Items related to Python for Data Science For Dummies (For Dummies (Computer/T...
Synopsis
Unleash the power of Python for your data analysis projects with For Dummies!
Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns. You’ll get familiar with the Python development environment, manipulate data, design compelling visualizations, and solve scientific computing challenges as you work your way through this user-friendly guide.
- Covers the fundamentals of Python data analysis programming and statistics to help you build a solid foundation in data science concepts like probability, random distributions, hypothesis testing, and regression models
- Explains objects, functions, modules, and libraries and their role in data analysis
- Walks you through some of the most widely-used libraries, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib
Whether you’re new to data analysis or just new to Python, Python for Data Science For Dummies is your practical guide to getting a grip on data overload and doing interesting things with the oodles of information you uncover.
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From the Back Cover
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
About the Author
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.
"About this title" may belong to another edition of this title.
- PublisherFor Dummies
- Publication date2015
- ISBN 10 1118844181
- ISBN 13 9781118844182
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages432
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