Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

Can't visualise 3D arrays with variables explorer

See original GitHub issue

Data science require visualising 3D arrays for testing/debugging purposes.

import numpy
array =  numpy.zeros((3,3,3))

When double clicking on the variable array in the variable explorer :

This array can’t be visualised in the variable explorer, only 2D arrays are allowed. Spyder displays it as a 2D array and allow to switch dimenssion and slice through the array. Not super intuitive at first but works and should be easy to implement. It’s just about extracting 2D from 3D.


Error: Failure during variable extraction:
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
c:\Users\Boris\Desktop\3Darray.py in <module>
     45         _VSCODE_df = _VSCODE_pd.Series.to_frame(_VSCODE_evalResult)
     46     elif _VSCODE_targetVariable['type'] == 'ndarray':
---> 47         _VSCODE_df = _VSCODE_pd.DataFrame(_VSCODE_evalResult)
     48 
     49     # If any rows, use pandas json to convert a single row to json. Extract

~\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy)
    438                 mgr = init_dict({data.name: data}, index, columns, dtype=dtype)
    439             else:
--> 440                 mgr = init_ndarray(data, index, columns, dtype=dtype, copy=copy)
    441 
    442         # For data is list-like, or Iterable (will consume into list)

~\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\internals\construction.py in init_ndarray(values, index, columns, dtype, copy)
    169     # by definition an array here
    170     # the dtypes will be coerced to a single dtype
--> 171     values = prep_ndarray(values, copy=copy)
    172 
    173     if dtype is not None:

~\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\internals\construction.py in prep_ndarray(values, copy)
    293         values = values.reshape((values.shape[0], 1))
    294     elif values.ndim != 2:
--> 295         raise ValueError("Must pass 2-d input")
    296 
    297     return values

ValueError: Must pass 2-d input