Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.
So you’ve got some interesting data - where do you begin your analysis? This course will cover the process of exploring and analyzing data, from understanding what’s included in a dataset to incorporating exploration findings into a data science workflow.
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!
So you’ve got some interesting data - where do you begin your analysis? This course will cover the process of exploring and analyzing data, from understanding what’s included in a dataset to incorporating exploration findings into a data science workflow.
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!
