# Data Analysis with Open Source Tools

- Data Analysis with Open Source Tools
- A Hands-On Guide for Programmers and Data Scientists
- Philipp K. Janert
- 540 pages
- O’Reilly (2010)
- ISBN: 978-0596802356

### From the Back Cover:

Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.

Along the way, you’ll experiment with concepts through hands-on workshops at the end of each chapter. Abova all, you’ll learn how to think about the results you want to achieve—rather than rely on tool to think for you.

### Table of Contents:

- Introduction
- A Single Variable: Shape and Distribution
- Two Variables: Establishing Relationships
- Time as a Variable: Time-Series Analysis
- More Than Two Variables: Graphical Multivariate Analysis
- Intermezzo: A Data Analysis Session
- Guesstimation and the Back of the Envelope
- Models from Scaling Arguments
- Arguments from Probability Models
- What You Really Need to Know About Classical Statistics
- Intermezzo: Mythbusting—Bigfoot, Least Squares, and All That
- Simulations
- Finding Clusters
- Seeing the Forest for the Trees: Finding Important Attributes
- Intermezzo: When More is Different
- Reporting, Business Intelligence, and Dashboards
- Financial Calculations and Modeling
- Predictive Analytics
- Epilogue: Facts Are Not Reality
- Appendix A: Programming Environments for Scientific Computation
- Appendix B: Results from Calculus
- Appendix C: Working with Data