How do I split time series data for training and testing?

How do I split time series data for training and testing?

To split time series data, you typically use a time-based split rather than a random split. You can reserve the last portion of your data for testing.

What percentage of data should I use for testing?

A common practice is to use 20% of your data for testing, but it can vary based on the dataset size and the specific use case.

Should I shuffle the data before splitting?

No, you should not shuffle time series data as it can disrupt the temporal order, which is crucial for training.

Can you give an example of how to implement this in Python?

Sure! You can use pandas to split your data. For example:

train = data[:-int(len(data) * 0.2)]
test = data[-int(len(data) * 0.2):]