Application is now open for the Digital Technology Awards 2018! The Digital Tech Awards on 26 April always attract fierce competition from all corners of our industry and provide an amazing opportunity to showcase your company. Be in with a chance to win one of their coveted awards. The Data Lab are proud to be […]
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Running R remotely: some options and tips
Why would you need to do this? Say, for instance, you are dealing with sensitive data that should not leave a specific system, or quite simply that you are away on a work retreat – but your laptop is far less powerful than your work desktop computer which you left behind – so you want […]
Excel-like functionality with Python pandas: The Data Lab takes the Pepsi Challenge!
Happy Birthday Excel! I would posit that the world’s most used data science software is the ubiquitous Microsoft Excel. Released for Windows in November 1987, this month marks its 30th anniversary. In that time I’d imagine it has been employed by all manner of people across near all industries: from the fund manager tracking his […]
Analysis of Gaelic Station Names: An exploration of inter-language similarity measures for place-names and the design of rural scores.
Motivation Most of modern Scotland was once Gaelic-speaking and a policy change in 2010 means Gaelic names appear alongside English names on almost all station signs across Scotland’s railway. I live in Glasgow and often travel out into the highlands and over time I hypothesised: H1: The Gaelic and English names of a station become more similar […]
Snakes and Ladders (Part 3 of 3): Analysing the classic children’s game
To recap the analysis from our previous article, we have now shown that the advantage to Player 1 in snakes and ladders is minimal (amounting to less than 6 extra wins out of every 1,000 games). In this post we look at visualising some results, focusing in particular on the distribution of game lengths and the […]
Dealing with many dimensions in historical data: Tracking cooperation & conflict patterns over space and time in R
For this post, I’ve managed to find some extremely interesting historical event data offered by the Cline Center on this page. As you will see, this dataset can be quite challenging because of the sheer number of dimensions you could look at. With so many options, it becomes tricky to create visualisations with the ‘right’ level of granularity: […]
Matt Higgs, Data Scientist at The Data Lab
First in a new series of Interviews with Data Scientists, we speak to Matt Higgs of The Data Lab.
Snakes and Ladders (Part 2 of 3): Analysing the classic children’s game
In the previous post in this series, we set out the basic Python code required to simulate a single game of snakes and ladders. In order to analyse the game in more detail we will be required to simulate multiple random games so that we can look at certain properties, such as expected game lengths, […]
Snakes and Ladders (Part 1 of 3): Analysing the classic children’s game
In this short series of three blog posts we show how easy it can be to take an everyday activity and analyse it using Python, gaining insights that might illuminate or in some cases even surprise… Anyone who has ever played games against young children knows that they absolutely must go first, and my daughter Eva is […]
Data guidelines: A set of recommendations for clean and usable data
The extent to which a dataset follows a set of commonly expected guidelines will often determine how much time you have left to spend thinking about your analysis. Ideally, you might intend to spend 20% of your time cleaning the data for a project, and 80% planning and carrying out your actual analysis. But often, […]