In the world of data analysis and manipulation, Python has long been the go-to language. With extensive and user-friendly libraries like NumPy, pandas, and PySpark, there’s a solution available for almost any data-driven task. Among these libraries, one name that’s been generating a significant amount of buzz lately is Polars. Polars is a high-performance DataFrame library, designed to provide fast and efficient data processing capabilities. Inspired by the reigning pandas library, Polars takes things to another level, offering a seamless […]

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Mastering While Loops Python’s while loop enables you to execute a block of code repeatedly as long as a given condition remains true. Unlike for loops, which iterate a known number of times, while loops are ideal for situations where the number of iterations isn’t known upfront. Loops are a pretty useful construct in […]

Interactive Quiz ⋅ 11 QuestionsBy Leodanis Pozo Ramos Share In this quiz, you’ll test your understanding of Python while Loops: Repeating Tasks Conditionally. The while keyword is used to initiate a loop that repeats a block of code while a condition is true. A while loop works by evaluating a condition at the start of each iteration. If the condition is true, then the loop executes. Otherwise, it terminates. The quiz contains 11 questions and there is no time limit. […]

Interactive Quiz ⋅ 15 QuestionsBy Bartosz Zaczyński Share In this quiz, you’ll test your understanding of Bytes Objects: Handling Binary Data in Python. By working through this quiz, you’ll revisit the key concepts related to this low-level data type. The quiz contains 15 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score is 100%. Good luck! Related Resources

Interactive Quiz ⋅ 10 QuestionsBy Ian Eyre Share In this quiz, you’ll test your understanding of the techniques covered in How to Work With Polars LazyFrames. By working through the questions, you’ll review your understanding of why LazyFrames are an efficient and preferred way of working in Polars. You’ll need to do some research outside of the tutorial to answer all the questions, so let this challenge take you on a learning journey. The quiz contains 10 questions and there […]

A Polars LazyFrame provides an efficient way to handle large datasets through lazy evaluation. Unlike traditional DataFrames, LazyFrames don’t contain data but instead store a set of instructions known as a query plan. Query plans perform operations like predicate and projection pushdown, ensuring only necessary rows and columns are processed. LazyFrames also support the parallel execution of query plans, further enhancing performance. By the end of this tutorial, you’ll understand that: A Polars LazyFrame allows efficient data processing by storing […]

Python has a few important naming conventions that are based on using either a single or double underscore character (_). These conventions allow you to differentiate between public and non-public names in APIs, write safe classes for subclassing purposes, avoid name clashes, and more. Following and respecting these conventions allows you to write code that looks Pythonic and consistent in the eyes of other Python developers. This skill is especially useful when you’re writing code that’s intended for other developers […]

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Sorting Data With Python Sorting in Python is a fundamental task that you can accomplish using sorted() and .sort(). The sorted() function returns a new sorted list from the elements of any iterable, without modifying the original iterable. On the other hand, the .sort() method modifies a list in place and doesn’t return a […]