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Another post looking at Twitter data in R. It follows this one and this one. I wanted to look again at my tweeting frequency over the 12 years on Twitter, but this time do it in a calendar view. Something like a GitHub commit calendar would be perfect. I have used a library for this in the past.

Published

Please consider this a “supplementary analysis” to my previous post looking at the frequency of tweets from my personal account over the last 12 years. I was curious about what times I was active on Twitter (measured by when I tweeted). Others might be interested in a solution to look at this in R. The code As in the previous post, we need to get the data into R and then make sure we have a date object to work with.

Published

At the time of writing, I have essentially left Twitter. It was a fun ride and without going into what’s happening there now, this is a good opportunity to look at my 12 years on the platform. Early in November, I downloaded my data and locked my Twitter account. This gave me all the data I needed. Using R, a few nifty libraries and the tweets.js file that was part of the download, I could gain quite a lot of insight.

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There are lots of ways for runners and cyclists to analyse training data. A key question most fitness enthusiasts want to know is “how am I doing?”. “How you are doing” is referred to as form . Unsurprisingly, form can be estimated in many ways. One method is using training stress scores (acute training load and chronic training load) to assess form as training stress balance.

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By 30th September 2022, I had clocked up a total of over 2000 km of running in 2022. This milestone was a good opportunity to look at how I got to this point. The code is shown below. First, we can make a histogram to look at the distance of runs. From this type of plot it’s clear that my runs this year consist of a lot of 4-5 km runs and then a chunk of 21 km plus.

Published

Sometimes an update causes a chain reaction which borks a system. Here are some notes on how I fixed a SMTP mail issue on my Raspberry Pi camera project. A quick recap: the RPi camera takes pictures every ten minutes, each night the images get sent to a server and each week the transferred images get deleted.

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It’s been a while since I posted a breakdown of half marathon times. The last time seems to have been 2018. I decided to give my old code a clean-up and quickly crunched the numbers from the 2022 Kenilworth Half Marathon. First, the results: Briefly, the code below reads in a csv file of race results downloaded from the provider.

Published

This website is all about niche tech tips and this post is no exception. I run a Plex media server. This allows me to stream my music collection when I am out and about. Plex pass owners get the nifty plexamp app for listening to music, which I really like. The databasing for the movie and TV show side of Plex works great, but the music side has its peculiarities. The problem I have a large music library.

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Niche tech tips are the cornerstone of this website, and here is another. How to upgrade an iTunes/Music library whilst maintaining the database. I know everyone streams music these days – hence this is likely a very niche tech tip – but I still maintain a large music database on a server. The data in my library is precious (to me) since it tracks my listening habits over 17 years.

Published

Previously I wrote about latin squares and set a puzzle. We can demonstrate this for an n x n latin square where n = 12 In the above images, the normalised latin square only has 12 different pairs out of a possible 66. The density plot shows the pairings in the lower triangle, grey represents 0. A randomly generated latin square (where all rows and all columns feature 1 to 12 exactly once) is shown where all possible pairs are captured.