Listing 1 - 10 of 21 | << page >> |
Sort by
|
Choose an application
Choose an application
'Panda Nation' demonstrates how the giant panda's transformation from an obscure animal into a national treasure reflects China's efforts to distinguish itself as a nation. Through government-directed science and popular nationalism, the story of the panda's iconic rise offers a striking reflection of China's dramatic ascent in global status.
Pandas --- Pandas --- Pandas --- Symbolic aspects. --- Political aspects. --- Conservation.
Choose an application
'Panda Nation' demonstrates how the giant panda's transformation from an obscure animal into a national treasure reflects China's efforts to distinguish itself as a nation. Through government-directed science and popular nationalism, the story of the panda's iconic rise offers a striking reflection of China's dramatic ascent in global status.
Pandas --- Symbolic aspects. --- Political aspects. --- Conservation.
Choose an application
The giant panda is one of the world's most recognized animals. With the environment undergoing unprecedented change at a rapid and accelerating rate, can such a highly specialized species survive? This 2006 book summarizes panda biology and encompasses topics such as reproduction, behaviour, nutrition, genetics and veterinary medicine. It also provides information on veterinary management, advances in neonatal care, disease detection and prevention and the use of 'assisted breeding' to promote reproduction and preserve genetic diversity, as the females are sexually receptive for only 3 days per year and generally produce twins, but often lose one due to maternal neglect. This book provides the scholarly knowledge that will help conserve this treasured species in nature, while there is still time.
Giant panda. --- Ailuropoda. --- Bears --- Pandas --- Ailuropoda melanoleuca --- Ursus melanoleucus --- Ailuropoda
Choose an application
This book introduces an assortment of powerful command line utilities that can be combined to create simple, yet powerful shell scripts for processing datasets. The code samples and scripts use the bash shell, and typically involve small datasets so you can focus on understanding the features of grep, sed, and awk. Companion files with code are available for downloading from the publisher. FEATURES:Provides the reader with powerful command line utilities that can be combined to create simple yet powerful shell scripts for processing datasetsContains a variety of code fragments and shell scripts for data scientists, data analysts, and those who want shell-based solutions to “clean” various types of datasetsCompanion files with code
Computer Science. --- Data Science. --- Pandas. --- Programming. --- Python. --- UNIX. --- awk. --- data mining. --- grep. --- sed.
Choose an application
Python is a robust, procedural, object-oriented, and functional language. The features of the language make it valuable for web development, game development, business, and scientific programming. This book deals with problem-solving and programming in Python. It concentrates on the development of efficient algorithms, the syntax of the language, and the ability to design programs in order to solve problems. In addition to standard Python topics, the book has extensive coverage of NumPy, data visualization, and Matplotlib. Numerous types of exercises, including theoretical, programming, and multiple-choice, reinforce the concepts covered in each chapter. FEATURES:Concentrates on the development of efficient algorithms, the syntax of the language, and theability to design programs in order to solve problemsFeatures both standard Python topics and also extensive coverage of NumPy, data visualization, and Matplotlib problem-solving techniques
Python (Computer program language). --- Matplotlib. --- NumPy. --- Pandas. --- algorithm. --- business communication. --- computer science. --- engineering. --- programming. --- science.
Choose an application
Long description: Die wichtigsten Tools für die Datenanalyse und-bearbeitung im praktischen Einsatz Python effizient für datenintensive Berechnungen einsetzen mit IPython und Jupyter Laden, Speichern und Bearbeiten von Daten und numerischen Arrays mit NumPy und Pandas Visualisierung von Daten mit Matplotlib Python ist für viele die erste Wahl für Data Science, weil eine Vielzahl von Ressourcen und Bibliotheken zum Speichern, Bearbeiten und Auswerten von Daten verfügbar ist. In diesem Buch erläutert der Autor den Einsatz der wichtigsten Tools. Für Datenanalytiker und Wissenschaftler ist dieses umfassende Handbuch von unschätzbarem Wert für jede Art von Berechnung mit Python sowie bei der Erledigung alltäglicher Aufgaben. Dazu gehören das Bearbeiten, Umwandeln und Bereinigen von Daten, die Visualisierung verschiedener Datentypen und die Nutzung von Daten zum Erstellen von Statistiken oder Machine-Learning-Modellen. Dieses Handbuch erläutert die Verwendung der folgenden Tools: IPython und Jupyter für datenintensive Berechnungen NumPy und Pandas zum effizienten Speichern und Bearbeiten von Daten und Datenarrays in Python Matplotlib für vielfältige Möglichkeiten der Visualisierung von Daten Scikit-Learn zur effizienten und sauberen Implementierung der wichtigsten und am meisten verbreiteten Algorithmen des Machine Learnings Der Autor zeigt Ihnen, wie Sie die zum Betreiben von Data Science verfügbaren Pakete nutzen, um Daten effektiv zu speichern, zu handhaben und Einblick in diese Daten zu gewinnen. Grundlegende Kenntnisse in Python werden dabei vorausgesetzt. Leserstimme zum Buch: »Wenn Sie Data Science mit Python betreiben möchten, ist dieses Buch ein hervorragender Ausgangspunkt. Ich habe es sehr erfolgreich beim Unterrichten von Informatik- und Statistikstudenten eingesetzt. Jake geht weit über die Grundlagen der Open-Source-Tools hinaus und erläutert die grundlegenden Konzepte, Vorgehensweisen und Abstraktionen in klarer Sprache und mit verständlichen Erklärungen.« – Brian Granger, Physikprofessor, California Polytechnic State University, Mitbegründer des Jupyter-Projekts Biographical note: Jake VanderPlas ist seit Langem User und Entwickler von SciPy. Derzeit ist er als interdisziplinärer Forschungsdirektor an der Universität Washington tätig, führt eigene astronomische Forschungsarbeiten durch und berät dort ansässige Wissenschaftler, die in vielen verschiedenen Fachgebieten arbeiten.
