Book Python for Data Science: A Hands-On Introduction PDF Download - Yuli Vasiliev

Download ebook ➡ http://filesbooks.info/pl/book/641083/850

Python for Data Science: A Hands-On Introduction
Yuli Vasiliev
Page: 240
Format: pdf, ePub, mobi, fb2
ISBN: 9781718502208
Publisher: No Starch Press

Download or Read Online Python for Data Science: A Hands-On Introduction Free Book (PDF ePub Mobi) by Yuli Vasiliev
Python for Data Science: A Hands-On Introduction Yuli Vasiliev PDF, Python for Data Science: A Hands-On Introduction Yuli Vasiliev Epub, Python for Data Science: A Hands-On Introduction Yuli Vasiliev Read Online, Python for Data Science: A Hands-On Introduction Yuli Vasiliev Audiobook, Python for Data Science: A Hands-On Introduction Yuli Vasiliev VK, Python for Data Science: A Hands-On Introduction Yuli Vasiliev Kindle, Python for Data Science: A Hands-On Introduction Yuli Vasiliev Epub VK, Python for Data Science: A Hands-On Introduction Yuli Vasiliev Free Download

Overview
A hands-on, real-world introduction to data analysis with the Python programming language, loaded with wide-ranging examples.

Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds. Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities. You’ll learn how to write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques for use cases in business management, marketing, and decision support.

You will discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn, matplotlib, and more. Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations. Later chapters go in-depth with demonstrations of real-world data applications, including using location data to power a taxi service, market basket analysis to identify items commonly purchased together, and machine learning to predict stock prices.