Data Curious 16501.2019 - And we're back 📈 2019
15.01.2019
Have you gotten used to writing "2019" yet? Me neither.
I'm not one for resolutions, but if I had one this year, it would be to continue this weekly newsletter and to keep adding helpful features. Have an idea of something you'd like to see added? Drop me a note.
Now back to the usual stuff: the best articles to read, visualizations to explore, datasets to analyze and tutorials to learn this week.
Read_
Planning data projects and saving democracy with data viz
How do I plan a data project from start to finish?
Here's a 7-step process that I found helpful as a starting point.
Start with a plan →
How can we save democracy through data visualization?
Teach kids how to read charts. This piece from Quartz explores recent studies and tools for visualization literacy, with a focus on how it impacts the democratic process.
Explore_
Weird charts and a meta 2018 list of inspiration
How can I add some variety to the charts I produce?
Browse the 45 best and weirdest charts from FiveThirtyEight in 2018 for inspiration.
Let's get weird →
What are some of the best data visualization moments I may have missed last year?
Maarten Lambrechts published the best of the best, a meta "lists of lists" if you will. All the 2018 recaps from the biggest names in data viz.
Analyse_
Top 10 of 2018 and a dataset of breweries
What datasets should I use for my new project?
This "top 10 datasets of 2018" list from data.world isn't a bad place to start.
Hooray for end-of-year-lists →
Where should I celebrate the end of dry January?
If you're doing that sort of thing, try analysing this Kaggle dataset of breweries and brewpubs in the U.S.
Learn_
Jupyter Notebook power-ups, quick data merging, and publishing charts with Flask
How do I add more features to my Jupyter Notebook?
Widgets, shortcuts, custom embeds, new layouts. Jupyter Notebook has a few tricks up its sleeve.
How do I quickly merge datasets without any code?
Sometimes you just want something done fast, no code required. Try this new tool for merging json, csv, geojson and topojson files.
How can I publish charts from my analysis online without writing different code?
You can do it all in Python with this Matplotlib + Flask API combo.
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Thanks for reading. More to come next week.
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