Visualization

Geocomputation with R

by Robin Lovelace, Jakub Nowosad, Jannes Muenchow

2018-12-05
Geocomputation with R

A book on geographic data with R. […] This is the online home of Geocomputation with R, a book on geographic data analysis, visualization and modeling. Note: This book has been published by CRC Press in the R Series. The online version of this book is free to read here. Inspired by bookdown and the Free and Open Source Software for Geospatial (FOSS4G) movement, this book is open source. This ensures its contents are reproducible and publicly accessible for people worldwide. The online version of the book is hosted at geocompr.robinlovelace.net and kept up-to-date by Travis, which provides … Read more →

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edav.info/

by Zach Bogart, Joyce Robbins

2018-12-05
edav.info/

This resource is a collaborative collection of resources designed to help students succeed in GR5702 Exploratory Data Analysis and Visualization, a course offered at Columbia University. While the course lectures and textbook focus on theoretical issues, this resource, in contrast, provides coding tips and examples to assist students as they create their own analyses and visualizations. It is our hope that students will contribute to edav.info and it will grow with the course. Read more →

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ntpu-data-visualization.utf8.md

by tpemartin

2018-11-29

經濟資料視覺化處理 […] This course is designed to develop the skill of efficient graphic language, where efficiency is defined as the data information delivery that is self-contained, concise, and non-distorting. The programming language is mainly based on R, with a little bit of Javascript toward the end. Though there is no computer programming knowledge required, basic R knowledge will help (the ebook, R for Data Science, would be a good start). By the end of the course, students who learn well should be able to … Read more →

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Introduction to Data Science

by Rafael A. Irizarry

2018-11-13

This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with GitHub, and reproducible document preparation with R markdown. Read more →

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Introduction to Econometrics with R

by Christoph Hanck, Martin Arnold, Alexander Gerber and Martin Schmelzer

2018-10-10
Introduction to Econometrics with R

Beginners with little background in statistics and econometrics often have a hard time understanding the benefits of having programming skills for learning and applying Econometrics. ‘Introduction to Econometrics with R’ is an interactive companion to the well-received textbook ‘Introduction to Econometrics’ by James H. Stock and Mark W. Watson (2015). It gives a gentle introduction to the essentials of R programming and guides students in implementing the empirical applications presented throughout the textbook using the newly aquired skills. This is supported by interactive programming exercises generated with DataCamp Light and integration of interactive visualizations of central concepts which are based on the flexible JavaScript library D3.js. Read more →

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Data Processing & Visualization

by Michael Clark

2018-09-23
Data Processing & Visualization

The focus of this document is on common data processing and exploration techniques in R, especially as a prelude to visualization. The first part of the document will cover data structures, the dplyr and tidyverse packages, which enhance and facilitate the sorts of operations that typically arise when dealing with data, including faster I/O and grouped operations. For visualization, the focus will be on using ggplot2 and other packages that allow for interactivity. In addition, basic programming concepts and techniques are introduced. Exercises may be found in the document as well. In addition, the demonstrations of the data processing section are available in Python via Jupyter notebooks. Read more →

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Data Visualization with R

by Rob Kabacoff

2018-09-03
Data Visualization with R

A guide to creating modern data visualizations with R. Starting with data preparation, topics include how to create effective univariate, bivariate, and multivariate graphs. In addition specialized graphs including geographic maps, the display of change over time, flow diagrams, interactive graphs, and graphs that help with the interpret statistical models are included. Focus is on the 45 most popular graph types. The guide also includes detailed instructions on how to customizing graphs, and ends with a chapter on graphing best practices. Although strongly based on the ggplot2 package, other approaches are included as well. Read more →

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Macroeconomics

by Mau-Ting Lin

2018-06-19

This is a collection of the discussion lists from Macroeconomics. […] The theory contents will follow 1 closely. Item 2 is for data visualization. And item 3 is for general discussion regarding world news. https://goo.gl/kbQwP5 Class participation and quizzes: 10% Midterm Exam: 30% Final Exam: 30% Others Rhttp://www.r-project.org/ RStudiohttp://rstudio.org/ Github desktophttps://desktop.github.com/ … Read more →

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Data Visualization Project

by Chiayi Yen

2018-06-17

Data Visualization Project […] This study aims at investigating how the change of information dissemination process would affect the window-dressing behaviors of mutual fund managers. By convention, window-dressing is defined as the portfolio manipulations right before the quarter-end date, when all the fund managers are required to disclosure their holding firms of that date. Over the past decades, technological progresses largely change the way how information disseminates, and these further influence the information flow of capital markets. For example, the implementation of “Electronic … Read more →

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Data visualization

by Mau-Ting Lin

2017-11-06

This is a collection of data visualization handouts from Macroeconomics. … Read more →

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Mastering Software Development in R

by Roger D. Peng, Sean Kross, and Brooke Anderson

2017-09-21
Mastering Software Development in R

The book covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. Read more →

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Data Science and Visualizations with R

by Jonathan Wong

2017-07-16

Data Science and Visualizations with R […] This is a course on the use of tidyverse packages tidyverse provides a complete suite of modern data-handling tools. It is an essential toolbox for any data scientist using R. The tidyverse package is designed to be easy to install. This course will dive into using tidyverse. It will assume you have already installed r and rstudio and how some familiarity on how to use the rstudio. This book will use the nycflights13 dataset This package contains information about all flights that departed from NYC in 2013: 336,776 flights with 16 variables. To … Read more →

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The Art of Data Science

by Roger D. Peng and Elizabeth Matsui

2017-04-26

The book covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. Read more →

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Interactive Data Visualization (2nd Day)

by Paul C. Bauer & Richard Traunmüller

2016-11-23

Script developed for a workshop at the CUSO doctoral school on the 4th and 5th November 2016. […] This document serves as slides and script for the second day of the workshop Data Visualization taught by Paul C. Bauer and Richard Traunmüller for the Programme doctoral en science politique (PDSPO) (Bern, 4-5 of November 2016). The present material is licensed under a Creative Commons Attribution-ShareAlike License 3.0. Regarding further use of this material contact Paul. Some of the material is inspired by the official shiny tutorial and Plotly for R by Carston Sievert. For potential future … Read more →

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Premier League Annual

by Andrew Clark

2016-10-29

Premier League Annual […] This is an ‘on the fly’ annual based on the 2016⁄17 Premier League season, updated weekly with charts, tables, highlight videos and trivia related to the games played. Each chapter features static visualizations relevant to the games that week. Greatly extended, fully-interactive and constantly updated versions can be found on the accompanying dashboard site Additional data is available at the Premier League Web site Most of the underlying data is unofficial, unguaranteed error-free and available for a million dollars. There is also likely to be use of James … Read more →

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Data Visualization

by Kieran Healy

2018-12-05*
Data Visualization

A practical introduction. […] Forthcoming, Princeton University Press. Incomplete draft. This version: 2018-04-25. You should look at your data. Graphs and charts let you explore and learn about the structure of the information you collect. Good data visualizations also make it easier to communicate your ideas and findings to other people. Beyond that, producing effective plots from your own data is the best way to develop a good eye for reading and understanding graphs—good and bad—made by others, whether presented in research articles, business slide decks, public policy advocacy, or … Read more →

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Fundamentals of Data Visualization

by Claus O. Wilke

2018-12-05*
Fundamentals of Data Visualization

A guide to making visualizations that accurately reflect the data, tell a story, and look professional. […] This is an online preview of the book “Fundamentals of Data Visualization” to be published with O’Reilly Media, Inc. Completed chapters will be posted here as they become available. The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations. Over the years, I have noticed that the same issues … Read more →

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