Stemgraphic v.0.5.x: stem-and-leaf EDA and visualization for numbers, categoricals and text

 Stemgraphic open source

In 2016 at PyDataCarolinas, I open-sourced my stem-and-leaf toolkit for exploratory data analysis and visualization. Later, in October 2016 I had posted the link to the video.

Stemgraphic.alpha

With the 0.5.x releases, I've introduced the categorical and text support. In the next few weeks, I'll be introducing some of the features, particularly those found in the new stemgraphic.alpha module of the stemgraphic package, such as back-to-back plots and stem-and-leaf heatmaps:

But if you want to get started, check out stemgraphic.org, and the github repo (especially the notebooks).

Github Repo

https://github.com/fdion/stemgraphic

Francois Dion
@f_dion

Readings in Communication

"Ex-Libris" part VI: Communication

Part 6 of my "ex-libris" of a Data Scientist is now available. This one is about communication.

When I started this series, I introduced this diagram.

I also quoted Johh Tukey:

"Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise" 

This is quite important since a data science project has to start with a question and come up with an answer.

But how do we communicate at the time of formulating the question? How about at the time of providing an answer? By any means necessary.

Do check out the full article with the list of books:

"ex-libris" part vi

See also

Part I was on "data and databases": "ex-libris" of a Data Scientist - Part i
Part II, was on "models": "ex-libris" of a Data Scientist - Part II
Part III, was on "technology": "ex-libris" of a Data Scientist - Part III
Part IV, was on "code": "ex-libris" of a Data Scientist - Part IV
Part V was on "visualization". Bonus after that will be on management / leadership.

Francois Dion
@f_dion

Readings in Visualization

"Ex-Libris" part V: Visualization

Part 5 of my "ex-libris" of a Data Scientist is now available. This one is about visualization.

Starting from a historical perspective, particularly of statistical visualization, and covering a few classic must have books, the article then goes on to cover graphic design, cartography, information architecture and design and concludes with many recent books on information visualization (specific Python and R books to create these were listed in part IV of this series). In all, about 66 books on the subject.

Just follow the link to the LinkedIn post to go directly to it:

"ex-libris of a data scientist, part V

From Jacques Bertin’s Semiology of Graphics

"Le plus court croquis m'en dit plus long qu'un long rapport", Napoleon Ier

See also

Part I was on "data and databases": "ex-libris" of a Data Scientist - Part i
Part II, was on "models": "ex-libris" of a Data Scientist - Part II
Part III, was on "technology": "ex-libris" of a Data Scientist - Part III
Part IV, was on "code": "ex-libris" of a Data Scientist - Part IV
Part VI will be on communication. Bonus after that will be on management / leadership.

Francois Dion
@f_dion

P.S.

Je vais aussi avoir une liste de publications en francais

En el futuro cercano voy a hacer una lista en espanol tambien

Readings in Programming

"Ex-Libris" part IV: Code

I've made available part 4 of my "ex-libris" of a Data Scientist. This one is about code. 

No doubt, many have been waiting for the list that is most related to Python.  In a recent poll by KDNuggets, the top tool used for analytics, data science and machine learning by respondents turned out to also be a programming language: Python.

The article goes from algorithms and theory, to approaches, to the top languages for data science, and more. In all, almost 80 books in just that part 4 alone. It can be found on LinkedIn:

"ex-libris" of a Data Scientist - Part IV

from Algorithms and Automatic Computing Machinesby B. A. Trakhtenbrot

See also

Part I was on "data and databases": "ex-libris" of a Data Scientist - Part i

Part II, was on "models": "ex-libris" of a Data Scientist - Part II


Part III, was on "technology": "ex-libris" of a Data Scientist - Part III

Part V will be on visualization, part VI on communication. Bonus after that will be on management / leadership.

Francois Dion
@f_dion

P.S.

Je vais aussi avoir une liste de publications en francais

En el futuro cercano voy a hacer una lista en espanol tambien

Readings in Technology

"Ex-Libris" part III

I've made available part 3 of my "ex-libris" of a Data Scientist. This one is on Technology, from some historical perspective (ie. Turing, Shannon, Von Neuman) all the way to the most recent trends (ie. Ansible, Docker, Cloud, Continuous Integration, Performance etc) and can be found on LinkedIn:

"ex-libris" of a Data Scientist - Part III

My CES Industries EdLab model #804, in the History section

See also

Part I was on "data and databases": "ex-libris" of a Data Scientist - Part i

Part II, was on "models": "ex-libris" of a Data Scientist - Part II

Part IV is right around the corner, and will have a significant Python section.

Francois Dion
@f_dion

Raspberry Pi 3 Canakit

It's been a long time...

I don't even remember when was the last time I talked about Raspberry Pi hardware on my blog. I do remember the first time, however, some 5 years ago. Meanwhile, the price of Raspberry Pis have both gone down (Zero) and up (Raspberry Pi 3) due to economies of scale, Moore's law and removal / addition of components from the various versions.

Raspberry Pi 3

So, I realize that I've covered everything from the original Raspberry Pi model B with 256MB of ram, all the way to the Raspberry Pi 2 and Zero, but nothing on the Raspberry Pi 3. I typically don't buy kits, but I picked one up to see how that would work for people who had never used a Raspberry Pi before. The reason there is that I suggested to my fellow data scientists (and those interested by data science, and whoever else who reads my posts) to also be technologists, to get better acquainted with technology and hardware. And to get one (or four - I'll follow up on that) Raspberry Pi 3. I wanted to make sure it would be smooth sailing.

The Canakit

I ordered a Canakit with a Raspberry Pi board and two heatsinks, a case, a 2.5A power supply and a guide. It is convenient to get a single ready to go package quickly, particularly with free 2nd day shipping (you know who).

I say ready to go, but not quite. Of course you'll need a monitor, keyboard and mouse if you don't enable ssh (distro dependent ways, some have ssh enabled by default). But you'll also need an SD card.

No SD card?

The kit I ordered basically got you the case, heatsinks and power supply for $15 above the price of the Raspberry Pi 3. But no microSD card. The step above kit includes a microSD card with the OS already pre-installed, but when I looked at it, the price difference was too much for just that and a plain HDMI cable.

Oh, but it's so hard to prepare an SD card! Don't panic. Use Etcher. Later, when you get your command line skills up, you'll be able to do it with dd.

If you get stuck, leave a comment or contact me on twitter

Francois Dion
@f_dion

Readings in Data Science models

Ex-libris

As I've previously mentioned, I recently started a 6 part series on LinkedIn called "ex-libris" of a Data Scientist. 

Part I was on "data and databases": "ex-libris" of a Data Scientist - Part i

I just posted part II, "models": "ex-libris" of a Data Scientist - Part II

It does cover machine learning, but before going there, I cover Metrics, Operations Research, Econometrics and Time Series and Statistics. Even more fundamentally, I start with Math.

Yes, if you slept through linear algebra or calculus (or analysis as it is called in certain parts of the world), check the list out. Book suggestions and links to videos and other resources.


Also, a reminder: Python specific books will show up in part IV.

Francois Dion
@f_dion