Python for Data Science For Dummies (For Dummies (Computer/Tech)) - Tapa blanda

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John Paul Mueller, consultant, application developer, writer, and technical editor, has written over 600 articles and 97 books. His topics range from programming to home security. Luca Massaron is a data scientist and a research director specializing in multivariate statistical analysis, machine learning, and customer insight. He is a pioneer of Web audience analysis in Italy and was named one of the top ten data scientists at competitions by kaggle.com.

De la contraportada

Learn to:

• 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