming into being. But now that the project is starting to look more and more like a full book, maybe you want to take a look. Maybe you want to read through some of its chapters. Or maybe you even want to try running its code (all fully <a href="https://geographicdata.science/infrastructure/2021/03/24/ci.html">tested</a> and reproducible!), either on <a href="https://mybinder.org/v2/gh/gdsbook/book/master?urlpath=lab/tree/notebooks/00_toc.ipynb">Binder</a> with no install required, or on your own laptop. In any case, we would love it if <strong>you could report any bug, typo, or comment you have about the book</strong>.</p>
<p>How can you report anything on the book? Very simple. Please open an issue on Github:</p>
<blockquote>
<p><a href="https://github.com/gdsbook/book/issues/new">https://github.com/gdsbook/book/issues/new</a></p>
</blockquote>
<p>You will need a Github account, which you can set up for free in a couple of minutes. If you don’t have an account and don’t want to set one up but would like to report, you can contact either of <a href="/authors">us</a> directly and we’ll report it for you.</p>
<p>We are thrilled about getting the full book out in the wild for you to enjoy. We are almost there. We only need a final push, and a little bit of help from you :-)</p>
<p>Happy hacking,</p>
<p>Serge, Dani & Levi</p>Dani Arribas-BelIt’s been a few months and, arguably, a few (pandemic) bumps along the road since we announced this project back in August’19. The good news is we’re almost done! We have submitted a first full draft to CRC and are putting the very final touches before sending over to production.Talk at the International Conference on Geospatial Information Sciences2021-11-04T00:00:00+00:002021-11-04T00:00:00+00:00https://geographicdata.science/talk/2021/11/04/igisc<p>On November 4th., Dani delivered one of the (online) keynote addresses at the <a href="https://igisc.org/">International Conference on Geospatial Information Sciences</a>, greatly organised by <a href="https://www.centrogeo.org.mx/">CentroGeo</a> in Mexico. His talk provided an overview of the process and philosophy behind writing “Geographic Data Science with Python” with Levi and Serge.</p>
<p>The video of the talk is available on <a href="https://youtu.be/vTsfBZyS-8E?t=13875">Youtube</a>:</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/vTsfBZyS-8E?start=13875" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>
<p>And the slides are also available as <a href="http://darribas.org/gdsbook_overview/202111_cg/index.html"><code class="language-plaintext highlighter-rouge">HTML</code></a> and <a href="http://darribas.org/gdsbook_overview/202111_cg/index.pdf"><code class="language-plaintext highlighter-rouge">PDF</code></a>.</p>Dani Arribas-BelOn November 4th., Dani delivered one of the (online) keynote addresses at the International Conference on Geospatial Information Sciences, greatly organised by CentroGeo in Mexico. His talk provided an overview of the process and philosophy behind writing “Geographic Data Science with Python” with Levi and Serge.Talk at the Geoinformation Science Symposium2021-10-28T00:00:00+00:002021-10-28T00:00:00+00:00https://geographicdata.science/talk/2021/10/28/gss<p>On October 26th., Dani delivered one of the (online) keynote addresses at the <a href="https://gss.geo.ugm.ac.id/gss-2021/">7th Geoinformation Science Symposium</a>, based in Indonesia. His talk provided an overview of the process and philosophy behind writing “Geographic Data Science with Python” with Levi and Serge.</p>
<p>The video of the talk is available on <a href="https://youtu.be/7ymkQKp_RL4?t=410">Youtube</a>:</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/7ymkQKp_RL4?start=410" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>
<p>And the slides are also available as <a href="http://darribas.org/gdsbook_overview/202110_gss/index.html"><code class="language-plaintext highlighter-rouge">HTML</code></a> and <a href="http://darribas.org/gdsbook_overview/202110_gss/index.pdf"><code class="language-plaintext highlighter-rouge">PDF</code></a>.</p>Dani Arribas-BelOn October 26th., Dani delivered one of the (online) keynote addresses at the 7th Geoinformation Science Symposium, based in Indonesia. His talk provided an overview of the process and philosophy behind writing “Geographic Data Science with Python” with Levi and Serge.Code as text… and text as code2021-03-24T00:00:00+00:002021-03-24T00:00:00+00:00https://geographicdata.science/infrastructure/2021/03/24/ci<p>With the merge of <a href="https://github.com/gdsbook/book/commit/90e3e32e078a06a5546be9dbc224c0dacec62e6c"><code class="language-plaintext highlighter-rouge">PR#149</code></a>, we turned on continuous integration (CI) for the book. This means that, everytime we commit something to the main branch of the book repository, a little robot at Github sets up a full environment and runs the book entirely to ensure all the code runs without glitches. This is common practice in modern software engineering, and we are excited about adopting it for book writing.</p>
<p>Besides providing an additional check to make sure we keep our book up to date and working as expected, the adoption of CI implies one step further in the philosophy we are trying to live by in this project. We have long been of the opinion that, for Geographic Data Science, code represents a medium of comunication and a vehicle for teaching. Code is (almost) like text when it comes to teaching computational concepts. By adopting CI for the book open repository, we’re also implying the oposite (text as code) also holds true: we treat the book as an artifact that contains software and that, as such, we believe needs to follow similar practices.</p>
<p>If you want to check how the last run went, click on the badge:</p>
<p><a href="https://github.com/gdsbook/book/actions/workflows/test_book.yml"><img src="https://github.com/gdsbook/book/actions/workflows/test_book.yml/badge.svg" alt="Test Book" /></a></p>
<p>We should also mention the “tester” is the second, not the first, robot we
