Why Do Python Make Data Science Complicated?

[uyoakaoma]

There are a lot articles about which language is better for data analysis. I have been using python for many things web development, data analysis etc. But I started learning R. It is easy. Anything that I would do with python for data analysis now I would just do it in one liners. Why do Python Make Data Science so complicated?

[devnonymous]

For the same reason why web development would be complicated using R. Python was designed as a general purpose programming language and can be used for a lot of things where as R was designed for data science.

[CyberFonic]

If you already know Python and you need to explore some aspect of data science then Python based tools are very practical. Once you confirm your initial hypothesis, then you will probably use R for the production versions of your analysis.

Python is becoming the Swiss Army Knife of computing, lots of great tools that work with it, but for heavy duty use you will choose the most appropriate tool. The SWK might have a saw like blade, but you'd probably reach for the Black and Decker when wanting to cut some lumber. It is certainly going to be quicker and result in less sweating.

[curiousgal]

R was made specifically for statistical computing.

[uyoakaoma]

I have been using sklearn to do basic regression on linear models. It would take more than 10 lines that is importing helper libraries like pandas to read csv's. But just a few days ago I tried R. Just two lines.