Simple function to turn a time series into an ML ready dataset.

Originally sourced from: Machine Learning Mastery

This Python function named takes a univariate or multivariate time series and frames it as a supervised learning dataset.

The function takes four arguments:

• data: Sequence of observations as a list or 2D NumPy array. Required.
• n_in: Number of lag observations as input (X). Values may be between [1..len(data)] Optional. Defaults to 1.
• n_out: Number of observations as output (y). Values may be between [0..len(data)-1]. Optional. Defaults to 1.
• dropnan: Boolean whether or not to drop rows with NaN values. Optional. Defaults to True.

The function returns a single value:

• return: Pandas DataFrame of series framed for supervised learning.