At Springboard, we pair mentors with learners in data science. We often get questions about whether to use Python or R – and we’ve come to a conclusion thanks to insight from our community of mentors ...

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis. Hoping to settle ...

With the emergence of the era of Big Data, frameworks like Hadoop arose and the focus of the enterprise shifted to which was processing this data. This is where data science came into the picture.

The advantage of Python is that you can apply operations to larger datasets with hundreds, even thousands, of data points ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your toolkit. Python’s rich ecosystem of data science tools is a big draw for ...

Data science and machine learning professionals have driven adoption of the Python programming language, but data science and machine learning are still lacking key tools in business and has room to ...

Java can handle large workloads, and even if it hits limitations, peripheral JVM languages such as Scala and Kotlin can pick up the slack. But in the world of data science, Java isn't always the go-to ...

The language R is in the midst of a sizzling resurgence this summer. One might hypothesize that this growth is coming at the expense of Python, by far the dominant language for data science. But some ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to ...

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. Researchers ...