Name: The elements of graphing data
ISBN: 9780963488411

The elements of graphing data

Contains graphical methods and principles for visualizing data in science and technology. Emphasizes the basic ideas, methods, and principles for creating readable graphs through an understanding of human visual and graphical perception, with a small section on computer graphics. Covers graphical methods, such as logarithms, visual reference grids, and statistical variation, and issues in graphical perception, including superposed curves, color encoding, and graphing along a common scale. Annotation copyright by Book News, Inc., Portland, OR

What Hacker News says

stiffNov 2023

William Cleveland did some research along those lines and he wrote two good books:

    - The elements of graphing data

    - Visualizing data

The first one is of general interest, the second one more specialized for statisticians.

thread

zcw100Dec 2021

William Cleveland, "Elements of Graphing Data"[1] and "Visualizing Data"[2]

Cleveland worked at Bell Labs and his work is timeless and very practical. It isn't about artwork or making things look nice. It's about communicating information. I like to contrast his work with Tufte's. Tufte comes up with some nice stuff but I find it to be more art than science where the information is clearly sacrificed to ascetics. With visualizations I always ask myself, "Do you know more now about what is going on than you did before or is it just something nice to look at?" Way too often it's the latter.

[1] https://www.amazon.com/Elements-Graphing-Data-William-Clevel...

[2] https://www.amazon.com/Visualizing-Data-William-S-Cleveland/...

thread

kylebgormanJul 2013

The difference between Cleveland and Tufte is that the former is "empirical" (he discusses lots of results from psychological studies on comprehension of graphics) rather than one man's opinion. Also, Cleveland actually has accomplished something other than scolding and praising.

Personally, I liked Cleveland's "Elements of Graphing Data" (http://www.amazon.com/Elements-Graphing-Data-William-Clevela...) better than "Visualizing Data", though they overlap a lot.

thread

jmountJul 2013

Another good source on visual presentation (of data) is Cleveland (author of "The Elements of Graphing Data", see http://www.win-vector.com/blog/2013/02/revisiting-clevelands... ). The neat thing is Cleveland formally tested a lot of his visualization principles (asking people to estimate things from different graphs).

thread

pseutDec 2012

Depends on the data sets you want to work with. For straight-up linear regression, with a heavy emphasis on observational data appropriate for microeconometrics, "Introductory Econometrics: A Modern Approach" by Jeff Wooldridge is absolutely phenomenal (an old edition is fine). (This is usually assigned for advanced undergraduate econ majors or non-advanced masters students; I don't know what the equivalent would be for undergraduate stats majors).

For more "intuition about working with data, especially if you're a visual person," Howard Wainer's books are wonderful; one example is "Graphic Discovery: A Trout in the Milk and Other Visual Adventures." They're non-technical, short chapters, discussions of different data sets.

Bill Cleveland's "Visualizing Data" and "Elements of Graphing Data" cover the same material -- graphing data -- at a more technical level. I don't know Cleveland's books would help with the issues you asked about, but... they are amazing books and if you're interested in the subject at all I can't recommend them highly enough.

I don't have any free recommendations, unfortunately.

thread

dmlorenzettiJan 2011

Largely for historical reasons, I mostly use R. It requires a lot of care & feeding, but rewards you with a lot of control.

A colleague uses MatPlotLib under Python. He makes nice-looking plots with it, and when I watch him driving it, I feel like I could learn to work with it pretty easily. The only reason I haven't given it a real try is the cost of setting up the larger framework I would want to use to generate the points I plot.

I used gnuplot for a project. It's conceptually easy to work with, but the inconsistent looks between different output formats (e.g., PNG vs SVG) made me choose it simply because scripting it from the command line was easy. Another gripe I had was that, given a file with multiple columns of data to plot, it has to parse the file once for every curve it puts in the plot. Finally, I found gnuplot wasn't very smart about how it chose points when plotting expressions (e.g., telling it to plot "sin(x)" rather than passing it points on a sine curve).

Re guides, I liked William Cleveland's "Elements of Graphing Data". However, I'm not widely-read on this subject, so this is kind of one point in the noise.

thread