prettymaps VS owid-grapher

These maps look great! Reminds me of a project I saw a long time ago [1]. Glad you made this downloadable for everyone who cannot write code.

P.S.: Now, I also have some (birthday) presents ;-)

[1] https://github.com/marceloprates/prettymaps

You can generate them yourself from Open Street Maps. Use this Google Colab. Source - prettymaps.

Check out this repo

Check out Pretty Maps, or the online version, and /r/prettymaps_

Great work! I love osmnx, it's such a nice library. I remember using it at school to work out distance from fire stations across my city. There's this nice library that uses it called prettymaps, I've been meaning to take some time with it to do some sweet posters.

prettymaps – A small set of Python functions to draw pretty maps from OpenStreetMap data

That's actually the part about people constantly negging on social sciences [1] that I often find confusing.

There's huge amounts of data available (geography, lots and lots of maps; history, huge amount of historical documentation; economics, vast amounts of public datasets produced every month by most governments; political science, censuses, voting records, driver registrations, political contest results all over the Earth - often for decades if not centuries).

Most is relatively well verified, and often tells you how it was verified [2]. Often it's obtainable in publicly available datasets that numerous other researchers can verify was obtained from a legitimate source. [3]

There's lots of data available. Much is also verifiable in a very personal way simply by walking somewhere and looking. In many ways, social sciences should be one of the most rigorous disciplines in most of academia.

[1] Using Wikipedia's grouping on "social sciences" (anthropology, archaeology, economics, geography, history, linguistics, management, communication studies, psychology, culturology and political science): https://en.wikipedia.org/wiki/Social_science

[2] Census 2020, Data Quality: https://www.census.gov/programs-surveys/decennial-census/dec...

[3] Economic Indicators by Country: https://tradingeconomics.com/indicators

[4] Our World in Data (with Demographics, Health, Poverty, Education, Innovation, Community Wellbeing, Democracy): https://ourworldindata.org/

Population data by country over time was scraped from ourworldindata.org

> filled our heads with candied dreams of endlessly-spanning information super-highways

* https://www.wikipedia.org

* https://www.openstreetmap.org

* https://github.com

* https://data.gov

* https://fred.stlouisfed.org

* https://ourworldindata.org

* ...

Plus the countless documentation websites that we technical writers lovingly toil away at day-in and day-out.

Neat!

This is one of my favorite spaces, so I'll add some generic advice which may or may not be helpful.

I once had the privilege of working for Max Roser and Hannah Ritchie at Our World in Data, as one of the engineers on their Grapher library (https://github.com/owid/owid-grapher), and learned a ton from them (and others on the team) about making great charts.

My one piece of advice from looking at your examples would be: don't neglect title, subtitle, and caption! They would be so easy to do well because you've already created your "simple headers thingies". A few words go along way. Check out "Storytelling with Data" by Cole Nussbaumer Knaflic for a great read on the subject. Owid's Grapher does those the best, IMO (followed closely by DataWrapper.de -- but that's not open source).

At some point, if you keep up with this, you'll also want to add a dataflow library and DSL. Hadley Wickham's dplyr in R was the GOAT, and I copied that in my Ohayo tool and in OWID Grapher's CoreTable library (https://github.com/owid/owid-grapher/tree/master/packages/%4...). Jeffrey Heer's newish Arquero (https://idl.uw.edu/arquero/) library is also along those lines.

Lately I've delving into Mike Bostock's new thing Plot (https://observablehq.com/plot/). So far, excited by it, but only spent a day or two with it at this point.

I don't use emacs anymore, but hopefully something helpful in the comments above.

https://ourworldindata.org/

I reach for it several times per week. Never struggle finding what I want, nor getting it into the shape I want it.

Let’s begin with a data visualization-friendly resource.

Here's a dashboard: https://ourworldindata.org/

Pick almost anything to see a positive trend.

I think the idea of Framework is really good, but static data limits the applications, excluding monitoring and other cases in which the data is constantly changing, but the dashboard can stay as it is. For example, I'd love to see a revamped Framework version of the LHC beam monitor and related pages (see https://op-webtools.web.cern.ch/vistar/, but check again in 2 months or so, when the accelerator will be running).

In high-energy physics, ROOT is /the/ toolkit for data analysis, and I guess jsROOT (https://root.cern.ch/js/) could also be used to load data to be shown in Framework dashboards. I thought the idea of Framework as a blogging engine with powerful data visualization built-in could be very interesting. Think, for example, about physicists pulling open data (https://opendata.cern.ch) and writing about their analysis or someone pulling data from https://ourworldindata.org/ in their own visualizations to support their case while writing about a particular subject, etc.

This is patently false. Visit ourworldindata.org and look at the data for the past few hundred years. 17th-century English philosopher Thomas Hobbes famously wrote the "the life of man [is] solitary, poor, nasty, brutish, and short," which was largely accurate in the 17th century. Today, the poorest people in developed nations enjoy a standard of living that royalty of Hobbes time would have envied. And while the percentage of humanity living in extreme poverty increased from 8.5% to just above 9% in 2022, overall it's down from 80% in the year 1800. We have made similar strides in the areas of education and healthcare.