Course
Exploratory Data Analysis in Python
Intermediate
Updated 04/2025Start Course for Free
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PythonExploratory Data Analysis4 hours14 videos49 Exercises4,150 XP70,670Statement of Accomplishment
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Course Description
Using data on unemployment figures and plane ticket prices, you’ll leverage Python to summarize and validate data, calculate, identify and replace missing values, and clean both numerical and categorical values. Throughout the course, you’ll create beautiful Seaborn visualizations to understand variables and their relationships.
For example, you’ll examine how alcohol use and student performance are related. Finally, the course will show how exploratory findings feed into data science workflows by creating new features, balancing categorical features, and generating hypotheses from findings.
By the end of this course, you’ll have the confidence to perform your own exploratory data analysis (EDA) in Python.You’ll be able to explain your findings visually to others and suggest the next steps for gathering insights from your data!
Prerequisites
Introduction to Statistics in PythonIntroduction to Data Visualization with Seaborn1
Getting to Know a Dataset
2
Data Cleaning and Imputation
3
Relationships in Data
4
Turning Exploratory Analysis into Action
Exploratory Data Analysis in Python
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