Data Science

Simplifying data analysis for everyone — Motivation Pivoting and Grouping operations are fundamental to every typical tabular data analysis process. The pivot_table() and groupby() method stands among one of the most commonly used methods in Pandas. Used primarily for understanding categorical data, Grouping lets you compute statistics for individual groups in the data.

Coming from an analytics & data science background, I used to see writing tests as something painful. I knew that it was important, but I never knew where to start and always procrastinated until the end of the project. What’s more boring than testing a piece of code that already…

And how they stack-up to the best SFF books of the past 50 years — As yet another year comes to a close, so has the science fiction & fantasy books award season. The Hugos, Nebulas, World Fantasy Awards, Sir Arthur C. Clarke, and dozens more have all chosen their champions. This means many great books were recognized and will rise in the public ethos…

Everything you must know about being a data analyst! You might not believe it, but more than 8 billion data analysts live on the earth! The logic is very simple. …

How StaticFrame can outperform Pandas by embracing NumPy array views — A NumPy array is a Python object that stores data in a contiguous C-array buffer. The excellent performance of these arrays comes not only from this compact representation, but also from the ability of arrays to share “views” of that buffer among many arrays. NumPy makes frequent use of “no-copy”…

Introduction At Homebound, the Machine Learning & Pricing team is responsible for developing and maintaining an Automated Valuation Model (AVM) to accurately predict the value of a property. Dubbed here as the Homebound Valuation Model (HVM), characteristics such as the size of a home, property view, proximity to major roads…