Analyze 20,000 real Jeopardy questions in Python using pandas, regular expressions, and text cleaning. This project walkthrough is perfect if you're comfortable with pandas basics and want to level up your text-analysis and statistics skills on a fun, real-world dataset. Follow along with Dataquest's Director of Curriculum, Anna Strahl.
Complete the project free here: https://www.dataquest.io/projects/gui...
What you'll learn:
How to clean and normalize messy text data using regular expressions and pandas
How to engineer features with custom functions and the .apply() method
How to investigate whether answers are hidden in the questions and whether clues get recycled over time
How to run a chi-squared test to check whether word usage differs between high- and low-value clues
Key skills covered: Python, pandas, regular expressions, text data cleaning, chi-squared testing, exploratory data analysis
New to Python? Build the foundational skills you need with our Python Basics for Data Analysis course: https://www.dataquest.io/path/python-...
00:00:00 Introduction
00:06:11 Load the data
00:09:50 Normalize the text data
00:20:52 Question #1: Are trivia answers in the questions?
00:31:27 Question #2: Does Jeopardy reuse questions?
00:42:50 Question #3: Are high-value questions predictable?
00:53:33 Next step suggestions
00:55:45 Q&A
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