Python Libraries for Data Analysis and Visualization

📚 Day 30/130 — Python Variables Today in my Python Programming Series, let’s understand one of the most important basics 👇 🔹 What is a Variable? A variable is a container used to store data values in a program. 🔹 Simple Understanding: 👉 Variable = Name that stores a value 🔹 Example: x = 10 name = "Gowthami" 👉 Here, "x" stores a number and "name" stores text 🔹 Rules for Variables: • Must start with a letter or underscore (_) • Cannot start with a number ❌ • No spaces allowed • Case-sensitive (name ≠ Name) 🔹 Types of Values Stored: • Integer → 10 🔢 • String → "Hello" 📝 • Float → 3.14 📊 • Boolean → True/False ✅ 🔹 Why Variables are Important? • Store data for reuse • Make programs dynamic • Improve readability 🔹 Key Idea: 👉 Variables help us store and use data easily in programs 📊See the diagram below for better understanding 📌 Tomorrow’s Topic: 👉 Python Data Types #Python #Programming #Coding #TechLearning #LearningInPublic #Students #Developer #100DaysOfCode

Modules are one of the most powerful features in Python that help you write clean, reusable, and organized code. * A module is simply a file that contains Python code (functions, variables, or classes) which you can reuse in other programs. * Why use modules? * Code reusability * Better organization * Easy maintenance * Faster development 🔧 Example: # math_module.py def add(a, b): return a + b # main.py import math_module result = math_module.add(5, 3) print(result) * Instead of writing the same logic again and again, modules allow you to write once and use anywhere. * Python also provides built-in modules like: * math * random * datetime #Python #Programming #DataAnalytics #Coding #Learning #PythonBasics

🔁 Python Revision – Sets Continuing my Python fundamentals revision 🐍 In this session, I focused on: ✔️ Sets (creation and properties) ✔️ Unique elements and unordered nature ✔️ Set methods (add, remove, discard, etc.) ✔️ Set operations (union, intersection, difference) Practiced using sets to handle unique data and perform efficient operations like finding common or different elements between datasets. Documented my practice in a Jupyter Notebook and shared it as a PDF to track my progress. Understanding sets is helping me work better with data and avoid duplicates 📊 Next: dictionaries and real-world data handling 🚀 #Python #Revision #Sets #Programming #DataAnalytics #LearningJourney #Coding

5 things you can do with Python now: 1. Automate Excel 2. Replace old VBA 3. Interact with APIs 4. Explore market data 5. Manipulating CSV files When learning Python, forget puzzles. Do something useful.

Deep Dive into Python Dictionaries yesterday, I explored key concepts of Python Dictionaries and strengthened my understanding of how they work in real-world scenarios 💡 🔹 Adding data to an empty dictionary 🔹 Heterogeneous data for both keys and values 🔹 Accessing dictionary data using keys 🔹 Keys can be any immutable type 🔹 Duplicate keys are not allowed but values can be duplicated 🔹 Dictionary is mutable 🔹 Another representation of dictionary using dict() 🔹 Deleting elements from dictionary 📌 Key Insight: Dictionaries are one of the most flexible and powerful data structures in Python, making data handling efficient and dynamic. Consistency is the key — learning something new every day and moving one step closer to becoming a better developer 💻🔥 #Globalquesttechnologies #GR Narendra Reddy #Python #LearningJourney #100DaysOfCode #Programming #DataStructures #Coding #DeveloperJourney #PythonBasics

Deep Dive into Python Dictionaries yesterday, I explored key concepts of Python Dictionaries and strengthened my understanding of how they work in real-world scenarios ◆ Adding data to an empty dictionary ◆ Heterogeneous data for both keys and values ◆ Accessing dictionary data using keys ◆ Keys can be any immutable type Duplicate keys are not allowed but values can be duplicated ◆ Dictionary is mutable ◆ Another representation of dictionary using dict() ◆ Deleting elements from dictionary Key Insight: Dictionaries are one of the most flexible and powerful data structures in Python, making data handling efficient and dynamic. Consistency is the key - learning something new every day and moving one step closer to becoming a better developer #Globalquesttechnologies #GR Narendra Reddy #Python #Learning Journey #100DaysOfCode #Programming #DataStructures #Coding #Developer Journey #PythonBasics

🚀 Python Learning Journey – Day 26 Today, I learned about PDBC (Python Database Connectivity) and how Python interacts with databases. Here’s what I explored: ✅ What PDBC is and why it is used ✅ Connecting Python with a database ✅ Executing SQL queries using Python ✅ Performing operations like create, insert, update, delete ✅ Using cursor and connection objects This helped me understand how Python works with real-world data stored in databases. Step by step, moving towards building data-driven applications 💪 #Python #LearningJourney #Day26 #PDBC #Database #SQL #Coding #KeepLearning

🚀 Exploring Python Data Structures: The Building Blocks of Efficient Code In Python, choosing the right data structure is key to writing clean, efficient, and optimized programs. Here’s a quick overview of the four fundamental data structures every developer should master: 🔹 List Ordered, mutable, and allows duplicate elements. Ideal for storing collections that may change over time. 🔹 Tuple Ordered but immutable. Useful when data integrity is important and values should not be modified. 🔹 Set Unordered collection with no duplicate elements. Perfect for operations like union, intersection, and removing duplicates. 🔹 Dictionary (Dict) Stores data in key-value pairs. Highly efficient for fast lookups and structured data representation. 💡 Understanding when and where to use each of these structures can significantly improve both performance and readability of your code. 📌 Keep learning, keep building! Python offers endless possibilities when you master its core concepts. #Python #Programming #DataStructures #Coding #SoftwareDevelopment #LearningJourney

🚀 Project Completed: Expense Tracker using Python I developed a command-line application to track daily expenses using Python and CSV file handling. 🔹 Features: ✔ Add and store expenses ✔ View all transactions ✔ Calculate total spending 🔗 GitHub Repository: https://lnkd.in/gQ4nwR95. This project helped me understand file handling and build a real-world application. #Python #DataScience #BeginnerProject #Learning

Unlock the power of APIs and master regular expressions in Python! In this lecture, you'll learn how to make API requests to fetch data from the web, handle JSON responses, and use Python's requests library. We'll also dive into regular expressions (regex) to efficiently search, match, and manipulate text data. Perfect for beginners and those looking to enhance their data processing skills. #Python #API #Regex #DataScience #Programming #Tutorial https://lnkd.in/gCZQdtnb