Plurrrr

Whenever I work on a local or remote Kubernetes cluster, I tend to want to connect to my application to send it a HTTP request or something similar.

One of the most basic analysis functions is grouping and aggregating data. In some cases, this level of analysis may be sufficient to answer business questions. In other instances, this activity might be the first step in a more complex data science analysis. In pandas, the groupby function can be combined with one or more aggregation functions to quickly and easily summarize data. This concept is deceptively simple and most new pandas users will understand this concept. However, they might be surprised at how useful complex aggregation functions can be for supporting sophisticated analysis.

This article will quickly summarize the basic pandas aggregation functions and show examples of more complex custom aggregations. Whether you are a new or more experienced pandas user, I think you will learn a few things from this article.

This article is a tutorial that’s meant to cover Python packages, modules, and import statements in enough depth for a beginner to intermediate Python developer. The goal is to answer common questions people have about these topics. We also will strive to explain everything clearly and step by step, to show you errors you might see along the way and how to solve them, and to illustrate how things work with simple examples.

Pete and Debbie are both about to turn 40, their kids hate each other, both of their businesses are failing, they're on the verge of losing their house, and their relationship is threatening to fall apart.