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Real Python

Just purchased a new book on Python to get me through the CO-VID-19 situation.

https://realpython.com/products/python-basics-book/

Python Basics Book

At USD $39 it is a reasonable price, but with the drop in the Australian dollar this comes to AUD $63 …. for a PDF 🙁


So why buy it?
– I don’t want to wait for the physical book which is months away.
– I am no longer twenty, the font in some books is too small making it hard to read.
But with a PDF I can read it on a 24″ monitor next to my main 29″ monitor so no problems with font size.
– The content is really good. The Real Python site has many excellent articles on python that have helped me. So this is my way of supporting their free content.

The book uses Python 3.8
I use Anaconda Python which is currently at version 3.7 So I have to install a 3.8 environment.
In Conda you can do this by:

$ conda create -n py38 python=3.8

Useful links for my purchase:

– https://realpython.com/lessons/python-basics-book-downloads/

– https://realpython.com/python-basics/resources/

– https://github.com/realpython/python-basics-exercises

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Web Links for March 2020

R

Python

Visual Studio Code

Raspberry Pi

Compile/install Python 3.8 on Raspberry Pi | Michael Hirsch, Ph.D.
Raspberry Pi 4 Bootloader Firmware Updating / Recovery Guide
Hass.io – Home Assistant
Turns your Raspberry Pi (or another device) into the ultimate home automation hub powered by Home Assistant
Dual Fan Aluminium Heatsink Case for Raspberry Pi 4 Black Australia
Raspberry Pi 4 USB Boot Config Guide for SSD / Flash Drives
GitHub – log2ram: ramlog like for systemd (Put log into a ram folder)
Log2Ram: Extending SD Card Lifetime for Raspberry Pi

Cycling

JaYoe World Tour Homepage | Follow Matt Cycling Around The World!

Purchased “The Art of Statistics” from Amazon for $30

Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way statistical claims can be sensationalised, particularly in the media. In the age of big data, as data science becomes established as a discipline, a basic grasp of statistical literacy is more important than ever.

In The Art of Statistics, David Spiegelhalter guides the reader through the essential principles we need in order to derive knowledge from data. Drawing on real world problems to introduce conceptual issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether serial killer Harold Shipman could have been caught earlier, and if screening for ovarian cancer is beneficial.

How many trees are there on the planet? Do busier hospitals have higher survival rates? Why do old men have big ears? Spiegelhalter reveals the answers to these and many other questions – questions that can only be addressed using statistical science.

https://dspiegel29.github.io/ArtofStatistics/
The Art of Statistics: Code, Data, Errata and Additions | ArtofStatistics

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Completed Introduction to Python Certificate

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Statistics and Programming Tutorials

From my point of view I am only interested in three languages for stats, R, Python and Excel. Excel I won’t cover here, but there are many fine books on it on Amazon.

R and Python are free open source languages. R is a language for statistics, whilst Python is a more general purpose programming language.

I prefer the syntax of Python over R any day, but for statistical modelling and making pretty graphs, R has a great mindshare.

Books about Python and statistics

Think BayesThink Bayes is an introduction to Bayesian statistics using computational methods. This version of the book is a rough draft. The author is making the draft available for comments, but it comes with the warning that it is probably full of errors.

Think Stats: Probability and Statistics for ProgrammersThink Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding. Most introductory books don’t cover Bayesian statistics, but Think Stats is based on the idea that Bayesian methods are too important to postpone. By taking advantage of the PMF and CDF libraries, it is possible for beginners to learn the concepts and solve challenging problems.

Think Python: How to Think Like a Computer ScientistThink Python is an introduction to Python programming for beginners.

R

R is used a lot in academia and science. A lot of online stats courses use R for teaching statistics.

A Crash Course in R | (R news & tutorials)single program with many examples of syntax

Getting staRted with R. | (R news & tutorials)lots of links to good tutorials

twotorials by anthony damicoexcellent tutorial screencasts on R

Flowingdata TutorialsFlowing data is a great site, not just for R, but statistics and presentation in general

The Guerilla Guide to RIt’s basically a number of Stack Overflow links organized and ordered in a way to help R programmers learn their way to the next level. If you are proficient in R, I hope these resources will help you get closer to being amazing. If you are just getting started with R, I’d suggest adding this page to your bookmarks and returning when you are familiar with the basics of R programming.
This “book” essentially writes itself since most of the experts (and peer-reviewers) are answering the questions. Most of the questions are “real-world” and are asked by novice or intermediate programmers.

Books

IPSUR – Introduction to Probability and Statistics Using Ra textbook written for an undergraduate course in probability and statistics.

Learning Statistics with R | Computational Cognitive Science LabA free book form the university of Adelaide, designed for an introductory statistics class for psychology students, using the R statistical package as the primary tool 

Introduction to Data ScienceThis book provides non-technical readers with a gentle introduction to essential concepts and activities of data science. For more technical readers, the book provides explanations and code for a range of interesting applications using the open source R language for statistical computing and graphics.
Available in PDF and ibook format 

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Python 2.7.3

I am now relearning statistics, oh what an exciting life I lead.
Since no learning is complete without procrastination, I though I would learn Python first.

Python is actually related b/c it is an ideal vehicle to screen scrape websites to get data for statistical analysis. And if you are so inclined you can use python for stats itself (SciPy, NumPy) as well as making pretty graphs.

Anyway, the latest version of Python is 2.7.3 and yes I am aware of version 3, but a lot of the popular modules still do not with with version 3.

Mac OS X 10.7.8 Mountain Lion comes with Python 2.7.2, to upgrade to 2.7.3 I used the following to help:

 

http://superuser.com/questions/388854/the-suggested-way-to-handle-pipeasy-install-with-homebrew
http://www.insomnihack.com/?p=442
http://www.insomnihack.com/?p=421 (old version of the link above)
http://www.thisisthegreenroom.com/2011/installing-python-numpy-scipy-matplotlib-and-ipython-on-lion/

 

Once I get confident with Python, I might just reinstall everything, but this time using a virtual environment for Python.