Datenanalyse --- Big Data --- Algorithmen --- NumPy --- SciPy --- Pandas --- Data Scientist --- sentiment analyse --- Sentiment Analysis
Choose an application
"This book contains a fast-paced introduction to as much relevant information about managing data that can be reasonably included in a book of this size. However, you will be exposed to a variety of features of NumpPy and Pandas, how to create databases and tables in MySQL, and how to perform many data cleaning tasks and data wrangling. Some topics are presented in a cursory manner, which is for two main reasons. First, it's important that you be exposed to these concepts. In some cases, you will find topics that might pique your interest, and hence motivate you to learn more about them through self-study; in other cases, you will probably be satisfied with a brief introduction. In other words, you will decide whether or not to delve into more detail regarding the topics in this book. Second, a full treatment of all the topics that are covered in this book would significantly increase the its size of this book, and few people have the time to read technical tomes"--
Computer programming. --- Pandas. --- Java. --- MySQL. --- NumPy. --- Python. --- RDBMs. --- awk. --- computer science. --- data cleaning. --- data science. --- programming.
Choose an application
Queer and Bookish: Eve Kosofksy Sedgwick as Book Artist represents the first book-length study to explore the intersections of Sedgwick’s critical writing, poetry, and, most importantly, book art, making the case that her art criticism, especially her meditations on domestic and nineteenth-century photography, and “artist’s book” projects are as formally complex and brilliant, conceptually significant and life-changing, as her literary criticism and theory. In addition, the book represents a significant intervention into recent debates about reparative reading, surface reading, and the descriptive turn across the humanities, because of its sustained, positive accounts on Sedgwick’s books as visual, textural, and material objects.The book ranges across Sedgwick’s published output, from The Coherence of Gothic Conventions (1980) to the posthumously published The Weather in Proust (2011), and features her meditations on a wide variety of art-historical topoi, including Judith Scott’s queer/crip fiber art; the anality of Polykleitos’s Doryphorus; queer Modernist typography; Piranesi’s punitive space; Duncan Grant and Vanessa Bell’s queer holy family; Manet’s frontality and thalassic aesthetics; fat and thin aesthetics of various stripes; and the queer photography of Anna Atkins, Clementina Hawarden, and Julia Margaret Cameron; Baron De Mayer, Eugene Atget, and P.H. Emerson; as well as David Hockney, Ken Brown, and her own father, a NASA lunar photographer. The book climaxes with two chapter-length explorations of Sedgwick’s own late-life book-art practice: her panda Valentine alphabet cards (c. 1996) and her Last Days of Pompeii/Cavafy unique artist’s book (c. 2007).
Choose an application
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of managing data using a variety of computer languages and applications. It is intended to be a fast-paced introduction to some basic features of data management and covers statistical concepts, data-related techniques, features of Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. Companion files with source code and color figures are available. FEATURES: Covers Pandas, RDBMS, NLP, data cleaning, SQL, and data visualization. Introduces probability and statistical concepts. Features numerous code samples throughout. Includes companion files with source code and figures.
Quantitative research --- Reliability. --- Data processing. --- NLP. --- Pandas. --- RDBMS. --- SQL. --- computer science. --- data analytics. --- data cleaning. --- data visualization. --- programming. --- python. --- statistics.
Listing 1 - 10 of 21 | << page >> |
Sort by
|