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

The data science skills gap has been well documented here and elsewhere. However, there appears to be a mismatch between talent supply and demand. Curiously, U.S. job hunters are most interested in ...

Useful Libraries for Data Analysis Whenever I start a data analysis project, I like to have at a minimum the following libraries installed: Requests. Matplotlib. Requests-html. Pandas.

Python data science essential: Dask 2021.07.0 Processing power is cheaper than ever, but it can be tricky to leverage it in the most powerful way—by breaking tasks across multiple CPU cores ...

That’s not to say tools don’t matter; today’s data analyst absolutely needs to be able to use at least a few of the most common tools such as Excel, SQL, Tableau, Power BI, R or Python. Such ...

This post is designed to spare other SEO pros the same fate. Within it, we’ll cover the Python equivalents of the most commonly used Excel formulas and features for SEO data analysis – all of ...

However, Python’s methods for parallelizing operations often require data to be serialized and deserialized between threads or nodes, while Julia’s parallelization is more refined.