The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

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.

It is a handy tool for keeping a record of data explorations, creating charts, styling text and sharing the results of that work. For data analysis, the cornerstone package in Python is “Pandas”.

Still using Excel for your data analysis? Learn how to leverage Python so you can work with larger datasets and automate repetitive tasks.

Already using NumPy, Pandas, and Scikit-learn? Here are five more powerful Python data science tools that deserve a place in your toolkit.

However, in recent years the open source community has developed increasingly-sophisticated data manipulation, statistical analysis, and machine learning libraries for Python. We are now at the point ...

Python libraries like Pandas, NumPy, SciPy, and Matplotlib streamline data cleaning, statistical analysis, and visualization directly within Excel.

Python’s Pandas library allows for advanced data manipulation, statistical analysis, and exploration directly within Excel, streamlining workflows.