Python for Data Science : A Hands-On Introduction by Yuli Vasiliev (2022, Trade Paperback) online kaufen

Über dieses Produkt

Product Identifiers

PublisherNo Starch Press, Incorporated

ISBN-101718502206

ISBN-139781718502208

eBay Product ID (ePID)13050099061

Product Key Features

Number of Pages240 Pages

LanguageEnglish

Publication NamePython for Data Science : a Hands-On Introduction

SubjectGeneral, Databases / Data Mining, Databases / General, Programming Languages / Python

Publication Year2022

TypeTextbook

Subject AreaMathematics, Computers

AuthorYuli Vasiliev

FormatTrade Paperback

Dimensions

Item Height0.7 in

Item Weight15.5 Oz

Item Length9.2 in

Item Width7 in

Additional Product Features

Intended AudienceTrade

LCCN2022-002116

Reviews"A great introduction to Python for data science in a compact package. I'm impressed with what Yuli Vasiliev included: the basics of Python, multiple angles at preparation, and a number of chapters on common types of data. The book is surprisingly visual for a field known for rows and columns--the location data was especially interesting to me. By the end of [ Python for Data Science ], I was ready to apply the principles to my own datasets." --Adam DuVander, @adamd, Founder of EveryDeveloper "Python to help you evaluate information is a great skill to have. Python for Data Science , written by Yuli Vasiliev, is an excellent resource for someone interested in getting started with Data Science. Although not intended for beginners in data analytics or python programming, this book explains how to implement some essential python concepts, gives excellent code snippets for practice, and guides you on using a few important libraries useful for processing and analyzing data with code." --Kelly Schuster-Paredes, Co-Host of Teaching Python Podcast, Educator, "A great introduction to Python for data science in a compact package. I'm impressed with what Yuli Vasiliev included: the basics of Python, multiple angles at preparation, and a number of chapters on common types of data. The book is surprisingly visual for a field known for rows and columns--the location data was especially interesting to me. By the end of [ Python for Data Science ], I was ready to apply the principles to my own datasets." --Adam DuVander, @adamd, Founder of EveryDeveloper

Dewey Edition23

Dewey Decimal005.133

SynopsisThe perfect guide for intermediate programmers, Python for Data Science shows you the best ways to leverage Python for data-driven applications. Loaded with practical examples, the book provides a wide-ranging tour of Python's abilities to obtain, transform, and analyze data. You'll discover Python's rich built-in data structures and its robust ecosystem of open source data science libraries, including NumPy, pandas, scikit-learn, and Matplotlib. You'll practice loading data in various formats; streamlining, grouping, and aggregating datasets; and creating visualizations like charts and maps, in-depth examples show you how to build real-world data applications, including a taxi service powered by location data, an association rule analysis of transaction data to identify items commonly purchased together, and a machine learning model to predict stock trends. Exercises throughout the book encourage you to try techniques out for yourself. You'll learn how to: Efficiently manipulate data structures such as lists, dictionaries, NumPy arrays, and pandas DataFrames, Move data to and from both relational and NoSQL databases, Gain actionable insights about your data through aggregation, visualization, and other analysis methods, Work with plaintext, GPS data, time series data, JSON and CSV files, and many other types and formats of data, Use machine learning for natural language processing tasks such as sentiment analysis, In Python for Data Science, you'll practice modern data processing techniques for immediate use in fields like business management, marketing, and finance. Discover the power of the Python programming language. Book jacket., 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 analyse data, practicing state-of-the-art data processing techniques for use cases in business management, marketing, and decision support., 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.

LC Classification NumberQA76.73.P98V37 2022