Charting software that pre-dates Excel

RJ Andrews digs up the PC archives of charting software. Scrolling through the thread, you can see the roots of Excel in the software that pre-dates the 1987 Windows release, along with what was considered nice back in the day. In many ways, such as in the interface, features, and chart types, things haven’t changed that much over the past few decades.

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R packages useful for sports analytics

If you’re into R and analyzing sports data, you’ll want to save this CRAN task view:

This CRAN Task View contains a list of packages useful for sports analytics. Most of the packages are sport-specific and are grouped as such. However, we also include a General section for packages that provide ancillary functionality relevant to sports analytics (e.g., team-themed color palettes), and a Modeling section for packages useful for statistical modeling. Throughout the task view, and collected in the Related links section at the end, we have included a list of selected books and articles that use some of these packages in substantive ways. Our goal in compiling this list is to help researchers find the tools they need to complete their work in R.

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Agent-based modeling in JavaScript

Atomic Agents is a JavaScript library by Graham McNeill that can help simulate the interactions between people, places, and things in a two-dimensional space. Saving for later. Looks fun.

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Ross Ihaka, co-creator of R, reflects on the language

NZ Herald talked to Ross Ihaka, one of the creators of R:

Today, R is depended upon around the world by analysts, data scientists and big-name companies like Facebook, Google, Amazon and the New York Times, and it’s garnered Ihaka something of a rockstar status in the field of data science and statistics.

He’s received numerous accolades over the years recognising his work, such as the Royal Society of New Zealand’s prestigious Pickering Medal, and the Statistical Computing and Graphics Award from the American Statistical Association.

Asked how many people use R on a daily basis, Ihaka’s guess is in the millions but he’s not quite sure how many million.

One of the reasons R is called R is because Ihaka and co-creator Robert Gentleman both had first names that started with the letter.

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Colors for All, R package

If you use color as a visual encoding, you should make sure every one can actually see the differences in your scale. The cols4All package from Martijn Tennekes can help by ranking and categorizing a wide set of color schemes.

Color palettes are well organized and made consistent with each other. Moreover, they are scored on several aspects: color-blind-friendliness, the presence of intense colors (which should be avoided), the overall aesthetic harmony, and how many different hues are used. Finally, for each color palette a color for missing values is assigned, which is especially important for spatial data visualization. Currently we support three types: categorical (qualitative) palettes, sequential palettes, and diverging palettes. In the near future, more palette types will be added, such as cyclic, bivariate, and hierarchical.

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SVG pattern repository

For when you want to fill SVG polygons with patterns instead of or in combination with color, Thomas Michael Semmler has a copy-and-paste collection. It’s just the basics, but it’s a convenient reference that could provide a starting point at the least.

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Generative art with R

Generative art seems to be having a moment right now, so it’s only appropriate that there’s an R package to help you make some. The aRtsy package by Koen Derks makes algorithms more straightforward to use. Set parameters and you’re off.

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Value of R, the Statistics-specific language

Paul Ford has been learning R to better understand the field of Statistics. The takeaway:

Deep in its heart, R is a language for making charts, and it’s genuinely fun to go into its world: statistics, natural sciences, sociology — all right there. You will never pry me away from JavaScript or Python or the whole web stack of standards and protocols. They’re how I make things happen in the world, and they are very much my home base, but using more specific tools is always an education. It’s like suddenly discovering a new wing of a big museum, and realizing that there’s still a lot to learn.

I would say it’s a language for analyzing data, and charts are a big part of the process. But the big sell of R has always been its specificity. The need to understand data drives its design and growth, which means you avoid starting a lot of analyses from scratch.

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Spatula, a Python library for maintainable web scraping

This looks promising:

While it is often easy, and tempting, to write a scraper as a dirty one-off script, spatula makes an attempt to provide an easy framework that most scrapers fit within without additional overhead.

This reflects the reality that many scraper projects start small but grow quickly, so reaching for a heavyweight tool from the start often does not seem practical.

The initial overhead imposed by the framework should be as light as possible, providing benefits even for authors that do not wish to use every feature available to them.

Although, without my dirty one-off scripts, what will I put in my tmp data folder?

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Observable Plot, a JavaScript library for more straightforward visualization of tabular data

If you’re into the notebook workflow, Observable Plot is a JavaScript library built for you:

We created Plot to better support exploratory data analysis in reactive, JavaScript notebooks like Observable. We continue to support D3 for bespoke explanatory visualization and recommend Vega-Lite for imperative, polyglot environments such as Jupyter. Plot lets you see your ideas quickly, supports interaction with minimal fuss, is flexible with respect to data, and can be readily extended by the community. We believe people will be more successful finding and sharing insight if there’s less wrestling with the intricacies of programming and more “using vision to think.”

In case you’re curious how Plot compares to D3, which was used to build Plot, you can find that information here.

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