Based on a recent Stack Overflow developer survey, more data scientists are using Python than ever. It’s become the most popular language for data analysis. Python’s ecosystem includes many data science libraries, and some folks that are learning need help navigating the space and choosing the right tools.
With that in mind, let’s explore some common situations you’ll face when using Python for data science. We’ll look at exception handling, converting objects between NumPy and pandas, working with datetime types, and more. Let’s dive in!