Here are 40 books that Exploratory Data Analysis fans have personally recommended if you like
Exploratory Data Analysis.
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Colin Koopman researches and teaches about technology ethics at the University of Oregon, where he is a Professor of Philosophy and Director of the interdisciplinary certificate program in New Media & Culture. His research pursuits have spanned from the history of efforts in the early twentieth century to standardize birth certificates to our understanding of ourselves as effects of the code inscribed into our genes. Koopman is currently at work on a book that will develop our understanding of what it takes to achieve equality and fairness in data systems, tentatively titled Data Equals.
W.E.B. Du Bois is widely acknowledged as the leading activist for racial equality of his generation. But until very recently little had been known of his deep commitment to the pursuit of equality within and through data technology. As Du Bois was preparing notes for his famous 1903 book The Souls of Black Folk, he was also preparing an exposition of what we would today call “infographics” (or what the editors of this volume aptly call “data portraits”) for exhibition at the 1900 Paris Exposition world’s fair. This volume handsomely reproduces for the first time a full-color complete set of Du Bois’s charts, graphs, maps, and ingenious spirals. A beautiful book to live with, it also subtly transforms one’s understanding of the history of racial progress and inequality in America.
"As visually arresting as it is informative."-The Boston Globe
"Du Bois's bold colors and geometric shapes were decades ahead of modernist graphic design in America."-Fast Company's Co.Design
W.E.B. Du Bois's Data Portraits is the first complete publication of W.E.B. Du Bois's groundbreaking charts, graphs, and maps presented at the 1900 Paris Exposition.
Famed sociologist, writer, and Black rights activist W.E.B. Du Bois fundamentally changed the representation of Black Americans with his exhibition of data visualizations at the 1900 Paris Exposition. Beautiful in design and powerful in content, these data portraits make visible a wide spectrum of African American culture, from…
In sixth grade, my teacher tried to teach the class how to read line charts – and something fell into place for me. Ever since then, I’ve tried to sort data into forms that we can use to make sense of it. As a researcher at Microsoft, I consulted with teams across the organization – from sales to legal; and from Excel to XBox – to help them understand their data. At Honeycomb, I design tools for software operations teams to diagnose their complex systems. These books each gave me an “ah-hah” moment that made me think differently about the craft of creating visualization. They now sit on my shelf in easy reach – I hope you find them fascinating too.
I’ve always felt a desire to make the world make sense through data – that numbers and structure could help unlock hidden meanings. When I read this novel, I felt seen: it’s told from the perspective of T. S. Spivet – a 12-year-old boy who has the same urge. Spivet thoroughly documents the world around him, sketching an ant he sees in the grass, and drawing schematics and maps of the spaces he travels through on his quest to travel to the Smithsonian Institution. The book’s margin is lavishly illustrated with Spivet’s diagrams – in seeing the world through his eyes, it felt like how I see it through my own.
A brilliant, boundary-leaping debut novel tracing twelve-year-old genius map maker T.S. Spivet's attempts to understand the ways of the world
When twelve-year-old genius cartographer T.S. Spivet receives an unexpected phone call from the Smithsonian announcing he has won the prestigious Baird Award, life as normal-if you consider mapping family dinner table conversation normal-is interrupted and a wild cross-country adventure begins, taking T.S. from his family ranch just north of Divide, Montana, to the museum's hallowed halls.
T.S. sets out alone, leaving before dawn with a plan to hop a freight train and hobo east. Once aboard, his adventures step into…
I have obsessed with maps my whole life, but I guess the main drive for studying them is my enjoyment of outdoor spaces, as a hiker, a mountaineer, and as a sailor: always with a paper map at hand. If you use GPS (a wonderful innovation) you will not only lose some of your precious orientation abilities but above all you will look less at the environment around you. I feel that paper maps do a great favor to my brain and to my enjoyment of places. The books below are a great tribute to maps; they helped me understand them better, and this affected the way I use them.
If you draw a map, you have many choices of symbols, colors, types of lines, sizes of characters, and so on. We may think these are just arbitrary choices perpetuated by tradition, but MacEachren successfully shows that we better conceive of those items as solutions to communication problems in a subtle dialogue with the Gestalt requirements of visual perception. Not any symbol will do. The symbols must be fit for minds like ours.
I learned a lot from this visual approach to maps.
