- Course
Data Science with Python: Distributions and Aggregations in Data
Mastering distributions and aggregations is essential for effective exploration, summarization, and analysis of datasets. This course will teach you how to analyze distributions and implement advanced data summarization techniques.
Beginner
- Course
Data Science with Python: Distributions and Aggregations in Data
Mastering distributions and aggregations is essential for effective exploration, summarization, and analysis of datasets. This course will teach you how to analyze distributions and implement advanced data summarization techniques.
Beginner
Get started today
Access this course and other top-rated tech content with one of our business plans.
Try this course for free
Access this course and other top-rated tech content with one of our individual plans.
This course is included in the libraries shown below:
- Data
What you'll learn
Distributions and aggregations are essential tools in data science enabling the exploration, summarization, and in-depth analysis of data to derive actionable insights.
In this course, Data Science with Python: Distributions and Aggregations in Data, you’ll gain the ability to explore complex datasets and extract meaningful information.
First, you’ll explore univariate and bivariate distributions using graphical techniques, with an emphasis on understanding the principles of correlation and causation.
Next, you’ll discover how to perform advanced data manipulation techniques, including grouping and aggregation.
Finally, you’ll learn how to reshape data using crosstabs and pivot tables for data summarization and analysis.
When you’re finished with this course, you’ll have the skills and knowledge of distributions and aggregations needed to explore, summarize, and analyze data with Python.
Data Science with Python: Distributions and Aggregations in Data
Beginner
Table of contents
As a data analyst enthusiast, Mihaela has special interests in translating vision into action using end-to-end data analysis while being very passionate about teaching.
