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My dataset comprises stock data, and due to some missing calender days, the timestamps in the dataset are not uniformly spaced. Is there a method to handle non-uniformly spaced data in models?
When using the dataset, I encountered the error 'AssertionError: Dataframe index is not uniformly spaced. If your dataframe contains data from multiple series in the same column ("long" format), consider constructing the dataset with PandasDataset.from_long_dataframe instead.
The text was updated successfully, but these errors were encountered:
Is there a method to handle non-uniformly spaced data in models?
not sure if there exists any in the model classes, but i tackled this at data prep stage e.g. by following an example provided in the documentation maybe this would be useful
--- update
came across this, might be related/of-interests for future: #1973
My dataset comprises stock data, and due to some missing calender days, the timestamps in the dataset are not uniformly spaced. Is there a method to handle non-uniformly spaced data in models?
When using the dataset, I encountered the error 'AssertionError: Dataframe index is not uniformly spaced. If your dataframe contains data from multiple series in the same column ("long" format), consider constructing the dataset with PandasDataset.from_long_dataframe instead.
The text was updated successfully, but these errors were encountered: