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