Are you looking for new and interesting things to add to your study? PhD student Nicolás Younes Cardenas has been hunting for ways to add pizzazz to his work. He’s found a simple answer to the question of how to jazz things up without wasting time. Nicolas shares his journey of learning how to code.
You’ve spent hours, days, weeks or months slaving over your work, but something is missing. Maybe you want to add some fancy graphs, repeat an analysis several times or use new datasets. Like me, many of my fellow PhD students spend a lot of time trying to figure out how to do these things, not knowing that there is a simple answer: learn how to code.
Programming and ‘coding’ have become buzzwords associated only with geeks and nerds. This could not be further from the truth! Programming skills are becoming increasingly important in academia, research and industry, where they are highly demanded and appreciated. Over time, I have learnt that coding allows us to do three things:
- Reduce the time we spend on repetitive tasks
- Use bigger datasets
- Make our research replicable
How does this relate to my research?
From new datasets to satellite images, I have had to repeat the same type of analysis more times than I can count. Despite all the time this has taken, I could not imagine how much longer this would have taken if I had not automated some of those tasks. Instead of spending hours (or days) manually doing the analysis, I created a program that runs over the data and, within seconds, comes up with an answer.
By reducing the amount of time I spend on the analysis, I can use bigger datasets for my research. For example, I can now use hundreds of satellite images to look at changes in mangrove forests, rather than using only five or 10. By looking at hundreds of images from the past 30 years, I can have a better understanding of how mangroves react to changes in their environmental conditions. For example, I’m interested in looking at how mangrove forests react to rising temperatures and the fluctuations in sea level. Without programming skills, I would not be able to do this project and I would be writing about something else. But because I’m learning to program, I can use all the images I want and not worry about doing the analyses manually. I can also share my code with colleagues and researchers.
Sharing our codes means that other people can replicate my results, use the code in their research, and correct any error that my code may contain. Once other people have used, corrected and enhanced my code, we can be sure that the code contains fewer errors and can be replicated in other ecosystems. This is important for two main reasons:
- If I share my code, other people can use it straight away instead of spending time writing and testing code. This speeds up the research process and we can analyse more ecosystems in less time.
- Software licenses can be very expensive and not all researchers can afford them. By giving away our code, other researchers could do a given analysis without having to buy expensive software, thereby we are making our research methods accessible to everyone.
Coding beyond research
But coding goes far beyond research and science. Coding is a skill that has many applications:
- Bored at work? Hack the coffee machine.
- Want to create an awesome costume? Add some lights.
- Always wanted a digital photo frame? Make one yourself.
- Make your own wireless printer.
- Or code with your kids.
Coding is a skill that will allow us to make better use of computer resources, make research more accessible and make research replicable and fast. So learn to code, and share your code with your colleagues, friends and kids.
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