DataCamp
FreeWorking with Categorical Data in Python
4.8(2,676)35k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
Non-numerical data requires specialized manipulation techniques. This intermediate course focuses on handling categorical variables using pandas and seaborn, working with diverse datasets like adoptable dog profiles, Las Vegas trip reviews, and census records.
Who It's For
Python data analysts and data scientists looking to effectively manage, transform, and visualize non-numeric categorical data.
Key Takeaways
- Pandas Categorical Type: Create, update, reorder, and delete categorical columns using specialized pandas data types.
- Categorical Visualization: Leverage seaborn to create clear visual summaries of non-numerical data distributions.
- Diverse Data Practice: Practical exercises using census data, pet adoption records, and travel reviews.
About this course
Being able to understand, use, and summarize non-numerical data—such as a person’s blood type or marital status—is a vital component of being a data scientist. In this course, you’ll learn how to manipulate and visualize categorical data using pandas and seaborn. Through hands-on exercises, you’ll get to grips with pandas' categorical data type, including how to create, delete, and update categorical columns. You’ll also work with a wide range of datasets including the characteristics of adoptable dogs, Las Vegas trip reviews, and census data to develop your skills at working with categorical data.
Price
Free
This course is free to enrol.
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