Language Practical Data Analysis (19 results)

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paperback. Condition: New. Paperback. Pub Date: 2024-01 Pages: 272 Publisher: Wuhan University Press This book starts with the basics of Python language. and introduces how to use Python software and related function packages to import. export and process common types of spatial data such as vector data. raster data. network data. point cloud data. etc. and introduces data visualization and spatial visualization techniques. In addition. this book specifically introduces Python programming in ArcGIS software. so that s.

paperback. Condition: New. Paperback. Pub Date: 2016-05-01 Pages: 392 Language: Chinese Publisher: Electronic Industry Press classical statistical theory and machine learning data mining provides the necessary analysis techniques. This book introduces the statistical analysis and machine learning fields * important and a variety of techniques and basic principles of popular. explain about the algorithm based on the combination of a large number of R language examples demonstrate the use of these theories in practice. S.

paperback. Condition: New. Paperback. Pub Date: 2015-5-1 Pages: 315 Publisher: Machinery Industry Press book consists of 24 chapters. Chapters 1-3 cover the basics of language acquisition and installation of R. R environment settings and R packages. Chapters 4 and 5 introduces R language basics and advanced data structures. involving math. vector. call the function and data boxes. lists. matrices and arrays. Chapter 6 describes how to import data. Chapter 7 relates to how to draw a statistical graph. 8-10 Chapter relat.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2017-05-01 Pages: $number Publisher: Machinery Industry Press This book will address some of the topics of data mining. such as mathematical presentation. implementation in software. and how to solve business problems accordingly. The purpose of this book is to enable readers to learn from data management techniques. exploratory data analysis. data visualization. and so on. until the establishment of high .

paperback. Condition: New. Paperback. Pub Date: 2019-06-01 Pages: 264 Publisher: China Railway Press This book introduces the technology uses the R language for data analysis and mining. the use of Deep framework: Introduction begins at the beginning of the R language the basic operation. and then introduce regression analysis. variance analysis and other data analysis to better explore the internal data .

paperback. Condition: New. Paperback. Pub Date: 2019-12-01 Pages: 452 Publisher: Machinery Industry Press Drawing on data scientist Jared P Lander rich in R language teaching experience. through many examples. explain in detail the core functions of the R language. For people new to the program and statistical models. content organization structure of the book makes learning the R language is quite simple .

paperback. Condition: New. Paperback. Pub Date: 2016-03-01 Pages: 424 Language: Chinese Publisher: Electronic Industry Press This book is an excellent primer R language to help readers quickly build relevant knowledge and data analysis system. and learn how to use the R software for data analysis. Regardless of whether the programming foundation or mathematical basis. this book can help readers grow into a qualified data analysts. This book describes the various data analysis algorithm derived from statistical analysis.

This book by Hiroki Kato, published by Daigaku Kyoiku Shuppan, provides a practical, step-by-step approach to data analysis and medical statistics, covering data processing techniques and how to select appropriate analytical methods. Ideal for students and professionals in the medical field, it offers hands-on guidance for applying statistical methods to real-world medical data. Note: The text is entirely in Japanese. Brand New Japanese Edition. Ships worldwide from Japan via Japan Post. Expedited shipping via FedEx available.

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Understand data analysis concepts to make accurate decisions based on data using Python programming and Jupyter NotebookKey FeaturesFind out how to use Python code to extract insights from data using real-world examplesWork with structured data and free text sources to answer questions and add value using dataPerform data analysis from scratch with the help of clear explanations for cleaning, transforming, and visualizing dataBook DescriptionData literacy is the ability to read, analyze, work with, and argue using data. Data analysis is the process of cleaning and modeling your data to discover useful information. This book combines these two concepts by sharing proven techniques and hands-on examples so that you can learn how to communicate effectively using data.After introducing you to the basics of data analysis using Jupyter Notebook and Python, the book will take you through the fundamentals of data. Packed with practical examples, this guide will teach you how to clean, wrangle, analyze, and visualize data to gain useful insights, and you'll discover how to answer questions using data with easy-to-follow steps.Later chapters teach you about storytelling with data using charts, such as histograms and scatter plots. As you advance, you'll understand how to work with unstructured data using natural language processing (NLP) techniques to perform sentiment analysis. All the knowledge you gain will help you discover key patterns and trends in data using real-world examples. In addition to this, you will learn how to handle data of varying complexity to perform efficient data analysis using modern Python libraries.By the end of this book, you'll have gained the practical skills you need to analyze data with confidence.What you will learnUnderstand the importance of data literacy and how to communicate effectively using dataFind out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysisWrangle data and create DataFrames using pandasProduce charts and data visualizations using time-series datasetsDiscover relationships and how to join data together using SQLUse NLP techniques to work with unstructured data to create sentiment analysis modelsDiscover patterns in real-world datasets that provide accurate insightsWho this book is forThis book is for aspiring data analysts and data scientists looking for hands-on tutorials and real-world examples to understand data analysis concepts using SQL, Python, and Jupyter Notebook. Anyone looking to evolve their skills to become data-driven personally and professionally will also find this book useful. No prior knowledge of data analysis or programming is required to get started with this book.

Taschenbuch. Condition: Neu. Practical Data Analysis using Jupyter Notebook | Learn how to speak the language of data by extracting useful and actionable insights using Python | Marc Wintjen | Taschenbuch | Kartoniert / Broschiert | Englisch | 2020 | Packt Publishing | EAN 9781838826031 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.