Probably the main reason I started studying Geology was for the opportunities that it gives you to travel. In the first instance, I thought spending two weeks in the Lake District would be a good break while studying maths and computing at college. It turned out this break would end up being 17 years, although as lovely as they are, thankfully that entire time wasn't spent in the lakes. Needless to say, I love looking at and making maps, so exploring georeferenced data is a natural progression as I'm learning about data science.

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On to the second part of the series documenting the process of setting up this blog. This post will cover setting up GitHub pages and pushing your website, looking at options for customisation such as theme, and finally creating some batch files to streamline the process for adding a new post to the blog to avoid excessive use of terminal.

GitHub Pages and gbp-import¶

• If you don't already have one, create an account on GitHub
• Create a new repository with the name yoursite.github.io without creating a readme or .gitignore
• Return to terminal and install ghp-import using: pip install ghp-pages
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One of the themes for this term is algorithm optimisation, so I've been looking over industry standard sort and search algorithms, ever trying to minimise the 'Big O'. A classmate shared these sort visualisations by morolin, which really help to visualise the differences in efficiency between the algorithms. While these visualisations were created in Golang, they have since been translated in to Python by Kirk Kaiser.

Let's face it, writing code to sort a list isn't particularly interesting, so I wanted to see if I could impliment and visualise my own sort algorithm(s). The next step of course, was to see if similar visualisations could be created to demonstrate search algorithms..

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Word on the town, getting in the habit of documenting your work with Jupyter notebooks is great practise. Jupyter notebooks allow you to create and share documents containing code and rich text, to demonstrate your workflows and visualisations. On a more personal level, it gives you some freedom to be forgetful and know you'll always have an easy repository to remember how you tackled a problem in the past.

The next logical step is how can I use these files to generate content for a blog, without having to reformat and convert any visualisations in to static images? And Pelican it seems, is the answer.

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I am currently pursuing a career change in to data science after previously working as a geophysicist.

As part of this process, I have decided to start blogging my progress in training to become a data scientist, not to share my progress through education, but to give myself an outlet to explore practical data science through my real world interests. What does this mean? Creating data science projects that explore the following themes:

• Geology, Geophysics or Georeferenced Data
• Gaming (Video and Modern Board Games)
• Design and Visualisation (Infographics)

The first couple of posts I'm working on are how to set up a free blog using Jupyter notebooks with Anaconda, which is a slightly different approach to lots of the existing guides online. Then following implementing a board game in my coursework, The Three Musketeers
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