Python String Methods: Practice Notes

🐍 Day 8 of Learning Python Topic: Multiple-Valued Datatypes – Tuple Today I learned about Tuples in Python — one of the important multiple-valued (collection) data types. 🔹 What is a Tuple? A tuple is a collection that can store multiple values in a single variable. It is: ✔️ Ordered ✔️ Allows duplicates ❌ Immutable (cannot be changed after creation) 🔹 Why use Tuples? • Faster than lists • Protects data from accidental changes • Useful for fixed data like coordinates, days, etc. 🔹 Example: Copy code Python my_tuple = (10, 20, 30, 40) print(my_tuple) 🔹 Accessing elements: Copy code Python print(my_tuple[1]) # Output: 20 Learning Python step by step and enjoying the journey 🚀 Excited for what’s next! #Python #PythonLearning #100DaysOfCode #DataTypes #Tuple #CodingJourney #LearningDaily

Added quite a few functions to my excel_in_python Python library yesterday. Purpose of the library is twofold: 1. For people familiar with Excel ways of working, you can read the code and understand how those functions might be implemented in Python. You can also use them as a bridge between your Excel expertise and your Python learning. 2. Some Excel functions have no direct simple equivalent in Python (looking at you YEARFRAC and DAYS360), so some of these may help you along your way when creating financial models in Python that use custom rules. Disclaimer: the tests do pass, but I haven't gone hand by hand verifying the output against equivalent function calls in Excel. That's a longer job which is ongoing and if you'd like to help and collaborate on this project, let me know! https://lnkd.in/gT6eJaKf #excel #python #data #analytics

Combining Sets in Python: Union Operator vs. Union Method Explained In Python, sets are powerful collections designed to hold unique elements, making them ideal for various mathematical operations such as unions. When you need to combine two sets, you can choose between two common approaches: the union operator (`|`) or the `union()` method. Both methods will produce a new set that includes all elements from both sets and automatically removes any duplicates. Understanding how sets handle duplicates is crucial. For example, if set A contains the numbers 1, 2, and 3 while set B contains 3, 4, and 5, the combination of these sets results in a single set containing 1, 2, 3, 4, and 5. Here, the number 3 appears in both sets but is only displayed once in the final combined output, demonstrating the uniqueness property of sets. Choosing between the union operator and the method typically comes down to personal preference. The union operator tends to be more concise, while the method can be clearer for beginners or when emphasizing the action being performed. Understanding these operations is essential for effective data manipulation, whether you're performing data analysis or working on application development. Quick challenge: What will be the output when you combine `set_a` with `{6, 7}` using the union operator? Explain your reasoning. #WhatImReadingToday #Python #PythonProgramming #Sets #DataStructures #Programming

🚀 Day 12 – Learning Dictionaries in Python 🐍 Today I explored Python Dictionaries, a powerful data structure used to store data in key–value pairs. Key things I learned: ✅ Creating dictionaries to organize related data ✅ Accessing values using keys ✅ Updating and adding new key–value pairs ✅ Looping through dictionaries for dynamic data handling For example, instead of using indexes, dictionaries let me work with meaningful keys like "name", "age", or "role"—making code clearer and more practical for real applications. 📌 Slowly building logic, one data structure at a time. #Python #PythonDictionary #DataStructures #Consistency

LEARNING PYTHON Why Python Lists are a beginner’s superpower 🐍 • Lists let you store multiple values in a single variable. • They are ordered,so elements keep their position. • Lists are mutable – you can add, remove, or update values anytime. • Duplicates are allowed, which is useful for real-world data. • Perfect for loops, algorithms, and data processing. • Commonly used in projects, interviews, and competitive coding • One of the most important Python datatypes to master early #Python #PythonBasics #DataTypes #Coding #LearningPython

Python Sets — Why They’re More Useful Than You Think In simple words: A set in Python is a collection that: • Stores only unique values. • Doesn’t maintain order. • Allows fast membership checks. Why it matters: - Removing duplicates becomes easy. - 'in' operations are much faster than lists. - Set operations like union & intersection are powerful in real-world logic. If you're serious about writing cleaner Python code, sets are essential. Which set operation do you use most in real projects? #Python #LearnPython #DataStructures #BackendDevelopment #PythonDeveloper #Coding

🚀 Day 10 – Learning Lists in Python 🐍 Today I explored Python Lists, one of the most powerful and commonly used data structures. I learned how lists help in: ✅ Storing multiple values in a single variable ✅ Accessing elements using indexing ✅ Modifying data (add, update, remove elements) ✅ Iterating through data using loops For example, instead of handling values one by one, a list lets me manage and process data efficiently—making code more readable and scalable. 📌 Step by step, turning concepts into confidence. #Python #PythonLists #DataStructures

Learning Python one concept at a time 🐍 Python Basics — Day 7🐍 Python Data Collections — Part 2 🐍 📌 Concept: Tuple & Set Where data starts getting organized 📦 🔹 Tuple → ordered & unchangeable 🔹 Set → unordered & unique values only The key lesson beginners miss 👇 Tuples protect data. Sets remove duplicates. Understanding when to use tuple vs set helps you write cleaner, smarter code. Sharing simple explanations + practice questions to learn by doing ✍️ 💬 Comment “DONE” after solving the practice questions If you’re learning Python step by step, let’s connect 🤝 #Python  #PythonBasics  #Learning  #Beginners  #Upskilling   #TechLearning  #CareerGrowth #AI

Today, I focused on learning Python Dictionaries, an essential data structure used for efficient data storage and retrieval through key–value pairs. Key concepts I covered include: • Creating and updating dictionaries • Accessing values using keys and the .get() method • Adding and removing elements using assignment and .pop() • Iterating through keys, values, and key–value pairs using .keys(), .values(), and .items() • Valid data types for dictionary keys (immutable types only) Additionally, I explored: Sorting dictionaries by keys Sorting dictionaries by values using lambda functions Practical Implementation: I implemented a program to count the frequency of unique characters in a string using dictionaries — a common real-world data processing task. Example: Input → rrsssstttt Output → { "r": 2, "s": 3, "t": 4 } This session helped reinforce how dictionaries improve performance and code readability in Python. #Python #DataAnalytics #LearningJourney #ProgrammingFundamentals #ContinuousLearning #PythonDictionaries

Learning 🐍: 🔹 Python Built-in Functions: ord(), chr(), and bin() When working with characters and numbers in Python, these three built-in functions are very useful! 🔸bin() Function 👉 bin() converts an integer number into binary format. 🔸ord() Function 👉 ord() returns the ASCII (or Unicode) value of a given character. 🔸 2️⃣ chr() Function 👉 chr() returns the character for a given ASCII (or Unicode) value. 💡 ord() and chr() are opposite functions. 🔥 Quick Summary Function Purpose ord() Character ➝ ASCII value chr() ASCII value ➝ Character bin() Integer ➝ Binary string #Python #PythonProgramming #DataAnalytics #CodingJourney