Birding and data visualization

Jer Thorp has combined birding and data visualization into a unique course called Binoculars to Binomials:

I dreamt up Binoculars to Binomials as a hybrid site of learning. It’s for coders who are interested in cultivating an observational practice, and for birders who want to dive into the rich pool of data that comes out of their hobby.

More broadly, it’s for anyone who’s interested in the overlap between nature, data and creativity.

Sounds good to me.

One of the best ways to learn how to visualize data is to apply it to a specific field. You figure out the mechanics and the context behind the data, which makes visualization meaningful and useful. In this case, you get your hands in all parts of the process.

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Steps for getting started with data visualization

Getting started with data visualization can be tricky because of all the resources and tools available these days. Approaches also change with what you want to visualize data for. For Datawrapper, Lisa Chartlotte Muth outlines how to take your first steps.

The main theme is to make more charts.

See also: getting started with visualization after getting started with visualization.

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Introduction to statistical learning, with Python examples

An Introduction to Statistical Learning, with Applications in R by Gareth James, Daniela Witten, Trevor Hastie, and Rob Tibshirani was released in 2021. They, along with Jonathan Taylor, just released an alternate version with applications in Python. So if Python is your thing, have at it. Like the R version, it is free to download as a PDF.

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✚ Unrestricted Visualization

Welcome to issue #205 of The Process, the newsletter for FlowingData members that looks closer at how the charts get made. I’m Nathan Yau, and I come to you from a dark room in California, where I’ve turned off almost everything, in the hopes there are no more rolling blackouts during these record-setting days of high heat. This week, I’m looking back at how I got started with FlowingData and visualization, because I guess that’s what I tend to do when I’m in the dark and it’s hot outside.

Become a member for access to this — plus tutorials, courses, and guides.

Introduction to statistical learning

An Introduction to Statistical Learning, by Gareth James, Daniela Witten, Trevor Hastie, and Rob Tibshirani:

As the scale and scope of data collection continue to increase across virtually all fields, statistical learning has become a critical toolkit for anyone who wishes to understand data. An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning. Each chapter includes an R lab. This book is appropriate for anyone who wishes to use contemporary tools for data analysis.

The PDF version of the book is free to download. There’s also a free online course companion.

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✚ For Your Own Approval – The Process 181

Welcome to issue #181 of The Process, the newsletter that looks closer at how the charts get made. I’m Nathan Yau, and this week I’m thinking that data visualization isn’t always for ultimate insights and actionability, and eventually you gotta make the charts for yourself.

Become a member for access to this — plus tutorials, courses, and guides.

✚ Foundational Visualization Skills – The Process 151

Welcome to issue #151 of The Process, the newsletter for FlowingData members about how the charts get made. I’m Nathan Yau, and this week I’m thinking about the foundational skills for visualization and how to develop them.

Become a member for access to this — plus tutorials, courses, and guides.

✚ Learning New Visualization Things Practically – The Process 149

Welcome to issue #149 of The Process, the newsletter for FlowingData members about how the charts get made. I’m Nathan Yau, and this week I’m thinking about how to learn as much as I can about new visualization things, but also get actual work done.

Become a member for access to this — plus tutorials, courses, and guides.

✚ Retired Minard – The Process 147

Welcome to issue #147 of The Process, the newsletter for FlowingData members about how the charts get made. I’m Nathan Yau, and this week I’m thinking about finite years, the long game, and learning visualization at an older age.

Become a member for access to this — plus tutorials, courses, and guides.

10 statistical lessons from the past pandemic year

The Royal Statistical Society published ten lessons governments should takeaway from this year, which should naturally apply to standard data practice:

  1. Invest in public health data – which should be regarded as critical national infrastructure and a full review of health data should be conducted 
  2. Publish evidence – all evidence considered by governments and their advisers must be published in a timely and accessible manner
  3. Be clear and open about data – government should invest in a central portal, from which the different sources of official data, analysis protocols and up-to-date results can be found
  4. Challenge the misuse of statistics – the Office for Statistics Regulation should have its funding augmented so it can better hold the government to account
  5. The media needs to step up its responsibilities – government should support media institutions that invest in specialist scientific and medical reporting
  6. Build decision makers’ statistical skills – politicians and senior officials should seek out statistical training
  7. Build an effective infectious disease surveillance system to monitor the spread of disease – the government should ensure that a real-time surveillance system is ready for future pandemics
  8. Increase scrutiny and openness for new diagnostic tests – similar steps to those adopted for vaccine and pharmaceutical evaluation should be followed for diagnostic tests
  9. Health data is incomplete without social care data – improving social care data should be a central part of any review of UK health data
  10. Evaluation should be put at the heart of policy – efficient evaluations or experiments should be incorporated into any intervention from the start.

See the full report here.

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