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docs: Add time series analysis notebook - #2328
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| # Auto-convert Date to datetime for hourly/per_minute frequency | ||
| if self.data_frequency in ["hourly", "per_minute"]: | ||
| timestamp_col = X.columns[0] | ||
| if "date" in X[timestamp_col].dtype.name: |
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Non-rhetorical question: What if the the column has dtype "datetime"? Is it necessary that we still cast that column as datetime, and warn that the column has "date" type?
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The error would not exist if column has a dtype "datetime". In this case, no cast/warning will exist.
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Hmmm, in that case the expression
"date" in X[timestamp_col].dtype.name
would still evaluate to True, right? Is that something we want?
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Thanks for suggestion. I believe Garrett has a fair point. Thus I revert the code change. Now this PR only include the notebook changes.
| timestamp_col = X.columns[0] | ||
| if "date" in X[timestamp_col].dtype.name: | ||
| warnings.warn( | ||
| f"Converting Date column '{timestamp_col}' to datetime for " |
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It seems not make sense to convert and predict with hourly and minute data frequency to date granularity. We should just let it emit errors.
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It is a fair point. I revert the code change and update notebook
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Adds a new notebook, timeseries_analysis.ipynb, to provide a comprehensive walkthrough of time series forecasting with TimesFM and ARIMAPlus. The notebook covers data loading, preprocessing, model training, and visualization of results for both single and multiple time series.
Fixes #<466169940> 🦕