Cyclist in the rain. Blog about python scraping data from wunderground rainfall data.

Analysis of Weather data using Pandas, Python, and Seaborn

The most recent post on this site was an analysis of how often people cycling to work actually get rained on in different cities around the world. You can check it out here. The analysis was completed using data from the Wunderground weather website, Python, specifically the Pandas and Seaborn libraries. In this post, I will …

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AWS Elastic Beanstalk – Logging to Logentries & InsightOps from Python

[Short version] The S3 ingestion script for Amazon applications provided by Logentries will not work for the gzip compressed log files produced by the Elastic Beanstalk log rotation system. A slightly edited script will work instead and can be found on Github here.[/Short Version] Logentries is a brilliant startup originating here in Dublin for collecting and …

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Fixing Office 2016 installation for Mac – error code 0xD0000006

This is a very quick post to help some people out on installation problems with Office for Mac 2016. On an excited day of installation of Excel 2016 on my Macbook, the following error threatened to ruin the day: “An unknown error has occurred, the error code is: 0xD0000006” Seemingly unfound on the internet, the solution, oddly enough …

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Parallel programming allows you to speed up your code execution - very useful for data science and data processing

Using Python Threading and Returning Multiple Results (Tutorial)

Threading in Python is simple. It allows you to manage concurrent threads doing work at the same time. The library is called “threading”, you create “Thread” objects, and they run target functions for you. You can start potentially hundreds of threads that will operate in parallel. Speed up long running tasks by parallelising and threading computation where you can.