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Distractions and amusements, with a sandwich and coffee.

In your hiding, you're alone. Kept your treasures with my bones.
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This section contains various art work based on `\pi`, `\phi` and `e` that I created over the years.

Some of the numerical art reveals interesting and unexpected observations. For example, the sequence 999999 in π at digit 762 called the Feynman Point. Or that if you calculate π to 13,099,586 digits you will find love.

`\pi` day art and `\pi` approximation day art is kept separate.

For some time I have been thinking about creating minimalist typographical art based on the digits of `\pi`. The `i`-ness `\pi` project was one of my first forays into this kind of art.

The `i`-ness is defined for each digit in `\pi`. It measures how close the digit is to its neighbouring digits, arithmetically.

I also show the `i`-ness of `phi` (Golden ratio) and `e` (natural logarithm base) in the poster section, as well as some humorous variants.

Similar to the `h` index in publishing, the `k` index is a measure of fitness performance.

To achieve a `k` index for a movement you must perform `k` unbroken reps at `k`% 1RM.

The expected value for the `k` index is probably somewhere in the range of `k = 26` to `k=35`, with higher values progressively more difficult to achieve.

In my `k` index introduction article I provide detailed explanation, rep scheme table and WOD example.

I've applied the char-rnn recurrent neural network to generate new words, names of drugs and countries.

The effect is intriguing and facetious—yes, those are real words.

But these are not: *necronology*, *abobionalism*, *gabdologist*, and *nonerify*.

These places only exist in the mind: *Conchar and Pobacia*, *Hzuuland*, *New Kain*, *Rabibus and Megee Islands*, *Sentip and Sitina*, *Sinistan* and Urzenia.

And these are the imaginary afflictions of the imagination: *ictophobia*, *myconomascophobia*, and *talmatomania*.

And these, of the body: *ophalosis*, *icabulosis*, *mediatopathy* and *bellotalgia*.

Want to name your baby? Or someone else's baby? Try *Ginavietta Xilly Anganelel* or *Ferandulde Hommanloco Kictortick*.

When taking new therapeutics, never mix *salivac* and *labromine*. And don't forget that *abadarone* is best taken on an empty stomach.

And nothing increases the chance of getting that grant funded than proposing the study of a new –ome! We really need someone to looking into the *femome* and *manome*.

An exploration of things that are missing in the human genome. The nullomers.

Julia Herold, Stefan Kurtz and Robert Giegerich. Efficient computation of absent words in genomic sequences. *BMC Bioinformatics* (2008) **9**:167

We've already seen how data can be grouped into classes in our series on classifiers. In this column, we look at how data can be grouped by similarity in an unsupervised way.

We look at two common clustering approaches: `k`-means and hierarchical clustering. All clustering methods share the same approach: they first calculate similarity and then use it to group objects into clusters. The details of the methods, and outputs, vary widely.

Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. *Nature Methods* **14**:545–546.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Logistic regression. *Nature Methods* **13**:541-542.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Classifier evaluation. *Nature Methods* **13**:603-604.

In this redesign of a pie chart figure from a Nature Medicine article [1], I look at how to organize and present a large number of categories.

I first discuss some of the benefits of a pie chart—there are few and specific—and its shortcomings—there are few but fundamental.

I then walk through the redesign process by showing how the tumor categories can be shown more clearly if they are first aggregated into a small number groups.

(bottom left) Figure 2b from Zehir et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. (2017) Nature Medicine doi:10.1038/nm.4333

After 30 columns, this is our first one without a single figure. Sometimes a table is all you need.

In this column, we discuss nominal categorical data, in which data points are assigned to categories in which there is no implied order. We introduce one-way and two-way tables and the `\chi^2` and Fisher's exact tests.

Altman, N. & Krzywinski, M. (2017) Points of Significance: Tabular data. *Nature Methods* **14**:329–330.