Python Tutorial: Introduction to packages & documentation

Want to learn more? Take the full course at https://learn.datacamp.com/courses/software-engineering-for-data-scientists-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- You've now learned some important software engineering concepts. We're now going to look at how beneficial these concepts can be as a user of python open source software. Namely, we're going to investigate packages. We'll cover how to install packages from the 'Python Package Index', and we'll see how these packages leverage software engineering concepts we've covered. Later in the course, we'll talk more about the 'Python Package Index', or PyPi for short, but for now, all you need to know is that PyPi gives us an easy platform to leverage published packages. Thanks to packages being modular, we can easily install them from PyPi using a tool called pip. pip is actually a recursive acronym that stands for 'Pip Installs Packages', and it does just that. The practice of leveraging pip install can save a lot of time and lets us avoid reworking problems that have already been solved and packaged by some smart members of the python community. If we wanted to install the popular package numpy we conveniently use the command pip install numpy. Barring any unexpected issues we now have numpy installed and we can leverage all the benefits that come with this powerful package. Note that pip will also install a package's dependencies as long as they're on PyPi. However, in some cases, a package's dependencies might require a little extra work. So how do we leverage numpy's features? Again thanks to good software engineering, numpy has excellent documentation available both on the web and in the package itself. Here we'll focus on the documentation shipped with the package. Let's say we want to count the number of work days in the year 2020. numpy provides the function, busday_count, that can help us accomplish this, but how do