Invoking BigVar with pandas DataFrame for data does not work, to_numpy() provides workaround

[extrospective]

It is not unusual to pass a pandas DataFrame where an array is requested.
(Not sure whether it is responsibility of library to know about this.)

With xyz as a DataFrame, I successfully invoked:

mod=BigVAR(xyz, p=lag_max, struct="Basic", gran=[150,10], T1=T1, T2=T2, VARX={})

But then rolling_validate(mod) fails with an error such as:

--> 190         trainY = np.array(Y[p:Y.shape[0], :], copy=True)
    191         print(f'trainY shape is {trainY.shape}')
    192         trainY = np.array(trainY[0:T2, :], copy=True)

d:\Anaconda3\envs\py39\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   3022             if self.columns.nlevels > 1:
   3023                 return self._getitem_multilevel(key)
-> 3024             indexer = self.columns.get_loc(key)
   3025             if is_integer(indexer):
   3026                 indexer = [indexer]

d:\Anaconda3\envs\py39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   3078             casted_key = self._maybe_cast_indexer(key)
   3079             try:
-> 3080                 return self._engine.get_loc(casted_key)
   3081             except KeyError as err:
   3082                 raise KeyError(key) from err

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

TypeError: '(slice(2, 365, None), slice(None, None, None))' is an invalid key

Workaround: be sure to convert DataFrame to a numpy array before calling BigVar.
This code does not encounter the same error when subsetting Y.

mod=BigVAR(xyz.to_numpy(), p=lag_max, struct="Basic", gran=[150,10], T1=T1, T2=T2, VARX={}) # {'k':var_count, 's':1})

Here, the DataFrame uses to_numpy() so the reduction to an array occurs before BigVAR sees the structure.

[extrospective]

A python label seems appropriate here; maybe labels should be added to project.