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.

The data manipulation API resembles Pandas, but adds .rows() and .cols() accessors to make it easy to do things like sort a DataFrame, filter by column values, alter data according to criteria, or ...

Introduction to Python for Data Analysis Recall that R is a statistical programming language—a language designed to do things like t -tests, regression, and so on. The core of R was developed during ...

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.