The Little Green Data


Book Description

The Little Green Data Book is a pocket-sized ready reference on key environmental data for over 200 countries. Key indicators are organized under the headings of agriculture, forestry, biodiversity, oceans, energy, emission and pollution, and water and sanitation. The 2013 edition of The Little Green Data Book introduces new set of ocean-related indicators, highlighting the role of oceans in economic development.




The Little Green Data Book 2014


Book Description

The Little Green Data Book is a pocket-sized ready reference on key environmental data for over 200 countries. Key indicators are organized under the headings of agriculture, forestry, biodiversity, oceans, energy, emission and pollution, and water and sanitation. For the second year, The Little Green Data Book presents a new set of ocean-related indicators, highlighting the role of oceans in economic development.




Ecuador's Environmental Revolutions


Book Description

An account of the movement for sustainable development in Ecuador through four eras: movement origins, neoliberal boom, neoliberal bust, and citizens' revolution. Ecuador is biologically diverse, petroleum rich, and economically poor. Its extraordinary biodiversity has attracted attention and funding from such transnational environmental organizations as Conservation International, the World Wildlife Fund, and the United States Agency for International Development. In Ecuador itself there are more than 200 environmental groups dedicated to sustainable development, and the country's 2008 constitution grants constitutional rights to nature. The current leftist government is committed both to lifting its people out of poverty and pursuing sustainable development, but petroleum extraction is Ecuador's leading source of revenue. While extraction generates economic growth, which supports the state's social welfare agenda, it also causes environmental destruction. Given these competing concerns, will Ecuador be able to achieve sustainability? In this book, Tammy Lewis examines the movement for sustainable development in Ecuador through four eras: movement origins (1978 to 1987), neoliberal boom (1987 to 2000), neoliberal bust (2000 to 2006), and citizens' revolution (2006 to 2015). Lewis presents a typology of Ecuador's environmental organizations: ecoimperialists, transnational environmentalists from other countries; ecodependents, national groups that partner with transnational groups; and ecoresisters, home-grown environmentalists who reject the dominant development paradigm. She examines the interplay of transnational funding, the Ecuadorian environmental movement, and the state's environmental and development policies. Along the way, addressing literatures in environmental sociology, social movements, and development studies, she explores what configuration of forces—political, economic, and environmental—is most likely to lead to a sustainable balance between the social system and the ecosystem.




The Little Green Data Book, 2013


Book Description

The Little Green Data Book is a pocket-sized ready reference on key environmental data for over 200 countries. Key indicators are organized under the headings of agriculture, forestry, biodiversity, oceans, energy, emission and pollution, and water and sanitation. The 2013 edition of The Little Green Data Book introduces new set of ocean-related indicators, highlighting the role of oceans in economic development.




The Little Green Data Book 2017


Book Description

The Little Green Data Book 2017 is based on World Development Indicators 2017 and its online database. Defining, gathering, and disseminating international statistics is a collective effort of many people and organizations. The indicators presented in World Development Indicators are the fruit of decades of work at many levels, from the field workers who administer censuses and household surveys to the committees and working parties of the national and international statistical agencies that develop the nomenclature, classifications, and standards fundamental to the international statistical system. Nongovernmental organizations have also made important contributions. We are indebted to the World Development Indicators partners, as detailed in World Development Indicators 2017 .




The Global Findex Database 2017


Book Description

In 2011 the World Bank—with funding from the Bill and Melinda Gates Foundation—launched the Global Findex database, the world's most comprehensive data set on how adults save, borrow, make payments, and manage risk. Drawing on survey data collected in collaboration with Gallup, Inc., the Global Findex database covers more than 140 economies around the world. The initial survey round was followed by a second one in 2014 and by a third in 2017. Compiled using nationally representative surveys of more than 150,000 adults age 15 and above in over 140 economies, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution includes updated indicators on access to and use of formal and informal financial services. It has additional data on the use of financial technology (or fintech), including the use of mobile phones and the Internet to conduct financial transactions. The data reveal opportunities to expand access to financial services among people who do not have an account—the unbanked—as well as to promote greater use of digital financial services among those who do have an account. The Global Findex database has become a mainstay of global efforts to promote financial inclusion. In addition to being widely cited by scholars and development practitioners, Global Findex data are used to track progress toward the World Bank goal of Universal Financial Access by 2020 and the United Nations Sustainable Development Goals. The database, the full text of the report, and the underlying country-level data for all figures—along with the questionnaire, the survey methodology, and other relevant materials—are available at www.worldbank.org/globalfindex.







Data Visualization


Book Description

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions




An Introduction to Statistical Learning


Book Description

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.




Data Points


Book Description

A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more Examines standard rules across all visualization applications, then explores when and where you can break those rules Create visualizations that register at all levels, with Data Points: Visualization That Means Something.