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When using forecast_on_df, the input data is required to have three columns: unique_id, ds, and value_name. In the ds column, I tried storing data as integers representing the elapsed seconds or days, instead of using timestamp data of the datetime type.
However, this led to an error during the forecasting process, with the error message indicating that the ds column must contain timestamp data.
I would like to know if there is a way to make forecast_on_df work with data types other than timestamps in the ds column, or if I should consider using a different forecasting method.
The text was updated successfully, but these errors were encountered:
When using
forecast_on_df
, the input data is required to have three columns:unique_id
,ds
, andvalue_name
. In theds
column, I tried storing data as integers representing the elapsed seconds or days, instead of using timestamp data of thedatetime
type.However, this led to an error during the forecasting process, with the error message indicating that the
ds
column must contain timestamp data.I would like to know if there is a way to make
forecast_on_df
work with data types other than timestamps in theds
column, or if I should consider using a different forecasting method.The text was updated successfully, but these errors were encountered: