Merging and Joining data sets are key activities of any data scientist or analyst. In this tutorial, we explore the process of combining datasets based on common columns quickly and easily with the Python Pandas library and it’s fast merge() functionality. Finally conquer merging and become a master with this 2-part tutorial.
Read More →Geocode your addresses for free with Python and Google For a recent project, I ported the “batch geocoding in R” script over to Python. The script allows geocoding of large numbers of string addresses to latitude and longitude values using the Google Maps Geocoding API. The Google Geocoding API is one of the most accurate geocoding […]
Read More →Pandas Data Selection There are multiple ways to select and index rows and columns from Pandas DataFrames. I find tutorials online focusing on advanced selections of row and column choices a little complex for my requirements. Selection Options There’s three main options to achieve the selection and indexing activities in Pandas, which can be confusing. The three selection cases and […]
Read More →Want better colours for ggplot2? “Ggthemr” is an R package that provides new colour themes and also the specification of your own colour palettes. Change the look and feel of your ggplot2 plots in R with two quick commands! Beautiful figures await!
Read More →How often do you get wet cycling to work? Cycling in Ireland is taking off. The DublinBikes scheme is a massive success with over 10 million journeys, there’s large increases in people cycling in Irish cities, there’s a good cyclist community, and infrastructure is slowing improving around the country. However, Ireland is a rainy place! It turns out that […]
Read More →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 […]
Read More →Pandas – Python Data Analysis Library I’ve recently started using Python’s excellent Pandas library as a data analysis tool, and, while finding the transition from R’s excellent data.table library frustrating at times, I’m finding my way around and finding most things work quite well. One aspect that I’ve recently been exploring is the task of […]
Read More →FAST TRACK: There is some python code that allows you to scrape bike availability from bike schemes at the bottom of this post… SLOW TRACK: As a recent aside, I was interested in collecting Dublin Bikes usage data over a long time period for data visualisation and exploration purposes. The Dublinbikes scheme was launched in […]
Read More →Self-Organising Maps Self-Organising Maps (SOMs) are an unsupervised data visualisation technique that can be used to visualise high-dimensional data sets in lower (typically 2) dimensional representations. In this post, we examine the use of R to create a SOM for customer segmentation. The figures shown here used use the 2011 Irish Census information for the […]
Read More →“Is there any online reading or courses I can do to get into data analysis?” At my workplace, I get asked the question above. The question is usually posed by people typically with a finance background, who’s working as a management consultant. In this post I propose a learning path for such people to “get […]
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