This tells pandas to build a pivot table, using the "region" column as the index, and the small, large, and "extra large" ...

What first interested you in data analysis, Python and pandas? I started my career working in ad tech, where I had access to log-level data from the ads that were being served, and I learned R to ...

You don't need to be a data scientist to use Pandas for some basic analysis. Traditionally, people who program in Python use the data types that come with the language, such as integers, strings, ...

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 ...

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.

Data science is an exciting and rapidly growing field that involves extracting insights and knowledge from data. To land a top data science job, it is important to have a solid foundation in key data ...

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 ...

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 ...

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 ...