The main reason to use Python is that you get a lot more options than what's included in most spreadsheets. Spreadsheets are ...

It is very common to analyze time series data, and the date and time stamp values can come in many different formats. Python supports converting from dates to strings and back.

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

Stefanie Molin's new book, “Hands-On Data Analysis with Pandas" is about using the powerful pandas library to get started with machine learning in Python.

Nested data structures are a boon to modeling, storage, and query performance, but pose challenges to traditional BI tools. Here’s how to overcome them ...