Technology Tales

Adventures & experiences in contemporary technology

Self-learning new computing languages

10th April 2021

Over the years, I have taught myself a number of computing languages with some coming in useful for professional work while others came in handy for website development and maintenance. The collection has grown to include HTML, CSS, XML, Perl, PHP and UNIX Shell Scripting. The ongoing pandemic allowed to me added two more to the repertoire: R and Python.

My interest in these arose from my work as an information professional concerned with standardisation and automation of statistical results delivery. To date, the main focus has been on clinical study data but ongoing changes in the life sciences sector could mean that I may need to look further afield so having extra knowledge never hurts. Though I have been a SAS programmer for more than twenty years, its predominance in the clinical research field is not what it was so that I am having to rethink things.

As it happens, I would like to continue working with SAS since it does so much and thoughts of leaving it after me bring sadness. It also helps to know what the alternatives might be and to reject some management hopes about any newcomers, especially with regard to the amount of code being produced and the quality of graphs being created. Use cases need to be assessed dispassionately even when emotions loom behind the scenes.

Both R and Python bring large scripting ecosystems with active communities so the attraction of their adoption makes a deal of sense. SAS is comparable in the scale of its own ecosystem though there are considerable differences and the platform is catching up when it comes to Data Science. The aforementioned open source languages may have had a head start but it seems that others are not standing still either. It is a time to have wider awareness and online conference attendance helps with that.

The breadth of what is available for any programming language more than stymies any attempt to create a truly all encompassing starting point and I have abandoned thoughts of doing anything like that for R. Similarly, I will not even try such a thing for Python. Consequently, this means that my sharing of anything learned will be in the form of discrete postings from time to time, especially given ho easy it is to collect numerous website links for sharing.

The learning has been facilitated by ongoing pandemic restrictions though things are opening up a little now. The pandemic also has given us public data that can be used for practice since much can be gained from having one’s own project instead of completing exercises from a book. Having an interesting data set with which to work is a must and COVID-19 data contain a certain self-interest as well though one always is mindful of the suffering and loss of life that has been happening since the pandemic first took hold.

Add a Comment

Your email address will not be published. Required fields are marked *

Please be aware that comment moderation is enabled and may delay the appearance of your contribution.

  • All the views that you find expressed on here in postings and articles are mine alone and not those of any organisation with which I have any association, through work or otherwise. As regards editorial policy, whatever appears here is entirely of my own choice and not that of any other person or organisation.

  • Please note that everything you find here is copyrighted material. The content may be available to read without charge and without advertising but it is not to be reproduced without attribution. As it happens, a number of the images are sourced from stock libraries like iStockPhoto so they certainly are not for abstraction.

  • With regards to any comments left on the site, I expect them to be civil in tone of voice and reserve the right to reject any that are either inappropriate or irrelevant. Comment review is subject to automated processing as well as manual inspection but whatever is said is the sole responsibility of the individual contributor.