Take advantage of Python data analysis programming
Work with Python objects, functions, modules, and libraries
Apply statistical concepts such as probability and random distributions
Use NumPy, SciPy, Scikit-learn, and Pandas libraries
Wow 'em with your mastery of Python for managing and analyzing data!
Python is a programming language perfectly suited for data science. Even if it's brand new to you, this straightforward guide will help you learn to use Python programming to acquire, organize, process, and analyze large amounts of information and identify trends and patterns. From installing Python to performing cross-validation, learn with this book!
See why Python works for data science — tour the data science pipeline and learn about Python's basic capabilities
Get set up — install Python, download datasets and example code, and start working with numbers and logic, creating functions, and storing and indexing data
Make it visual — explore MatPlotLib and create graphs, pie and bar charts, histograms, and advanced scatterplots
Delve deeper — venture into classes and multiprocessing, define descriptive statistics for numeric data, and use applied visualization
Advanced data wrangling — examine solutions to dimensionality reduction, perform hierarchical clustering, and learn to detect outliers in your data
Make data tell you something — work with linear models and perform cross-validation, selection, and optimization
Open the book and find:
Fundamentals of Python data analysis programming
All about the Python development environment
How to use random distributions and regression models
Advice on accessing data from the web
What to do with NumPy, pandas, and SciPy
Tips on working with HTML pages
How to create interactive graphical representations
Ten essential data resources
To download the source code files for the examples in this book, go to www.Dummies.com/extras/pythonfordatascience
John Paul Mueller is a technical editor and freelance author who has written on topics ranging from database management to heads-down programming, from networking to artificial intelligence. He is the author of Start Here!™ Learn Microsoft Visual C#® 2010.