3 ms·
would love to hear input from people with both lab and software dev experience to compare and contrast the two notetaking experiences
by neoluddite 7y ago
would love to hear input from people with both lab and software dev experience to compare and contrast the two notetaking experiences
- Odenwaelder 7y agoThese are excellent suggestions and are taught in science classes. Except for the use of Excel. Yes, Excel is easy, but its flexibility will lead to sloppiness, and drawing figures sucks. Excels statistical functions are also wrong in some cases. For data analysis, learn R or Python, period. If you have lots of data, learn to use SQLite in addition. The learning curve is steep, but well worth it. Source: I have a decade of experience in science, and some 5 years in software development.
- dhruvmittal 7y agoSo I had the opposite experience-- learned to do all my data processing in undergrad+grad school for physics using Python. Moved out to my first industry job developing simulations and learned that everyone (other scientists, management, etc) would rather me process results in excel (unless we were working on a database scale, in which case we used postgres). I actually had to learn excel properly for the first time for this job. I'm now at another large university-affiliated research lab and excel is king here as well, though I can get away with using Matlab generated plots in my slides when I'm working solo. People still don't like python for some reason. I had a similar experience with paper writing-- in academics it was conventional to do everything in LaTeX from my first lab courses in freshman year. In both workplaces, we've just been using word. And it's not that people don't know python/latex here-- we've just apparently developed a culture of using these matlab/excel/word tools instead.