Project overview
In this project, you’ll assume the role of a data analyst tasked with exploring a real-world dataset on helicopter prison escapes. Using Python in JupyterLab, you’ll apply data wrangling techniques to clean and analyze the data, uncovering trends such as the countries and years with the most escape attempts.
This project provides hands-on experience with essential data analysis skills in Python and JupyterLab. You’ll learn to load data, use loops and functions to clean and transform it, create visualizations, and draw meaningful conclusions. By analyzing an intriguing real-world dataset, you’ll build a compelling project for your portfolio.
Objective: Use Python and Jupyter Notebook to analyze a dataset on helicopter prison escapes, identifying key trends and developing data storytelling skills.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Working with Python variables and data types
- Running Python code in Jupyter Notebook cells
- Adding text to Jupyter cells
- Using Jupyter to analyze data and document work
Projects steps
Step 1: JupyterLab
Step 2: Running Code
Step 3: Running Code Using the Keyboard
Step 4: Helicopter Escapes!
Step 5: Get the Data
Step 6: Text and Markdown Cells
Step 7: Removing the Details
Step 8: Extracting the Year
Step 9: Attempts per Year I
Step 10: Attempts per Year II
Step 11: Attempts per Year III
Step 12: Attempts by Country
Step 13: Review
Step 14: Takeaways
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