How do I preprocess time series data for analysis?

How do I preprocess time series data for analysis?

Preprocessing time series data involves several steps like handling missing values, normalization, and feature extraction.

What techniques can I use to handle missing values?

You can use techniques like interpolation, forward filling, or even machine learning models to predict missing values.

Should I normalize my data before analysis?

Yes, normalizing your data can help improve the performance of many algorithms, especially those sensitive to scale.

What features should I extract from time series data?

Common features include trend, seasonality, and lagged values, which can provide valuable insights for modeling.