Now available in paperback for the first time, this classic work presents a cognitive-semiotic framework for understanding how maps work as powerful, abstract, and synthetic spatial representations. Explored are the ways in which the many representational choices inherent in mapping interact with information processing and knowledge construction, and how the resulting insights can be used to make informed symbolization and design decisions. A new preface to the paperback edition situates the book within the context of contemporary technologies. As the nature of maps continues to evolve, Alan MacEachren emphasizes the ongoing need to think systematically about the ways people interact…
In sixth grade, my teacher tried to teach the class how to read line charts – and something fell into place for me. Ever since then, I’ve tried to sort data into forms that we can use to make sense of it. As a researcher at Microsoft, I consulted with teams across the organization – from sales to legal; and from Excel to XBox – to help them understand their data. At Honeycomb, I design tools for software operations teams to diagnose their complex systems. These books each gave me an “ah-hah” moment that made me think differently about the craft of creating visualization. They now sit on my shelf in easy reach – I hope you find them fascinating too.
A new edition of Bertin’s 1963 Semiology was released a few years ago, and my heart swelled with joy. For years, I’d worked off of bad photocopies of an inter-library loan book that had long since gone out of print. In this new edition, I could see how Bertin works through different dimensions and axes – when you want to plot two different quantitative axes over a map, what are your choices? What if you want to plot them over a graph, instead? What changes? I loved exploring these choices with Bertin, as he explores how different color mappings, iconic representations, and design choices change the way the reader interprets the graph.
Originally published in French in 1967, Semiology of Graphics is internationally recognized as a foundational work in the fields of design and cartography. Based on Jacques Bertin's practical experience as a cartographer, part one of this work is an unprecedented attempt to synthesize principles of graphic communication with the logic of standard rules applied to writing and topography. Part two brings Bertin's theory to life, presenting a close study of graphic techniques, including shape, orientation, colour, texture, volume, and size, in an array of more than 1,000 maps and diagrams.
I am a financial data scientist. I think it is important that data scientists are highly specialized if they want to be effective in their careers. I run a business called Conlan Scientific out of Charlotte, NC where me and my team of financial data scientists tackle complicated machine learning problems for our clients. Quant trading is a gladiator’s arena of financial data science. Anyone can try it, but few succeed at it. I am sharing my top five list of math books that are essential to success in this field. I hope you enjoy.
One of my favorite professors, Gretchen Martinet, used this to teach a course called “Mathematical Statistics” when I was at the University of Virginia. It is an extremely profound course full of dense but fundamental mathematical proofs in classical statistics.
You will learn why the formula for the normal distribution is the way it is, why the sum of squares appears everywhere in statistics, and how to fit a linear regression by hand. In the same way calculus elevates our understanding of rates of changes, the book elevates your understanding of samples, averages, and distributions. Quant trading requires an intuitive sense of how data, models, and aggregates work, making this content essential for your success.
Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data.
The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The…
When people ask me why I became a statistician, and what its attraction is, I simply tell them that, using statistics, I have been on voyages of discovery and travelled to worlds they didn’t know existed. Using data and statistical methods instead of light and optics, I have seen things others could not imagine. Like an explorer of old, I have joined adventures peeling back the mysteries of the world around us. In my books on statistics, data science, data mining, and artificial intelligence, I have tried to convey some of this excitement, and to show the reader how they too can take part in this wonderful modern adventure.
This is a wonderful book because it says it all. Of course, that’s an exaggeration because no book could possibly encompass the vast breadth of modern statistics, but anyone who read through this multi-volume work would have an enviable knowledge of the discipline. It’s an unsurpassed general source of information about the foundational concepts and tools of statistics, and a reference source I regularly turn to when I need to remind myself of the theory underlying a concept or method.
I never had a real career. Closest I came was the Air Force Reserve for 27 years. Along the way, I built fighter-vs-fighter computer models for the Defense Department, served as an advisor to a Saudi Air Force prince, led a team that designed a replacement for the Air Force’s A-10 tankbuster (which was never built, unfortunately), sold C-130 transport aircraft in Saudi Arabia, taught statistics in business school, became a yoga instructor, and did PR work in Atlanta. Starting in 1975, I collaborated a little with a retired Air Force colonel, John Boyd, creator of the infamous “OODA loop.” I was never a published author in the US, although I am in India, Portugal, and Japan.
