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.

Not necessarily for the data-science and machine-learning communities built around Python extensions like NumPy and SciPy, but as a general programming language.

Granted, Python is certainly not perfect. No language is. “Due to its interpreted nature, Python does not have the most efficient runtime performance,” said Story.

As programming languages go, there’s no denying that Python is hot. Originally created as a general-purpose scripting language, Python somehow became the most popular language for data science. But is ...

Translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays). Flexible binding to different versions of Python including virtual ...

Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).

Python has never been as speedy as C or Java, but several projects are in the works to get the lead out of the language.

Java has a lot going for it, but it's not the top language for data science. Java professionals may want to familiarize themselves with Python or R for data science workflows.

As part of our mini-series on programming languages, James Fransham makes the case for R being the best language for data journalism and our team shares their tips for getting started with it.