[nimmer]

> If Nim can work with numpy it's a plus

Nim goes further there by removing the need for tools like Pandas and numpy. You don't have to write code in "Pandas-style" because native Nim is equally fast and sometimes faster.

[memling]

> Nim goes further there by removing the need for tools like Pandas and numpy. You don't have to write code in "Pandas-style" because native Nim is equally fast and sometimes faster.

Can you clarify this? Is there an equivalent data stack in Nim? Or is it that nim is lighter-weight because, for example, it permits transforming tabular data into language structures natively (i.e., without library support)?

[cb321]

Besides @nimmer's fine response, there is also https://github.com/SciNim/Datamancer

[nimmer]

The latter. For most uses of Pandas you can simply use native arrays. You can use for loops and so on.

For N-dimensional array computation: https://github.com/mratsim/Arraymancer/