create dataframe format after tabularize_univariate_datetime

[Kevin-Chen0]

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Is your feature request related to a problem? Please describe.

In the neuralprophet.time_dataset.tabularize_univariate_datetime() method (see test_time_dataset() example of how it's used), it outputs inputs (a dict of keys time and lags) and targets (an ndarray of dim n_rows and n_timesteps). This by itself is not easy to be used.

Describe the solution you'd like

Combine inputs and targets into a dataframe, which is just the original time-series but tabularized. For example, the AIR_FILE is an univariate time-series that only contains ds and y. After tabularization with only n_lags=3, I expect the output to be a dataframe with only the columns ds, y, y-1, y-2, y-3. Using the values from the original time-series without any traces of normalization, standardization, or any other transformations.

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Additional context

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