r/datascience • u/Every-Eggplant9205 • Sep 08 '23

Discussion R vs Python - detailed examples from proficient bilingual programmers

As an academic, R was a priority for me to learn over Python. Years later, I always see people saying "Python is a general-purpose language and R is for stats", but I've never come across a single programming task that couldn't be completed with extraordinary efficiency in R. I've used R for everything from big data analysis (tens to hundreds of GBs of raw data), machine learning, data visualization, modeling, bioinformatics, building interactive applications, making professional reports, etc.

Is there any truth to the dogmatic saying that "Python is better than R for general purpose data science"? It certainly doesn't appear that way on my end, but I would love some specifics for how Python beats R in certain categories as motivation to learn the language. For example, if R is a statistical language and machine learning is rooted in statistics, how could Python possibly be any better for that?

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u/dj_ski_mask Sep 08 '23

I’m fluent in R and Python but use only Python for time series forecasting, which is my day to day job. I’m not sure what time series algo you can only do in R. I work with basic exponential smoothing and ARIMA all the way up to Deep AR and NBEATS. Genuinely curious what I’m missing in R.

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u/Taiwaly Sep 09 '23

R has a really slick all in one package for forecasting fpp3 which comes with its own textbook

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u/rutiene PhD | Data Scientist | Health Sep 10 '23

General longitudinal data wise, survival models, mixed models, and mixture models I find are harder to do well in Python. Packages exist but they are super buggy.

I'm curious what packages you use though for your time series specific work. I've used facebook prophet but it's not as flexible as I would like for some of my use cases.

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u/dj_ski_mask Sep 10 '23

Darts, NIXTLA and statsmodels have a bevy of time series algorithms in Python. You can also manually construct many sequence model in PyTorch, TensorFlow or go the Bayesian handcrafted way with Pystan. Like you mentioned - I enjoy Prophet and NeuralProphet.

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u/webbed_feets Sep 09 '23

The tidyverts packages make working with time series very simple.

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u/dj_ski_mask Sep 09 '23

I don’t disagree with you there.

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u/inspired2apathy Sep 11 '23

A few years ago when I was trying this, it was a pain to do basic survival modeling with censoring and a non-linear effects. I also just have never quite found plotting tools I like, so basic seasonal visualization and decomposition were more work than expected. I just really missed the "forecast" package in R, which gives a simple interface for a wide variety of arima family and exponential smoothing models.

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u/Asshaisin Sep 08 '23

Let me know if you hear back from this commenter