13.12.2018

We're reaching the end of the year and I'm finding myself deep in lots of "Best of 2018" type lists. One thing I love about the data viz community is how open it is — people share their work, as for feedback, encourage others to learn, and write openly about their mistakes. Most of the time.

This week I found lots of inspiration in beautiful stories from the year. Here we go.

Read_

Why data viz projects fail and the Type A data scientist

Why do so many data visualization projects fail?
Give me all the features. I am the only end user. You don't need the data yet. It has to be a Sunburst chart. The list goes on, in this very familiar feeling article by Ganes Kesari on Medium.

Commence the collective sigh →


Which type of Data Scientist should I be?
No, the all-in-one data science unicorn is probably not your best bet. In this article, Conor Dewey makes a sound argument for Type A. "While analysis and communication may not be as sexy as machine learning, the reality is that they offer the most consistent impact in industry."

Type A, Type B →

Explore_

Living on other planets, the land of London, and single-income families

How close are we to living on another planet?
The folks over at Interactive Things are digging through NASA data to find out. I love the design of this scrollable interactive story. So spacy.

Life on...Mars? Saturn? →


Who owns London?
No, this is not another Domesday Book visualization. The Mobility Space Report shows how much of London's urban areas are given to cars, rail networks and bicycles. I love watching the shapes fall into place over the satellite imagery. So satisfying.

I like shapes →

Is there a certain income threshold for single-income families?
Nathan Yau released another scrollable data story on FlowingData. This one uses D3.js + the Scrollama library from The Pudding for an excellent scrolling walkthrough of the data.

Income data incoming →

Analyse_

Boy bands and grant funding

What are the greatest boy band hits of all time?
Have you seen The Pudding's fantastic new story on Boy Bands? Well, story is a stretch: it's more of a nostalgiac, interactive audio tour. You can find all of the data they used in the story on their Github page below.

Take me there →


Which grants in the UK are receiving the most funding?
360Giving has a data portal called GrantNav. It allows you to search and download data for 300,000 grants in the UK.

To the grant data →

Learn_

Sharing data science work, spatial analysis with Python, and an intro to Tableau

How can I discover and share my recent data work?
Heard of Github? How about Observable notebooks? Meet Kyso, a new platform for collaborative and reproducible data science. The website allows you to upload JupyterLab notebooks into interactive blog posts and features. Currently in beta mode.

Cool! →

How can I get started with spatial analysis in Jupyter Notebooks?
Folium, a Python library for visualising data on top of Leaflet maps layers. I have mentioned it in previous editions, but this new write-up from Anthony Ivan is a perfect introduction (with some nice hidden methods to show geospatial over time as well).

Let's get mapping →

How can I start using Tableau for quick visualizations?
Maybe you've seen Tableau and thought: "Hey, that looks cool. I should probably learn to do that someday." Well you can. With this walkthrough on how to recreate the iconic Gapminder scatter plot from Hans Rosling.

Bubble plot time →

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Thanks for reading. More to come next week.

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