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.
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.
Table of contents
About the author
As a data analyst enthusiast, Mihaela has special interests in translating vision into action using end-to-end data analysis. She is very passionate about teaching and resolving real-world business problems. Her greatest joy is learning new data exploration techniques and pushing the boundaries of data analytics. Mihaela has a bachelor’s degree in economic cybernetics and in her spare time she loves to travel and dance.