Multidimensional Data Visualization

The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you're new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems. Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful dat

內容介紹: [用最熟悉的 Excel 製作儀表板, 實現商業智慧]近年來, 無論是大型還是中小企業都能接觸到大量的數據, 也越來越熱衷於資料的搜集和儲存。然而, 經營層不可能消化所有原始數據, 所以在用資料做出商業決策以前, 原始數據必須先轉換為有效資訊才行, 而這樣的過程就是我們所說的『商業智慧（BI, business intelligence）』, 製作儀表板（dashboards）就是資料視覺化成果的重要一環。其實 BI 的概念早就存在很長時間了, 只不過隨著相關軟體工具日益強大且普及，BI 也逐漸成為熱門話題。可以說：在『資料取得門檻降低』與『BI 工具大行其道』的雙重影響下, 開啟了各家企業對於製作『儀表板』的需求。在眾多軟體中, Excel 已然成為整合各種 BI 工具的標準。微軟公司投入了大量資源開發 Excel 內建與外部的 BI 插件；不但建立了包含 Power Query、Power Pivot 等工具的 Power BI 家族, 還在 Excel 新版本中添加了許多先前沒有的圖表類型。以上努力得到的成果就是：許多本來得透過專業軟體達成的功能, 現在人人都能以 Excel 完成。在過去, 為了存取資料和製作儀表板必須自己開發 IT 工具；如今這些工具可能早就在安裝進你的電腦中了, 而關鍵就在各職場皆不可缺的 Excel。話雖如此, 再熟悉的軟體也有不會的功能。如果你正想學習製作儀表板卻不具備相關知識, 那麼歡迎閱讀本書！我們會完整介紹 Excel 的資料視覺化功能, 從使用形狀、設定條件式格式、到繪製各類圖表等。各位將能從本書提供的實例中, 瞭解如何以儀表板回答真實的商業問題。此外, 還包括許多進階功能, 例如圖表自動化、VBA 設計、Power Query/Power Pivot 在匯入資料之前做前期處理, 以及在 Excel 中建立類似關聯式資料庫的資料模型（data model）等都很值得學習。Excel 的功能不斷地在進化, 期望讀者能學以致用。本書特色:◎台灣唯一 Excel 儀表板專書, 內容豐富, 全書 488 頁全彩印刷。◎三種儀表板從頭做到尾：專案目標進度監控、關鍵績效指標、企業營運的財務指標。◎20 種一定要會的圖表製作與使用情境。◎連續 12 年微軟最有價值專家 Dick Kusleika 經驗傳承。 

The book will provide a comprehensive overview on information visualization and visual exploration. In the era of Big Data visual interactive approaches that support the investigation of large volumes

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Py

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine

"This book brings a broad spectrum of artificial intelligence and its applications under the purview of 3D image processing so that it is able to trigger further inspiration among various research com

Data Visualization for Design Thinking helps you make better maps. Treating maps as applied research, you’ll be able to understand how to map sites, places, ideas, and projects, revealing the complex

Data Visualization for Design Thinking helps you make better maps. Treating maps as applied research, you’ll be able to understand how to map sites, places, ideas, and projects, revealing the complex

Time is an exceptional dimension that is common to many application domains such as medicine, engineering, business, or science. Due to the distinct characteristics of time, appropriate visual and ana

This is a new edition to the classic book by ggplot2 creator Hadley Wickham. ggplot2 is a data visualization package for R that helps users create data graphics, including those th

Big data is a broad term that defines the structured or unstructured data sets. It is a challenging field which includes analysis, transfer and visualization of data. This book presents in-depth descr

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered

The only Oracle Press guide to creating useful, expressive, highly visual presentations of BI data quickly and easilyData Visualization for Oracle Business Intelligence 11g reveals the best procedures

A series of business processes within healthcare including data architecture, software, analytics, and data visualization are required to make big data and health analytics possible. In this book some

In the age of Big Data, the tools of information visualization offer us a macroscopeto help us make sense of the avalanche of data available on every subject. This book offers a gentleintroduction to

A leader in the field of data visualization, Stephen Few exposes the common problems in dashboard design and describes its best practices in great detail and with a multitude of examples in this updat

Go beyond design concepts and learn to build state-of-the-art visualizationsThe visualization experts at Microsoft's Pragmatic Works have created a full-color, step-by-step guide to building specific

A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this exp

Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining by Glenn J. Myatt (978-0-470-07471-8), Making Sense of Data II: A Practical Guide to Data Visualization, Advanced D

Art, or Science? Which of these is the right way to think of the field of visualization? This is not an easy question to answer, even for those who have many years experience in making graphical depic

The 13 chapters in this collection survey current work in storing and analyzing data and using algorithms to search and discover new knowledge automatically from multidimensional data sets. Several co

Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining by Glenn J. Myatt (978-0-470-07471-8) and Making Sense of Data II: A Practical Guide to Data Visualization, Advance

This richly illustrated book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. Chapters include clustering, supervised classification, and working with m

Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection – a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining – also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields a

Provides an overview of data mining's uses, methods, technologies, commercial products, and future challenges. Part I describes technologies involved, such as warehousing and visualization, and Part I