I'm looking for input on using/creating a "standard" data structure to store PV measurement datasets, such as I-V curves supporting IEC 61853-1. I'm thinking of something flexible/extensible and self-documenting (esp. w.r.t. units). This space also seems to intersect with time-series of I-V curves and maybe PECOS workflows.

For example, I have a collection of I-V-F-T curves, each with possibly varying numbers of points, that are each taken at a "nominal" matrix of effective irradiance F = 0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.1 (unitless) and temperature T = 15, 25, 50 degC. Sticking to just python and numpy (pandas doesn't seem like the right fit here), I came up with this dict-based structure:

data = {
('0.1', '15 degC'): {'v_V': numpy.array([v_1, v_2, ..., v_M]), 'i_A': numpy.array([i_1, i_2, ..., i_M]), 'f': numpy.array([f_1, f_2, ..., f_M]), 't_degC': numpy.array([t_1, t_2, ..., t_M])},
('0.2', '15 degC'): {'v_V': numpy.array([v_1, v_2, ..., v_N]), 'i_A': numpy.array([i_1, i_2, ..., i_N]), 'f': numpy.array([f_1, f_2, ..., f_N]), 't_degC': numpy.array([t_1, t_2, ..., t_N])},
...
}

In this case, I could retrieve the currents vector for a particular curve using data[('0.2', '15 degC')]['i_A']. I also need to concatenate (in a consistent order) all the currents, voltages, etc. from all the curves together. One could also imagine repeated I-V-F-T curve measurements at each nominal setting (with possibly a different number of points in each repetition).

The ordered-pair keys can also be sorted in various ways using sorted(), as long as the chosen strings don't cause ordering problems. Note that replacing the keys with timestamps would produce time-series I-V-F-T curve data.