Leading instructors Michael Freeman and Joel Ross guide readers through installing and configuring the tools needed to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, students will master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman and Ross teach through practical examples and exercises…mehr
Leading instructors Michael Freeman and Joel Ross guide readers through installing and configuring the tools needed to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, students will master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything’s focused on real-world application, so students can quickly start analyzing their own data and getting answers they can act upon.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Michael Freeman is a senior lecturer at the University of Washington Information School, where he teaches courses in data science, interactive data visualization, and web development. Prior to his teaching career, he worked as a data visualization specialist and research fellow at the Institute for Health Metrics and Evaluation. There, he performed quantitative global health research and built a variety of interactive visualization systems to help researchers and the public explore global health trends. Michael is interested in applications of data visualization to social justice, and holds a Master’s in Public Health from the University of Washington. Joel Ross is a senior lecturer at the University of Washington Information School, where he teaches courses in web development, mobile application development, software architecture, and introductory programming. While his primary focus is on teaching, his research interests include games and gamification, pervasive systems, computer science education, and social computing. He has also done research on crowdsourcing systems, human computation, and encouraging environmental sustainability. Joel earned his M.S. and Ph.D. in information and computer sciences from the University of California, Irvine.
Inhaltsangabe
Part I: Getting Started Chapter 1: Setting Up Your Computer Chapter 2: Using the Command Line Part II: Managing Projects Chapter 3: Version Control with git and GitHub Chapter 4: Using Markdown for Documentation Part III: Foundational R Skills Chapter 5: Introduction to R Chapter 6: Functions Chapter 7: Vectors Chapter 8: Lists Part IV: Data Wrangling Chapter 9: Understanding Data Chapter 10: Data Frames Chapter 11: Manipulating Data with dplyr Chapter 12: Reshaping Data with tidyr Chapter 13: Accessing Databases Chapter 14: Accessing Web APIs Part V: Data Visualization Chapter 15: Designing Data Visualizations Chapter 16: Creating Visualizations with ggplot2 Chapter 17: Interactive Visualization in R Part VI: Building and Sharing Applications Chapter 18: Dynamic Reports with R Markdown Chapter 19: Building Interactive Web Applications with Shiny Chapter 20: Working Collaboratively Chapter 21: Moving Forward Index
Part I: Getting Started Chapter 1: Setting Up Your Computer Chapter 2: Using the Command Line Part II: Managing Projects Chapter 3: Version Control with git and GitHub Chapter 4: Using Markdown for Documentation Part III: Foundational R Skills Chapter 5: Introduction to R Chapter 6: Functions Chapter 7: Vectors Chapter 8: Lists Part IV: Data Wrangling Chapter 9: Understanding Data Chapter 10: Data Frames Chapter 11: Manipulating Data with dplyr Chapter 12: Reshaping Data with tidyr Chapter 13: Accessing Databases Chapter 14: Accessing Web APIs Part V: Data Visualization Chapter 15: Designing Data Visualizations Chapter 16: Creating Visualizations with ggplot2 Chapter 17: Interactive Visualization in R Part VI: Building and Sharing Applications Chapter 18: Dynamic Reports with R Markdown Chapter 19: Building Interactive Web Applications with Shiny Chapter 20: Working Collaboratively Chapter 21: Moving Forward Index
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