Here’s some bad news for non-STEM people: You’re going to have to learn a little about statistics. Otherwise, at some point, you going to get, as Nassim Nicholas Taleb puts it, “fooled by randomness.” An example: Suppose you’ve been a sales manager for a long time but recently you failed to close a string of prospects. How unusual is this? It could be just a run of bad luck, or is it time to make some significant personnel moves? Basic knowledge of statistics can help. If your math is rusty, you might want to take a stat course for non-math majors. Otherwise, here’s a book that I used with my MBA students that features scenarios from businesses.
Discover how statistical information impacts decisions in today's business world as Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's leading ESSENTIALS OF STATISTICS FOR BUSINESS AND ECONOMICS, 9E connects concepts in each chapter to real-world practice. This edition delivers sound statistical methodology, a proven problem-scenario approach and meaningful applications that reflect the latest developments in business and statistics today. More than 350 new and proven real business examples, a wealth of practical cases and meaningful hands-on exercises highlight statistics in action. You gain practice using leading professional statistical software with exercises and appendices that walk you through using JMP (R) Student Edition 14 and Excel (R) 2016.…
I’m a historian who’s spent far too much time thinking about how the color magenta contributed to climate change and why eighteenth-century humanitarians were obsessed with tobacco enemas. My favorite historical topics—like sensation, color, and truth—don’t initially seem historical, but that’s exactly why they need to be explored. I’ve learned that the things that seem like second nature are where our deepest cultural assumptions and unconscious biases hide. In addition to writing nonfiction, I’ve been lucky enough to grow up on a ranch, live in Paris, work as an interior design writer, teach high school and college, and help stray dogs get adopted.
I had never really given much thought to counting until I read this book, but in the very first chapter, Stone made me rethink everything I thought I knew about “one fish, two fish, red fish, blue fish.” She shows that every time we count, we’re making cultural assumptions. For example, what counts as a fish? And what makes the color of the fish more relevant than other features? Counting reveals that while these choices may seem intuitive, basic, and meaningless, they have very real impacts on people’s lives. Especially when we use numbers to measure things like merit, poverty, race, and productivity, those fundamental assumptions matter more than we care to admit.
Early in her extraordinary career, Deborah Stone wrote Policy Paradox, a landmark work on politics. Now, in Counting, she revolutionises how we approach numbers and shows how counting shapes the way we see the world. Most of us think of counting as a skill so basic that we see numbers as objective, indisputable facts. Not so, says Stone. In this playful-yet-probing work, Stone reveals the inescapable link between quantifying and classifying, and explains how counting determines almost every facet of our lives-from how we are evaluated at work to how our political opinions are polled to whether we get into…
A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.
I have used this book to teach my Financial Risk Analytics course at Northwestern University for many years. As a textbook, it is surprisingly easy to read, and the abundant exercises are great. This would be a foundational text to read after you have read my own books. It puts you on solid ground to understand all the financial babble that you may read elsewhere. It includes extensive coverage of most basic topics important to a serious quantitative trader, while not being overly mathematical. Easily understandable if you have basic programming and math background from first year of university.
Everything is practical in this book, which isn’t what you would expect from a textbook! There is no math for math’s sake. I have used the techniques discussed in this book for real trading, and for creating features at my machine learning SaaS predictnow.ai. Examples: What’s the difference between net…
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code…
I’ve been fascinated by information technology since I was a child–whether in the form of books, libraries, computers, or cell phones! Living through a massive expansion in the volume of data, I believe it is essential to study the long history of information to make sense of our current data-driven times–which is why I became a historian of data, which I teach and write about full time. Here are some of the most informative and insightful books that have helped me make sense of our issues, ranging from information overload and artificial intelligence to privacy and data justice.
Finding yourself overwhelmed, confused, or just plain curious about artificial intelligence?
Then this is the book for you! Wiggins and Jones provide a lucid, comprehensive overview of how we arrived at our current data-saturated times and how artificial intelligence emerged from the political climate of the Cold War as one attempt in a longer history of the ties between political power and information.
I found myself constantly surprised and enlightened by the history of data sketched out by Wiggins and Jones!
From facial recognition-capable of checking us onto flights or identifying undocumented residents-to automated decision systems that inform everything from who gets loans to who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn't just appear: they are part of a history that goes back centuries, from the birth of eugenics in Victorian Britain to the development of Google search.
Expanding on the popular course they created at Columbia University, Chris Wiggins and Matthew Jones illuminate the ways in which data has long been used as a tool and a weapon in arguing…
