Python: Beginner to Expert
John Lockwood 
Most Python developers know about dictionaries, lists, and tuples — three workhorse collections that are so useful that they repeatedly appear in Python code. Compared to other languages, these essential collections have such excellent support in the language that they feel almost like native types. For example, they all have special constructors and operators unique … Read more
Developers make all sorts of mistakes. We wouldn’t have debuggers, QA engineers, code review, automated unit testing, and the rest if we were perfect. One mistake many developers make early in their career is applying the label “Junior Developer” to themselves. Move over, “heartbreak of psoriasis”. For real beginner pain, nothing tops the heartbreak of … Read more
Pandas is a hugely popular tool for data analysis and machine learning. It builds on the strengths and speed of Numpy to allow for mixed column types in a two-dimensional DataFrame that is indexable by column or row. As popular as it is, Pandas offers so many different ways to do things that it helps … Read more
Working with spreadsheets in Python on your local machine is relatively simple. For example, Pandas can open a spreadsheet into a DataFrame using read_excel. To do this, Pandas relies on another package for reading and writing spreadsheets, openpyxl. Once you’ve installed this package using your favorite package manager, the process is straightforward. To the extent … Read more
Jupyter Notebook is a popular development environment that supports Python and other programming languages. It is a browser-based environment, which is excellent since you can connect to notebooks running either online or locally. Our goal in this article is two-fold and reflects the article’s division into two parts: Part One: Up and Running Running Online … Read more
Many Python developers consider generators an advanced topic because they are less well known than sequence types such as lists, arrays, and strings. Also, because the syntax for generator functions can appear strange at first, many developers don’t take the time to learn about them at all. That’s a shame, really, because, in some instances, … Read more
Python lists are one of its most flexible and widely used data types. This article is a beginner’s guide to Python lists, but like everything in programming, remembering what you learned requires sufficient early practice. With this in mind, in addition to the lesson, we also feature several exercises at the end that you can … Read more
One of the features I love most about working in Jupyter Lab and Jupyter Notebooks is that it supports visual, interactive experiments with code and documenting what you’re doing in Markdown. (If you need a more general primer on using Jupyter, check out Jupyter Notebook: A Complete Introduction). With tools like Binder or CoCalc, it’s … Read more
Have you learned some NumPy, but now your learning has stalled because you don’t have any practice questions or exercises to review what you’ve learned? This practice set of forty-five NumPy examples features NumPy questions in varying degrees of difficulty. Some are very common examples of NumPy arrays, others get into some more advanced features. … Read more
One of those questions that every Python developer wonders about at some point are those weird extra directories and files they’ll see crop up from time to time. Setting aside __init__.py for a moment, sometimes you’ll see directories you didn’t create: __pycache__, filled with files with a .pyc extension that have the same root filename … Read more