welcome to the GDS Book family. For a <a href="https://github.com/gdsbook/book/commit/3705ed45eed715129459307765a93667a554263e">long(er) time</a>, we have had a different one that automatically re-builds the website that hosts the book whenever we make a new change. For the list of builds of this bot, click on the badge below:</p>
<p><a href="https://github.com/gdsbook/book/actions/workflows/build_website.yml"><img src="https://github.com/gdsbook/book/actions/workflows/build_website.yml/badge.svg" alt="Build Jupyter book" /></a></p>
<h2 id="tech-epilogue">Tech epilogue</h2>
<p>If you are interested in the backend and various wirings we do to create and
operate both bots, here’s a short overview.</p>
<p>We use <a href="https://github.com/features/actions">Github Actions</a>, which allows us
to trigger actions on every commit. We have two of these “actions” specified,
one for the test bot, one for the build bot. The specs of each are specified
on a separate <code class="language-plaintext highlighter-rouge">.yml</code> file that lives under the <a href="https://github.com/gdsbook/book/tree/master/.github/workflows"><code class="language-plaintext highlighter-rouge">gdsbook/.gihub/workflows</code></a>
directory of the book repository.</p>
<p>To <a href="https://github.com/gdsbook/book/blob/master/.github/workflows/test_book.yml">test the book</a> on Windows/Linux/macOS, we set up a conda environment that mirrors the <a href="https://darribas.org/gds_env">GDS env</a> (<code class="language-plaintext highlighter-rouge">6.0post1</code> at the time of writing, but we plan to keep this in sync with the latest version), and the use <code class="language-plaintext highlighter-rouge">make test</code>, a comand that uses the <a href="https://github.com/gdsbook/book/blob/master/Makefile">Makefile</a> in the repository, to execute every chapter in the book. This is a lightweight approach that allows us to use the same workflow when we’re testing the book locally on our own machines and when it runs on Github’s cloud.</p>
<p>The infrastructure to <a href="https://github.com/gdsbook/book/blob/master/.github/workflows/build_website.yml">build the website</a> is a bit more lightweight in that we only really need <code class="language-plaintext highlighter-rouge">jupyterbook</code> and affiliated dependencies to be able to create an updated version of the website from the notebook files. We use a small <a href="https://github.com/gdsbook/book/blob/master/infrastructure/ga_environment.yml"><code class="language-plaintext highlighter-rouge">.yml</code> file</a> to set up such environment.</p>Dani Arribas-BelWith the merge of PR#149, we turned on continuous integration (CI) for the book. This means that, everytime we commit something to the main branch of the book repository, a little robot at Github sets up a full environment and runs the book entirely to ensure all the code runs without glitches. This is common practice in modern software engineering, and we are excited about adopting it for book writing. Besides providing an additional check to make sure we keep our book up to date and working as expected, the adoption of CI implies one step further in the philosophy we are trying to live by in this project. We have long been of the opinion that, for Geographic Data Science, code represents a medium of comunication and a vehicle for teaching. Code is (almost) like text when it comes to teaching computational concepts. By adopting CI for the book open repository, we’re also implying the oposite (text as code) also holds true: we treat the book as an artifact that contains software and that, as such, we believe needs to follow similar practices. If you want to check how the last run went, click on the badge: We should also mention the “tester” is the second, not the first, robot we welcome to the GDS Book family. For a long(er) time, we have had a different one that automatically re-builds the website that hosts the book whenever we make a new change. For the list of builds of this bot, click on the badge below: Tech epilogue If you are interested in the backend and various wirings we do to create and operate both bots, here’s a short overview. We use Github Actions, which allows us to trigger actions on every commit. We have two of these “actions” specified, one for the test bot, one for the build bot. The specs of each are specified on a separate .yml file that lives under the gdsbook/.gihub/workflows directory of the book repository. To test the book on Windows/Linux/macOS, we set up a conda environment that mirrors the GDS env (6.0post1 at the time of writing, but we plan to keep this in sync with the latest version), and the use make test, a comand that uses the Makefile in the repository, to execute every chapter in the book. This is a lightweight approach that allows us to use the same workflow when we’re testing the book locally on our own machines and when it runs on Github’s cloud. The infrastructure to build the website is a bit more lightweight in that we only really need jupyterbook and affiliated dependencies to be able to create an updated version of the website from the notebook files. We use a small .yml file to set up such environment.Spanish overview of Geographic Data Science…2020-11-24T00:00:00+00:002020-11-24T00:00:00+00:00https://geographicdata.science/talk/2020/11/24/udsa<p>Last week, Dani gave an overview of the book (in Spanish) for the students of the MSc in Economics at the Universidad de San Andrés (UdeSA, BsAs, Argentina). A lightly edited version of the talk is available at:</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/K5wWn5ZOOZ0" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>
<p>And the slides can be found <a href="https://github.com/gdsbook/talks/blob/main/2020_udsa.pdf">here</a>.</p>Dani Arribas-BelLast week, Dani gave an overview of the book (in Spanish) for the students of the MSc in Economics at the Universidad de San Andrés (UdeSA, BsAs, Argentina). A lightly edited version of the talk is available at: