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.

In contrast, Python follows a multiprogramming paradigm, which makes it easy for developers to write concise code using syntactic sugar. Python was not built specifically for data science workloads, ...

Students in the Bridge to Data Science Pathway may be required to complete one or more of the following courses (up to 7 credits).Courses should be taken in the first year and are subject to Graduate ...

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

In this section, we use the dataset cargame.csv to demonstrate how to create basic graphical displays in Python. Below is the scenario for the data: A toy company has four types of vehicles for sale: ...

His argument against Python is that a person using it for data science needs to learn about extra Python packages, like NumPy, which brings Matlab-like data-analysis powers to Python.

Find out what makes Python a versatile powerhouse for modern software development—from data science to machine learning, systems automation, web and API development, and more.

What are some use cases for which it would be beneficial to use Haskell, rather than R or Python, in data science? This question was originally answered on Quora by Tikhon Jelvis.