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Python for Data Science For Dummies (For Dummies (Computer/Tech))

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Unleash the power of Python for your data analysis projectswith For Dummies!

Python is the preferred programming language for data scientistsand combines the best features of Matlab, Mathematica, and R intolibraries specific to data analysis and visualization. Pythonfor Data Science For Dummies shows you how to take advantage ofPython programming to acquire, organize, process, and analyze largeamounts of information and use basic statistics concepts toidentify trends and patterns. You’ll get familiar with thePython development environment, manipulate data, design compellingvisualizations, and solve scientific computing challenges as youwork your way through this user-friendly guide.

  • Covers the fundamentals of Python data analysis programming andstatistics to help you build a solid foundation in data scienceconcepts like probability, random distributions, hypothesistesting, and regression models
  • Explains objects, functions, modules, and libraries and theirrole 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 guideto getting a grip on data overload and doing interesting thingswith the oodles of information you uncover.

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Python for Data Mining Quick Syntax Reference
Python for Data Mining Quick Syntax Reference
?Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.

Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks
Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks
Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples.

Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian
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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas,...


Python Data Analysis Cookbook
Python Data Analysis Cookbook

Key Features

  • Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types
  • Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning
  • Authored by Ivan Idris, expert in python programming and proud...
Pro Python Best Practices: Debugging, Testing and Maintenance
Pro Python Best Practices: Debugging, Testing and Maintenance

Learn software engineering and coding best practices to write Python code right and error free. In this book you’ll see how to properly debug, organize, test, and maintain your code, all of which leads to better, more efficient coding.

Software engineering is difficult. Programs of any substantial length are...

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you...

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