Humanities Data Analysis: Case Studies with Python (Karsdorp Folgert)(Pevná vazba)

Humanities Data Analysis: Case Studies with Python (Karsdorp Folgert)(Pevná vazba)

A practical guide to data-intensive humanities research using the Python programming languageThe use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials

Digital Cultural Heritage (Kremers Horst)(Pevná vazba)

Augmenting Network Analysis with Linked Data for Humanities Research.- A Memorial Design Pattern Catalogue for commemorative digital culture.- Annotation in Digital Humanities.- Establishment of a complex database for the study of cultural her-itage through the reading and analysis of the

Multivariate Humanities (Kroonenberg Pieter M.)(Pevná vazba)

This case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields

Graphical Data Analysis with R (Unwin Antony)(Pevná vazba)

See How Graphics Reveal InformationGraphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages

Handbook of Latin American Studies Vol. 72: Humanities (McCann Katherine D.)(Pevná vazba)

Python for Arcgis (Tateosian Laura)(Pevná vazba)

Introduction.- Beginning Python.- Basic data types: numbers and strings.- Basic data types: lists and tuples.- Preparing for Python in ArcGIS.- Calling tools with arcpy.- Getting user input.- Controlling flow.- Decision-making and describing data.- Repetition: Looping for geoprocessing.- Batch

Applied Compositional Data Analysis: With Worked Examples in R (Filzmoser Peter)(Pevná vazba)

Preface.- Acknowledgements.- Compositional data as a methodological concept.- Analyzing compositional data using R.- Geometrical properties of compositional data.- Exploratory data analysis and visualization.- First steps for a statistical analysis.- Cluster analysis.- Principal component

Learn Data Analysis with Python: Lessons in Coding (Henley A. J.)(Paperback)

Table of Contents1. IntroductionHow to use this bookInstalling iPython NotebookWhat is iPython notebook?What is Anaconda?Getting StartedGetting the datasets for the workbook's exercises2. Getting Data into and out of PythonLoading Data from CSV FilesSaving Data to CSVLoading Data from Excel

Complex Network Analysis in Python: Recognize - Construct - Visualize - Analyze - Interpret (Zinoviev Dmitry)(Paperback)

Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks

Practical Python Data Visualization: A Fast Track Approach to Learning Data Visualization with Python (Pajankar Ashwin)(Paperback)

Chapter 1: Data Visualization with LeatherChapter Goal: Introduce readers to the data visualization with a simple library leatherNo of pages: 15Sub - Topics: 1. Introduction to leather2. Installation to leather3. Various types of graphs with leatherChapter 2: Introduction to the Scientific Python

Bayesian Methods for Data Analysis (Carlin Bradley P.)(Pevná vazba)

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian

Data Mining for Business Analytics: Concepts, Techniques and Applications in Python (Shmueli Galit)(Pevná vazba)

Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and

Applied Regression Analysis and Generalized Linear Models (Fox John)(Pevná vazba)

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as

Case Studies in Cardiothoracic Medicine (Fernandez Raquel Salguero)(Pevná vazba)

Wine Positioning: A Handbook with 30 Case Studies of Wine Brands and Wine Regions in the World (Mora Pierre)(Pevná vazba)

Securities Regulation - Cases and Analysis (Choi Stephen J.)(Pevná vazba)

Offers a clear and concise introduction to the economics and regulation of securities markets, with a single-minded focus on disclosure and the economics of disclosure. The book is concise, easy to read, and student

Introduction to Meta-Analysis (Borenstein Michael)(Pevná vazba)

A clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. The first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated

Rna-Seq Data Analysis: A Practical Approach (Korpelainen Eija)(Pevná vazba)

The State of the Art in Transcriptome Analysis RNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine

Excel Data Analysis: Modeling and Simulation (Guerrero Hector)(Pevná vazba)

Why does the World Need--Excel Data Analysis, Modeling, and Simulation? When spreadsheets ?rst became widely available in the early 1980s, it spawned a revolution in teaching. What previously could only be done with arcane software and large scale computing was now available to the common-man, on a

Statistics and Analysis of Scientific Data (Bonamente Massimiliano)(Pevná vazba)

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis

Mediterranean Mobilities: Europe's Changing Relationships (Paradiso Maria)(Pevná vazba)

Contains primary data and lessons learned for policy makers Describes case studies useful as laboratory and field preparation materials Includes chapters by authors from different continents appealing to classroom teaching and to general audiences far beyond

Case Studies in Personalized Nutrition (Walker Angela)(Pevná vazba)

A practical reference and teaching book of case studies for nutrition practitioners and other healthcare professionals, demonstrating how to apply the latest evidence-informed principles of personalized nutrition. Covering a range of complex cases such as autoimmunity and inflammation, hormonal

Radiographic Image Analysis (McQuillen Martensen Kathy)(Pevná vazba)

Learn to produce quality radiographs on the first try with Radiographic Image Analysis, 5th Edition. This updated, user-friendly text reflects the latest ARRT guidelines and revamped chapters to reflect the latest digital technology. Chapters walk you through the steps of how to carefully evaluate

The Frailty Model (DuChateau Luc)(Pevná vazba)

This book discusses the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients