What this book covers
Chapter 1, Laying the Foundation for Reproducible Data Analysis, is a pretty important chapter, and I recommend that you do not skip it. It explains Anaconda, Docker, unit testing, logging, and other essential elements of reproducible data analysis.
Chapter 2, Creating Attractive Data Visualizations, demonstrates how to visualize data and mentions frequently encountered pitfalls.
Chapter 3, Statistical Data Analysis and Probability, discusses statistical probability distributions and correlation between two variables.
Chapter 4, Dealing with Data and Numerical Issues, is about outliers and other common data issues. Data is almost never perfect, so a large portion of the analysis effort goes into dealing with data imperfections. ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access