I keep telling myself that I should do more Python programming as it’s the future and R is a dying language. R isn’t the most popular language compared to Python.

But the thing is Python remains far behind R when it comes to map making and graphics. And there is a ton of useful packages out there for R, sometimes much better packages for R then Python especially when it comes to graphics and light manipulation of data, especially Census data. PANDAS might be better for heavy lifting then tidyverse but for many things the tidyverse is simpler.

Yet I concede R is a like adopting the Macintosh System 7 platform decades ago in the era of Windows 95. Your simply not using what the masses are using and you are somewhat locked out of benefits of a popular platform. Moreover, the underlying code in R is often slow and inefficient, with a legacy of 50 year old designs unlike the relatively modern clean and elegant of Python. Much like Macintosh System 7 compared to Windows 95. Macintosh System 7 did a lot of things good in graphics and user interface but the underpinning were a hot mess of hacks built on code from the early 1980s. Windows 95 had protected memory and preemptive multitasking while System 7 was stuck in the era of shared memory and cooperative multitasking.

But R is different than Macintosh System 7. R might be creaky and old but it’s actively maintained and unlikely to be killed off with a single shot by a corporation like Apple did with Macintosh System 7 with the release of Mac OS X. R programming will last forever even if it eventually dies out to Python as it’s open source and not controlled by a profit seeking corporation. Old R code is unlikely to stop working, as there is enough existing code base that interpretive environments are likely to be maintained just like how GNU FORTRAN still is a thing despite little new FORTRAN code written anymore.

Yet my bigger fear is that every time I use R programming language not only am I not writing truly future compatible code, I’m not practicing a skill that is beneficial for my future. I’ve read a lot of books on Python code and I’ve written a lot of Python but the way to be truly good at something is to use it a lot and practice. It’s great to be a skilled R programmer but if Python is the future it’s what for naught. Yet, I constantly find when I write code in Python the weakness of the graphics, geospatial and even data wrangling capacities come back to bite my compared to what I can easily do in R no matter how much research I do into libraries and best practices. And that troubles me to keep going back to the second fiddle known as R programming.