First, thank you for creating and maintaining such a wonderful package! It addresses a need I've had for a long time.

I'm writing to request a feature that would enhance the package's utility for paleoclimate data visualization, specifically the creation of stackplots.

A common challenge when working with paleoclimate data from multiple sources is that these datasets often come in the form of "non-equal length" dataframes (i.e., dataframes with varying lengths) and have different temporal resolutions. This often leads to a situation where each proxy (paleoclimate indicator) has its own dedicated age/time column alongside its paleoclimate value column.

Given this scenario, I'm wondering:

Is it possible to create stackplots directly from a "wide" dataframe structure where each proxy has separate age/value columns?

If not directly from a wide format, what is the recommended approach for generating stackplots in this situation? Would it involve converting the data to a "long" dataframe format? If so, could you provide guidance or examples on how to structure the long dataframe and use your package to create the stackplot?

Any advice or potential implementation of this feature would be greatly appreciated. Thank you for your time and consideration.

As shown in the figure below: wider data.frame

Columns starting with ​**"KA"​ represent the year/period columns.
Columns starting with ​"VAL"​ indicate the proxy indicator values.
Columns starting with ​"ATR"**​ denote the data's proxy indicator attributes.