I primarily use Python, but I think R is here to stay. Ecologists and other researchers are not computer scientists. If the software tool is good enough, and has adequate support in the community, there is no need to switch. Switching to python would mean that researchers would have to learn a new system, and they would rather spend the time writing or collecting data.

yeah, python can do anything.

Though now the shortage of python is obvious that it is difficult for stats bacgroud, I still recommend you to learn and grasp it.

Python has lots of a #trump #cards, R is used in #Statistics. Python is one the the most used in scientifc community. Code's expert also use #Haskell, compact Langage.

I agree with you Christopher A Varnon, I have no doubt R is here to stay. Actually, I think Python will follow the same path, even in Ecology. For Ecological studies, my guess is that Python will gain more space in intensely computational investigations, like simulation models.

There may be case of working simultaneously with R and Python. I have seen some progress in compilers that allow running Python inside R.

Cheers

R is the lingua franca of statistics (and graphics), while Python is a multi-purpose language that allows improving the productivity of developers

Compared to Python, it is easier to perform complex data analysis in R. The large number of statistical packages allows you to perform any data analysis easily and quickly, with few lines of code.

While Python has packages for statistical analysis, it still lacks some of the richness of R for data analysis. Right now R is ahead at this point, although little by little the gap is closing.

@Abdiel Jover Capote For example in aspects of species modeling we use R, but when we use QGIS to customize our graphics there is the Phyton console option that if we know this language we can introduce improvements to what we are doing, I think they complement each other and right now I use more R that Phyton

The strength of Python lies in interfacing powerful programs between them in a simple and efficient way. So I guess I'll call R from python:

https://sites.google.com/site/aslugsguidetopython/data-analysis/pandas/calling-r-from-python

https://rpy2.readthedocs.io/en/version_2.8.x/introduction.html

R Vs Python: What’s the Difference?

R and Python are both open-source programming languages with a large community. New libraries or tools are added continuously to their respective catalog. R is mainly used for statistical analysis while Python provides a more general approach to data science.

R and Python are states of the art in terms of programming language oriented towards data science. Learning both of them is, of course, the ideal solution. R and Python requires a time-investment, and such luxury is not available for everyone. Python is a general-purpose language with a readable syntax. R, however, is built by statisticians and encompasses their specific language.

Conclusion:

In the end, the choice between R or Python depends on:

1. The objectives of your mission: Statistical analysis or deployment

2. The amount of time you can invest

3. Your company/industry most-used tool

https://www.guru99.com/r-vs-python.html

My advice is learn both and then choose the easiest for your current problem. Best. D. Booth

As R has been using in Ecology field from the long days, it became popular and already so many functions or packages are developed. So, when researcher are applying any methods who are not programmer or those who are doing only application part, they are getting already developed packages and using it. That is why day by days R is becoming more popular on that field.

But, Python is more flexible and more capable in any field.

So, its depend on your purpose of application. R is little slower when you will use loop, it used to lag but Python is very smooth. And sometimes you will feel that R is more easier than Python because for some operations and application the syntax length is little bit larger. Now, you can run your R code in Python platform, that means Python is more diversified.

follow R!

I work on a related field as yours but in microbial ecology. I have changed from R to python almost a year ago, after using it for 5 or so years. Don't regret a second. Gained flexibility and speed - that is an understatement. I am a pythonista now! R is great though, but with large datasets my experience is that python brings many advantages that you can find more detailed explanation online for. And I like the language syntax a lot more. Additionally, I prefer to use a single language for everything I do. And if I really wanted to speed up my analysis, then I guess I would learn C++, or actually Julia nowadays. With that said, I would not venture to guess if python will take over in this field. As I said, I think R is great. Best wishes!