[cpgeier]

I have a feeling languages like this have their niche cases however I'm not getting a good reason for why this is need when compared to Python for data science. Maybe I'm missing something but this is essentially a wrapper for Golang code to make it feel more like Python.

[DataJunkie]

Agreed, but it might be useful for a full stack data scientist that is forced to work in a Go systems environment.

That's why Python+PyData has had so much success. There are packages to support data science, but the language itself can also be used to implement a system, so integration is rather seamless. That's not true for, say, R.

[cepth]

I guess it depends on what you’re trying to accomplish (I’ve worked heavily with both R and Python).

If you’re trying to create ETL pipelines that integrate with BigQuery, Mongo, or whatever other database, I think it’s fair to say that the Python packages are generally better documented than their R counterparts.

For most other things, IMO it’s hard to really separate the two languages. Is standing up a Flask API really easier than in plumber?

For dashboarding, it’s is as quick (if not much quicker) to create a decent prototype with Shiny vs Plotly Dash or bokeh.

For simple linear and logistic model training, R’s built-in stats package has much more interpretable outputs vs sklearn, and directly inspired statsmodel. Wes McKinney has acknowledged that pandas draws heavily from R’s native dataframe. And so on and so on.

EDIT:

Also forgot to mention that with R packages like reticulate, you can also directly run Python code within an R environment now. So if there happens to be some Python package that doesn’t have an R equivalent, you can still work in R (though I’ve found the opposite situation to be far more common).

[techwizrd]

I use Python and R for data science, and I've never had any issue with R. In fact, I find that many tasks are much simpler in R than in Python.

[DataJunkie]

I am referring to using R to build systems. It's not common.

[cepth]

What would you consider a system? Python definitely has more market share than R, but there's still name brand companies of various sizes that use an R stack for data science.

RStudio lists dozens of example clients here: https://rstudio.com/about/customer-stories/.

Use cases include collaborative model development, EDA tools, dashboarding, printed report generation (PDFs and HTML), public facing websites, etc.

[livvelupp]

> never had any issue

[devy]

The official Github repo of Go+ is hosted on a PaaS company called Qiniu's team repo with their founder & CEO as the top contributor[1][2]. He is a Golang enthusiast[3] and my guess is that this is probably his favorite pet project ;)

[1]: https://github.com/qiniu/goplus/graphs/contributors

[2]: https://github.com/xushiwei

[3]: https://twitter.com/xushiwei