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@ngupta23 ngupta23 commented Oct 10, 2021

Related Issuse or bug

#1665
#1666

Fixes: #[issue number that will be closed through this PR]
Closes #1665
Closes #1666

Describe the changes you've made

Type of change

  • Bug fix (non-breaking change which fixes an issue)

How Has This Been Tested?

Unit tests pass

Checklist:

  • My code follows the style guidelines of this project.
  • I have performed a self-review of my own code.
  • I have commented my code, particularly in hard-to-understand areas.
  • I have made corresponding changes to the documentation.
  • My changes generate no new warnings.
  • I have added tests that prove my fix is effective or that my feature works.
  • New and existing unit tests pass locally with my changes.
  • Any dependent changes have been merged and published in downstream modules.

@ngupta23 ngupta23 added the time_series Topics related to the time series label Oct 10, 2021
@ngupta23 ngupta23 added this to the Time Series Beta Release milestone Oct 10, 2021
@ngupta23 ngupta23 requested a review from Yard1 October 10, 2021 11:21
@ngupta23 ngupta23 changed the title Ts improve Time Series Bug Fixes and Error Handling Oct 10, 2021
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Thanks!

forecaster.fit(y_train, X_train, **fit_params)
except ValueError as error:
## Currently only catching ValueError. Can catch more later if needed.
logging.error(error)
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Perhaps we could switch the order around. That's how we do it in other places (first the message, then the exception)

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Thank you. I have update it.

data.name = "Time Series"
## Make a local copy so as not to perfrom inplace operation on the
## original dataset
data_ = data.copy(deep=True)
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copy() without deep should suffice (unless it's there for a specific reason)

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Just a catch all. Should be the same as without deep since we are passing just a dataframe. Do you see any potential issues with including it?

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Updated anyway now...

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setup function in pycaret.time_series is doing inplace operation on index of original dataset tune_model failing in pycaret.time_series
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