1, December, 2023

I attempted to fit an ARIMA model to the ‘Total’ column of the dataset using the `ARIMA` function from the `statsmodels` library.
– The order of the ARIMA model was set to (1, 1, 1), indicating a first-order autoregressive model with a first-order differencing and a first-order moving average component.

Encountered a Warning:
– Upon executing the model fitting code, a `ValueWarning` was generated by the `statsmodels` library.
– This warning indicated that the library had to infer the frequency of the time series data. It assumed a daily frequency, denoted as ‘D’.

Understanding the Warning:
– The warning was not an error but a notification. It suggested that the library wasn’t explicitly provided with the frequency of the data and had to make an assumption.
– If the dataset indeed represents daily observations and there are no gaps in the dates, this assumption by the library is appropriate.

Implications of the Warning:
– If the data genuinely has daily measurements and is consistent without missing days, the inference made by the library aligns with the dataset’s structure.
– However, if the dataset follows a different frequency or has irregular intervals, I would need to set the frequency explicitly to match the actual data pattern.


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