Python Data Analysis

Why Learn 📚#

What to Learn 📝#

Market Data Analysis#

• L01: Getting Started with DA: Measuring the World in Data
• L02: Multidimensional and Comparative Analysis: Common Data Analysis Methods Ⅰ
• L03: Funnel Analysis and A/B Testing: Common Data Analysis Methods Ⅱ

Using Data with NumPy#

• L04: N-Dimensional Array: Drafting the Star Player
• L05: Boolean Indexing: Perfecting Predictions

Data Processing with Pandas#

• L06: Series and DataFrames: Exploring Data Dimensions
• L07: Advanced Data Operations: Unveiling Sales Champions
• L08: Data Filtering: Profiling Sales Performance
• L09: Data Grouping: Decoding Team Success
• L10: Data Cleaning: Polishing Your Data
• L11: Practical Analysis:Mining Loyal Customers with RFM

Data Visualization with Plotly#

• L12: Stacked Bar Charts: Unstacking Fitness Trends
• L13: Donut Charts: Slicing into New User Engagement
• L14: Scatter Plot Charts: Uncovering Healthcare Patterns
• L15: Pyramid Charts: Layering Demographic Insights

Market Data Analysis#

• L16: Market Metrics: Decoding the 5C4P & Beyond
• L17: Integrating A/B Testing & AARRR: Unlocking Reading App Bottlenecks
• L18: Advanced Analysis & Insights: Charting Paths for Iteration
• L19: Association Rules: Discovering Unlikely Pairings

Data & Society#

• L20: GDP Analysis: Tracing a Nation’s Pulse
• L21: Movie Data Analysis: Spotting the Flops

How to Learn ✨#

• Interactive Courses: Engaging interactive lessons that feel like having a direct conversation with your personal tutor.
• **Hands-on Projects: ** Each topic comes with corresponding coding exercises, allowing you to program directly in the course’s compiler.
• AI Tutor: Personalized answers are provided by an AI tutor for any questions or programming errors encountered during the course.