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  • SCIPY_ARRAY_API before importing sklearn or scipy
  • NaN in the Cloud, but none locally
  • Use the same index
  • Reset the index
  • Other
  1. Competitions

Known Issues

A list of known problem and how to solve them.

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Last updated 3 days ago

SCIPY_ARRAY_API before importing sklearn or scipy

Since the is experimental, models that need it must enable it.

In a dedicated cell at the very top—even before the imports—and without changing anything, write the following:

Notebook Cell (Python)
# @crunch/keep:on

import os
os.environ['SCIPY_ARRAY_API'] = '1'

NaN in the Cloud, but none locally

The index might not always be the same in the Cloud and locally as the data that is shared is different.

Depending on your code, this could cause some issues when trying to do operation between pandas objects that do not share the same index.

Notebook Cell (Python)
# will use a range index, from 0 to len(X_test)
final_ensemble = pd.Series(
    [0] * len(X_test),
    dtype='float'
)

# pandas objects do not share the same index, it will likely result in only nans
final_ensemble += (X_test.loc[:, 'some_colomn'] * 2)

Use the same index

Notebook Cell (Python)
final_ensemble = pd.Series(
    [0] * len(X_test),
    index=X_test.index,
    dtype='float',
)

Reset the index

Notebook Cell (Python)
X_test.reset_index(inplace=True)

# then do your operations
final_ensemble += (X_test.loc[:, 'some_colomn'] * 2)

Other

If your problem is not listed, don't hesitate to reach the team!

SciPy array API