Tuesday Tip #39: Six quick Python tricks 🎯


Hi Reader,

There's a gift for you somewhere in this email... just look for the 🎁 emoji!


πŸ‘‰ Tip #39: Six quick Python tricks

Here's what I'll cover below:

  1. Return the number of unique values
  2. Count values with Counter
  3. Better debugging with f-strings
  4. Return multiple values from a function
  5. Count while looping
  6. Create a dictionary with a comprehension

Let's get started! πŸ‘‡


1️⃣ Return the number of unique values

Need to know the number of unique values in an iterable? Convert it to a set and check the length:

A set is a collection of values (like a list), except it can't contain any duplicate values:

You can use this trick with any iterable, including strings:


2️⃣ Count values with Counter

Need to know how many times each letter appears? Use the Counter class:

Counter objects act like dictionaries, which means that if we want to know how many times 'a' appears, we pass it the 'a' key:

Counters have useful methods like most_common, which returns the specified number of most common values:


3️⃣ Better debugging with f-strings

You've probably used f-strings for substitution:

But f-strings can also help with debugging!

Normally you might print out variables within a function to check that it's working as expected:

But with self-documenting expressions (new in Python 3.8), the output is more useful:

The secret is to end each replacement field with an equals sign!


4️⃣ Return multiple values from a function

Let's say that your function needs to return multiple values:

The function returns a tuple:

But if you want those return values as separate objects, you can use multiple assignment (also known as tuple unpacking):


5️⃣ Count while looping

Let's say that you need to loop through a list:

Sometimes you need to keep track of the index while looping. Don't do this:

Use enumerate instead, which keeps track of the index for you:

It actually generates a tuple, which we're unpacking into i and word!


6️⃣ Create a dictionary with a comprehension

List comprehensions are useful all over the place in Python:

By slightly tweaking the syntax, you can write a dictionary comprehension instead:


πŸ“ˆ Going further

Many of these tricks are taken from my online course, Python Essentials for Data Scientists:

  • The first half of the course will help you build a solid foundation in Python's data structures, operators, functions, control flow, and best practices.
  • The second half of the course will challenge you with a 7-part project, in which you'll practice everything you've learned plus dive deeper into intermediate Python topics.

🎁 Just for fun, I'm giving readers of Tuesday Tips a 25% discount on this course for the next week. Use code TUESDAY25 at checkout! 🎁


πŸ‘‹ Until next time

Did you like this week’s tip? Please send it to a friend or share this link on social. It really helps me out! πŸ™Œ

See you next Tuesday!

- Kevin

P.S. Uber's new "Save with Ads" option (parody) πŸ˜‚

Did someone AWESOME forward you this email? Sign up here to receive Data Science tips every week!

Learn Artificial Intelligence from Data School πŸ€–

Join 25,000+ intelligent readers and receive AI tips every Tuesday!

Read more from Learn Artificial Intelligence from Data School πŸ€–

Hi Reader, This week, I've got a short tip about AI agents, followed by some Data School news... πŸ‘‰ Tip #56: What are AI agents? Google is calling 2025 "the agentic era," DeepLearning.AI says "the agentic era is upon us," and NVIDIA's founder says "one of the most important things happening in the world of enterprise is agentic AI." Clearly AI agents are a big deal, but what exactly are they? Simply put, an AI agent is an application that uses a Large Language Model (LLM) to control its...

Hi Reader, Last week, I launched a brand new course: Build an AI chatbot with Python. 120+ people enrolled, and a few have already completed the course! πŸ‘ Want to join us for $9? πŸ‘‰ Tip #55: Should you still learn to code in 2025? You’ve probably heard that Large Language Models (LLMs) are excellent at writing code: They are competitive with the best human coders. They can create a full web application from a single prompt. LLM-powered tools like Cursor and Copilot can autocomplete or even...

Hi Reader, The Python 14-Day Challenge starts tomorrow! Hope to see you there 🀞 πŸ‘‰ Tuesday Tip: My top 5 sources for keeping up with AI I'll state the obvious: AI is moving incredibly FAST πŸ’¨ Here are the best sources I follow to keep up with the most important developments in Artificial Intelligence: The Neuron (daily newsletter) My top recommendation for a general audience. It’s fun, informative, and well-written. It includes links to the latest AI news and tools, but the real goldmine is...