[elcapitan]

Not intending to start a language war here, but if somebody who has experience with both R and Python/pandas/etc could answer - how's the current state of the emerging Python data/statistics ecosystem compared to R? (not counting all the other differences like R being allegedly weird or Python more general purpose and so on).

[Fomite]

Also assuming you don't want to count things like "You can call R from Python, and Python from R", here's my take on it, as someone who uses both languages:

- Pandas has helped Python tremendously, but I don't think it's quite to where the R data frame is.

- For 90% of what someone who wants to do statistics wants to do, it honestly doesn't matter at all. You can do nice data visualization in both. You can fit most generalized linear models in both.

- At the cutting edge, R still takes the cake. Odds are if someone has developed a new method (especially outside machine learning), it's in R before it's in Python. Your local university's statistics department is likely running R (or SAS), not Python.

[TheLogothete]

We did an evaluation recently. Not even close.

[elcapitan]

Is that evaluation somehow public, or could you share some details?