While some people love dataframes, in both Python and Julia, they feel constraining to me.
Does this mean there will be more features limited to DataFrames?
For example, Gadlfy is nice in many ways but by not using Dataframes it means I have to do my own colors for each data I plot. Some of the statistics features in GLM seem to rely heavily on DFs as well.
Dataframes could be much more useful more broadly if the interface was more consistent, better documented (e.g. still haven't figured out how to instantiate with half my data).
Basically, null-ability is pretty useful feature in many fields, not just statistics. Will the plans include any items to help generalize nullability?
(Replying to PARENT post)
Does this mean there will be more features limited to DataFrames?
For example, Gadlfy is nice in many ways but by not using Dataframes it means I have to do my own colors for each data I plot. Some of the statistics features in GLM seem to rely heavily on DFs as well.
Dataframes could be much more useful more broadly if the interface was more consistent, better documented (e.g. still haven't figured out how to instantiate with half my data).
Basically, null-ability is pretty useful feature in many fields, not just statistics. Will the plans include any items to help generalize nullability?