Python Math Domain Error (How to Fix This Stupid Bug)

You may encounter a special ValueError when working with Python’s math module. Python raises this error when you try to do something that is not mathematically possible or mathematically defined. To understand this error, have a look at the definition of the domain: “The domain of a function is the complete set of possible values … Read more

Python Regex Match

Why have regular expressions survived seven decades of technological disruption? Because coders who understand regular expressions have a massive advantage when working with textual data. They can write in a single line of code what takes others dozens! This article is all about the re.match() method of Python’sΒ re library. There are two similar methods to … Read more

Minimum Viable Product (MVP) in Software Development — Why Stealth Sucks

This chapter from my upcoming book “The Art of Clean Code” (NoStarch 2022) teaches you a well-known but still undervalued idea. The idea is to build a minimum viable product (in short: MVP) to test and validate your hypotheses quickly without losing a lot of time in implementation. In particular, you’ll learn how to apply … Read more

np.shape()

This tutorial explains NumPy’s shape() function. Return the shape of an array or array_like object a. Argument Data Type Description a array_like NumPy array or Python list for which the shape should be returned. If it is a NumPy array, it returns the attribute a.shape. If it is a Python list, it returns a tuple … Read more

Python Regex Fullmatch

Why have regular expressions survived seven decades of technological disruption? Because coders who understand regular expressions have a massive advantage when working with textual data. They can write in a single line of code what takes others dozens! This article is all about the re.fullmatch(pattern, string) method of Python’s re library. There are three similar methods … Read more

np.polyfit() — Curve Fitting with NumPy Polyfit

The np.polyfit() function, accepts three different input values: x, y and the polynomial degree. Arguments x and y correspond to the values of the data points that we want to fit, on the x and y axes, respectively. The third parameter specifies the degree of our polynomial function. For example, to obtain a linear fit, … Read more

Python Regex Compile

The method re.compile(pattern) returns a regular expression object from the pattern that provides basic regex methods such as pattern.search(string), pattern.match(string), and pattern.findall(string). The explicit two-step approach of (1) compiling and (2) searching the pattern is more efficient than calling, say, search(pattern, string) at once, if you match the same pattern multiple times because it avoids … Read more

How to Calculate the Column Variance of a DataFrame in Python Pandas?

Want to calculate the variance of a column in your Pandas DataFrame? In case you’ve attended your last statistics course a few years ago, let’s quickly recap the definition of variance: it’s the average squared deviation of the list elements from the average value. You can calculate the variance of a Pandas DataFrame by using … Read more

Python Function Call Inside List Comprehension

Question: Is it possible to call a function inside a list comprehension statement? Background: List comprehension is a compact way of creating lists. The simple formula is [expression + context]. Expression: What to do with each list element? Context: What elements to select? The context consists of an arbitrary number of for and if statements. … Read more

Python Regex Flags

In many Python regex functions, you see a third argument flags. What are they and how do they work? Flags allow you to control the regular expression engine. Because regular expressions are so powerful, they are a useful way of switching on and off certain features (e.g. whether to ignore capitalization when matching your regex). … Read more