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”.

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.

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

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

Style analysis helps you interpret how funds are likely to behave. Copy and paste these code snippets to evaluate investments for style drift.

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

According to statistics from Liepin.com, 90% of big data positions require at least one programming language to be mastered. From a data analysis assistant earning 8k a month to a data scientist ...

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 ...