scenario

This is more or less similar to what we were doing long time ago with pybullet (#110, #149).

In few words, after #346 the pure-Python gym-ignition package will depend on scenario. When gym-ignition gets installed in a system (currently only Ubuntu is supported), the wheel of scenario will be installed first. Since the wheel of scenario is not self-contained (i.e. it needs to find in t

A naive user (read: me) can obtain an obscure error message if set_meta_from_data() is used in an unintended way.

Take for example the regional SR15 dataframe. The following code will elicit the following error message:

df.set_meta_from_data(
    name='CO2 Emissions in 2050',
    variable='Emissions|CO2',
    year=2050,
)
...
File c:\users\gidden\work\iiasa\pyam\pyam\core.py:890

It would be nice to have a handful of "standard" derived variables added to the database without the need to calculate them by hand. Initial candidates would be per capita values for final/primary energy (total), GDP, emissions, and intensities of energy/GDP, emissions/GDP, or emissions/energy. The Kaya decomposition indicators would be a good first step: https://en.wikipedia.org/wiki/Kaya_identi