Python for Data Science For Dummies 9781119547624

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Titel: Python for Data Science For Dummies
Auteur: Luca Massaron
ISBN: 9781119547624
Conditie: Beetje gebruikt

• Learn Python data analysis programming and statistics
• Write code in the cloud with Google Colab™
• Wrangle data and visualize information

Relax! Data science doesn't have to be scary Curious about data science, but a bit intimidated? Don't be! This book shows you how to use Python to do all sorts of cool things with data science. You'll see how to install the Anaconda tool suite, so working with Python is a breeze. You'll discover Google Colab, which lets you write code in the cloud using your tablet. You'll find out how to perform all kinds of interesting calculations using the latest version of Python. And you'll learn to use the various libraries that enable scientific statistical analysis, plotting and graphing, and much more. Inside...

• Python set-up for data science
• Working with Jupyter Notebook
• Conditioning and shaping data
• Graphing with MatPlotLib
• Ways to analyze your data
• Getting more from Python
• Useful data science algorithms
• Ten essential data resources

The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud.

• Get started with data science and Python
• Visualize information
• Wrangle data
• Learn from data

The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

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