Have you ever needed to clean up data? Survey data can be some of the messiest. What are the techniques you need? How do you analyze the data after cleanup? This course looks at dealing with real-world data, mine!
Analyzing Real-World Survey Data
Survey data can be messy. If you can clean this up, you can clean up almost anything! Free form text! Missing data! Ranges instead of numbers! One-off outliers!
This course will show:
Anonymizing data
Loading the data
Exploring the types and why they are messed up
Writing clean code to clean up messy data
Reformatting code to make it easy to come back to
Exploratory data analysis
Using machine learning techniques to explore the data
I'm OK with basic Pandas but I struggle to handle complex Pandas
Pandas can be tricky. Writing good Pandas code takes time and effort to use best practices. We will walk through a real-world example and show you a process that you can use to write better code. We even show how to test your code to ensure it works.
Then you can use these techniques and try them out in the lab. You can compare your results with the walkthrough.
Powerful Code!
Use powerful techniques to understand your data. Machine Learning to the rescue.
No more junk code!
Write code to make your colleagues jealous! It reads like a recipe, meaning it is easy for you to follow, and easy for your colleagues to pick up and use!
Wield Pandas Superpowers!
Learn to leverage chaining to make it easy to slice, dice, and visualize data.
Explore the data!
Understand what you are dealing with.
Master Complex Survey Data with Pandas
Move beyond simple one-liner tutorials.
Basic Version
Perfect to learn how to write better Pandas code but don't want to commit to mastery through practice and exercises.
