CoursesCourse Overview →Data Visualization With Python - Course Overview →How to Set Up Visual Studio Code →Install PostgreSQL on MacOS →Install PostgreSQL on Windows →Installing Python on MacOS →Installing Python on Windows →Lesson 1 - Introduction to Object-Oriented Programming →Lesson 1 - Introduction to Pandas and Series →Lesson 1 - NumPy Essentials and 1D Arrays →Lesson 1 - Programming in Python →Lesson 1 - Understanding Graphs and Coordinates →Lesson 1: Introduction to Software Engineering →Lesson 10 - Apply, Map, and Transform Functions →Lesson 10 - Creating Bar Plots →Lesson 10 - Regular Expressions for Text Processing →Lesson 10 - Working With Files →Lesson 10: Behaviour-Driven Development →Lesson 11 - Advanced Collections and Data Structures →Lesson 11 - Creating Histograms →Lesson 11 - Exception Handling →Lesson 11 - Handling Missing Data →Lesson 11: Gherkin Language →Lesson 12 - Comparing Distributions →Lesson 12 - Data Type Conversion and Cleaning →Lesson 12 - List Comprehension →Lesson 12 - Working With Dates, Times, and Timezones →Lesson 12: CI/CD and DevOps →Lesson 13 - Lambda Functions →Lesson 13 - Modules and Packages →Lesson 13 - Pandas Plot Method →Lesson 13 - Removing Duplicates and Handling Outliers →Lesson 13: Security Best Practices →Lesson 14 - Creating Subplots →Lesson 14 - Filter and Map Functions →Lesson 14 - Virtual Environments and Dependency Management →Lesson 14 - Working With String Data →Lesson 15 - Grid Charts →Lesson 15 - GroupBy and Aggregation →Lesson 16 - Final Project - Traffic Analysis →Lesson 16 - Pivot Tables →Lesson 17 - Concatenating DataFrames →Lesson 18 - Merging and Joining DataFrames →Lesson 19 - MultiIndex and Hierarchical Data →Lesson 2 - 2D Arrays and Working With CSV Data →Lesson 2 - Class Methods, Properties, and Encapsulation →Lesson 2 - DataFrames and Reading Data →Lesson 2 - Introduction to Matplotlib →Lesson 2 - Variables and Data Types →Lesson 2: Implementing SDLC in Real-World Projects →Lesson 20 - Window Functions and Rolling Operations →Lesson 21 - Final Project: Real-World Data Analysis →Lesson 3 - Customizing Plots →Lesson 3 - For Loops and Iteration →Lesson 3 - Inheritance and Polymorphism →Lesson 3 - Selecting and Slicing Data →Lesson 3 - Selecting Data With .Loc[] →Lesson 3: Software Development Methodologies →Lesson 4 - Multiple Lines and Series →Lesson 4 - Selecting Data With .Iloc[] →Lesson 4 - Special Methods and Python's Data Model →Lesson 4 - Vector Operations and Calculations →Lesson 4 - Working With Lists →Lesson 4: Software Design and Architecture →Lesson 5 - Advanced Function Concepts →Lesson 5 - Boolean Indexing and Data Filtering →Lesson 5 - Conditional Statements →Lesson 5 - Scatter Plots Basics →Lesson 5 - Series Operations and Value Counts →Lesson 5: Design Patterns →Lesson 6 - Creating Scatter Plots →Lesson 6 - DateTime Fundamentals →Lesson 6 - Decorators and Metaprogramming →Lesson 6 - Modifying Data and Assignment →Lesson 6 - Python Dictionaries →Lesson 6: Object-Oriented Programming →Lesson 7 - Advanced Dictionaries and Frequency Tables →Lesson 7 - Boolean Filtering in Pandas →Lesson 7 - Iterators and the Iterator Protocol →Lesson 7 - Understanding Correlation →Lesson 7: Clean Code and Best Practices →Lesson 8 - Comparing Correlations →Lesson 8 - Generators and Memory-Efficient Processing →Lesson 8 - Python Functions →Lesson 8 - Sorting and Ranking →Lesson 8: Version Control With Git →Lesson 9 - Adding and Modifying Columns →Lesson 9 - Context Managers and Resource Management →Lesson 9 - Python Functions: Arguments, Parameters, and Debugging →Lesson 9 - Understanding Distributions →Lesson 9: Software Testing →Overview of the NumPy Fundamentals Module →Overview of the Python Advanced Module →Overview of the Python Basics Module →Pandas Data Analysis Module Overview →Python for Data Analytics Course →Resources →