Text data is often recorded as a time series with significant variability over time. Some examples of time-series text data include social media conversations, product reviews, research metadata, ...

This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers.

The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases. The book introduces the core libraries essential for working with ...

The embedded Python Processing Engine in InfluxDB 3 allows developers to write Python code that analyzes and acts on time series data in real time. In 2017, I was developing software focused on ...

Eventual's data processing engine Daft was inspried by the founders' experience working on Lyft's autonomous vehicle project.