Let me tell you about something.

Distractions and amusements, with a sandwich and coffee.

Poetry is just the evidence of life. If your life is burning well, poetry is just the ash
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Typography geek? If you like the geometry and mathematics of these posters, you may enjoy something more lettered. Visions of type: Type Peep Show: The Private Curves of Letters posters.

numbers.tgz

1,000,000 digits of π, φ, e and ASN.

Watch the video at Numberphile about my art.

Explore Pi Day art for 2014.

All the artwork can be purchased from Fine Art America.

Proclus got it right when he said (as quoted by M. Kline in *Mathematical Thought from Ancient to Modern Times*)

Wherever there is number, there is beauty.

So let's explore what Pi looks like with something whimsical and pretty and colourful. Rational art of the highly irrational, a regime where beauty runs with her hair down and lets her "*ribbons to flow confusedly.*" Robert Herrick says it well in Sweet Disorder,

I see a wild civility;—

Do more bewitch me, than when art

Is too precise in every part.

The posters explore the relationship between adjacent digits in Pi, which are encoded by color using the scheme shown above. The design appears to shimmer due to the luminance effect. In some versions of the poster, adjacent identical (or similar) digits are connected by lines.

Want more math + art? Discover the Accidental Similarity Number and other number art. Find humor in my poster of the first 2,000 4s of Pi.

The recipe for each poster is included and gives the color of the *i*th outer/inner circle. π[i] is used to represent the *i*th digit of π. For example, the recipe

π[i] / π[i+1]

generates a poster whose outer circle color encodes the *i*th digit and the inner circle color encodes the next digit (*i*+1). In this scheme, inner and outer circles of adjacent positions have the same color.

The posters were generated automatically with a Perl script that generated SVG files. Post processing and layout was done in Illustrator. If you are interested in depicting your favourite number this way, let me know.

The design was inspired by the beautiful AIDS posters by Elena Miska.

I calculated Pi to 13,099,586 digits and then I found love.

It's fun to look for words in Pi. I wanted to know the first time that *love* appears in Pi. When encoded using the scheme a=0, b=1, ..., z=25, *love* is the digit 1114214. This digit appears first at position 13,099,586 (...8921991631**1114214**8187311392...). And, of course, infinitely many times after that.

If you use the scheme a=1, b=2, ..., z=26, then *love* becomes 1215225. This is first seen at 6,317,696 (...6103119129**1215225**6606850141...).

Because the digits of Pi never repeat and are distributed randomly (as far as we know), if you look long enough you'll find all the words in Pi infinitely many times.

π[i] / grey, 80% opacity

π[i] / π[i+1], 80% opacity

π[i] / grey, 80% opacity (equal neighbours connected)

π[i] / π[i+1], 80% opacity (equal neighbours connected)

— / π[i+1] (equal neighbours connected, unconnected digits not shown)

π[i] / π[i+1] (equal neighbours connected with line width proportional to difference in neighbour digits *d*∈{0,1,2}, unconnected digits not shown)

π[i] / π[i+1] (equal neighbours connected with line width proportional to difference in neighbour digits *d*∈{0..5}, unconnected digits not shown)

Pi (π): — / red (equal neighbours connected, unconnected digits not shown)

Phi (φ): — / white (equal neighbours connected, unconnected digits not shown)

e: — / grey (equal neighbours connected, unconnected digits not shown)

π[i] / grey, 80% opacity (equal neighbours connected)

π[i] / π[i+1], 80% opacity (equal neighbours connected)

π[i] / π[i+1] &>

π[i] / grey, 80% opacity (equal neighbours connected, unconnected digits not shown)

π[i] / π[i+1], 80% opacity (equal neighbours connected, unconnected digits not shown)

In the April Points of Significance Nature Methods column, we continue our and consider what happens when we run a large number of tests.

Observing statistically rare test outcomes is expected if we run enough tests. These are statistically, not biologically, significant. For example, if we run *N* tests, the smallest *P* value that we have a 50% chance of observing is 1–exp(–ln2/*N*). For *N* = 10^{k} this *P* value is *P*_{k}=10^{–k}ln2 (e.g. for 10^{4}=10,000 tests, *P*_{4}=6.9×10^{–5}).

We discuss common correction schemes such as Bonferroni, Holm, Benjamini & Hochberg and Storey's *q* and show how they impact the false positive rate (FPR), false discovery rate (FDR) and power of a batch of tests.

Krzywinski, M. & Altman, N. (2014) Points of Significance: Comparing Samples — Part II — Multiple Testing *Nature Methods* **11**:215-216.

Krzywinski, M. & Altman, N. (2014) Points of Significance: Comparing Samples — Part I — *t*-tests *Nature Methods* **11**:215-216.

Krzywinski, M. & Altman, N. (2013) Points of Significance: Significance, *P* values and *t*-tests *Nature Methods* **10**:1041-1042.

Celebrate Pi Day (March 14th) with the art of folding numbers. This year I take the number up to the Feynman Point and apply a protein folding algorithm to render it as a path.

For those of you who liked the minimalist and colorful digit grid, I've expanded on the concept to show stacked ring plots of frequency distributions.

And if spirals are your thing...

In the March Points of Significance Nature Methods column, we continue our discussion of *t*-tests from November (Significance, *P* values and *t*-tests).

We look at what happens how uncertainty of two variables combines and how this impacts the increased uncertainty when two samples are compared and highlight the differences between the two-sample and paired *t*-tests.

When performing any statistical test, it's important to understand and satisfy its requirements. The *t*-test is very robust with respect to some of its assumptions, but not others. We explore which.

Krzywinski, M. & Altman, N. (2014) Points of Significance: Comparing Samples — Part I *Nature Methods* **11**:215-216.

Krzywinski, M. & Altman, N. (2013) Points of Significance: Significance, *P* values and *t*-tests *Nature Methods* **10**:1041-1042.

Beautiful Science explores how our understanding of ourselves and our planet has evolved alongside our ability to represent, graph and map the mass data of the time. The exhibit runs 20 February — 26 May 2014 and is free to the public. There is a good Nature blog writeup about it, a piece in The Guardian, and a great video that explains the the exhibit narrated by Johanna Kieniewicz, the curator.

I am privileged to contribute an information graphic to the exhibit in the Tree of Life section. The piece shows how sequence similarity varies across species as a function of evolutionary distance. The installation is a set of 6 30x30 cm backlit panels. They look terrific.

Quick, name three chart types. Line, bar and scatter come to mind. Perhaps you said pie too—tsk tsk. Nobody ever thinks of the box plot.

Box plots reveal details about data without overloading a figure with a full frequency distribution histogram. They're easy to compare and now easy to make with BoxPlotR (try it). In our fifth Points of Significance column, we take a break from the theory to explain this plot type and—I hope— convince you that they're worth thinking about.

The February issue of Nature Methods kicks the bar chart two more times: Dan Evanko's Kick the Bar Chart Habit editorial and a Points of View: Bar charts and box plots column by Mark Streit and Nils Gehlenborg.

Krzywinski, M. & Altman, N. (2014) Points of Significance: Visualizing samples with box plots *Nature Methods* **11**:119-120.

I recently presented at the Wired Data|Life 2013 conference, sharing my thoughts on The Art and Science of Data Visualization.

For specialists, visualizations should expose detail to allow for exploration and inspiration. For enthusiasts, they should provide context, integrate facts and inform. For the layperson, they should capture the essence of the topic, narrate a story and deligt.

Wired's Brandon Keim wrote up a short article about me and some of my work—Circle of Life: The Beautiful New Way to Visualize Biological Data.