This data-heavy course focuses on trends and patterns in air travel history. Using complex visualizations and time series analysis, you will learn about growth trajectories and seasonal fluctuations in the air travel sector.
Overview
Syllabus
- Lesson 1: Exploring the Seaborn Flights Dataset: An Initial Glimpse
- Exploring the Flights Dataset: First Impressions
- Slightly Shifting our Spaceship: Adjusting our View on Flight Data
- Navigating Through the Turbulence: Dataset Entry Count Issue
- Navigating the Cosmos: Total Entries and Dimensions of the Airline Dataset
- Flight Data Exploration: Final Takeoff
- Lesson 2: Guiding Through Air Travel Using Line Plots: An Introduction to Trend Analysis in Python
- Visualizing Trends in Air Travel with Line Plots
- Plotting July Passenger Counts Over a Decade
- Debugging the Flight Passenger Trends Plot
- Creating a Line Plot to Visualize Monthly Passenger Counts
- Visualizing Yearly Total Passenger Counts with a Line Plot
- Lesson 3: Analyzing and Visualizing Seasonal Fluctuations with Python
- Visualizing Seasonal Trends in Air Travel Passenger Counts
- Analyzing Monthly Trends in Air Travel Passenger Counts
- Debugging Monthly Passenger's Count Plot
- Customizing a Line Plot for Monthly Passenger Counts Visualization
- Visualizing Seasonal Trends in Air Travel From Scratch
- Lesson 4: Unveiling Heat Maps for Monthly Data Analysis in Python
- Creating and Visualizing a Heatmap of Air Travel Data
- Altering Heatmap's Color Scheme
- Debugging Heat Map Creation
- Enhancing the Heatmap Visualization of Monthly Airline Passenger Counts
- Crafting a Detailed Heatmap from Scratch
- Lesson 5: Predicting Air Travel Trends with Linear Regression
- Predicting and Visualizing Future Flight Traffic with Linear Regression
- Predicting Far Beyond: The Passenger Counts of 1975!
- Flight to the Future: Debugging Passenger Prediction
- Predicting the Sky Traffic: Next Decade's Passenger Counts
- Predicting Decade Passenger Counts using Linear Regression
- Drawing the Future: Predicting Passenger Trends with Regression
