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.

This online data science specialization is designed for learners with little to no programming experience who want to use Python as a tool to play with data. You will learn basic input and output ...

Python for Everybody: Coursera Python 3 Programming: Coursera Applied Data Science with Python: Coursera Data Science Fundamentals with Python and SQL: Coursera Introduction to Programming with ...

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, ...

Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the 'human-centered' machine-learning infrastructure it uses for building and deploying data-science workflows.

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.

Although Julia is purpose-built for data science, whereas Python has more or less evolved into the role, Python offers some compelling advantages to the data scientist.

Data queries written in Python, a commonly used programming language, can grind data analytics platforms to a crawl, but a new platform may finally solve the Python efficiency problem.

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.