nice ggplot intro tutorial. Just run the commands, about 6 pages = flexible 1-3 hours of learning, depending how much reading you want to pair it with
by Ramon Saccilotto
Posts tagged with ggplot2
> data(quakes)> head(quakes)
lat long depth mag stations 1 -20.42 181.62 562 4.8 41 2 -20.62 181.03 650 4.2 15 3 -26.00 184.10 42 5.4 43 4 -17.97 181.66 626 4.1 19 5 -20.42 181.96 649 4.0 11 6 -19.68 184.31 195 4.0 12
> summary(quakes)
lat long depth mag
Min. :-38.59 Min. :165.7 Min. : 40.0 Min. :4.00
1st Qu.:-23.47 1st Qu.:179.6 1st Qu.: 99.0 1st Qu.:4.30
Median :-20.30 Median :181.4 Median :247.0 Median :4.60
Mean :-20.64 Mean :179.5 Mean :311.4 Mean :4.62
3rd Qu.:-17.64 3rd Qu.:183.2 3rd Qu.:543.0 3rd Qu.:4.90
Max. :-10.72 Max. :188.1 Max. :680.0 Max. :6.40
stations
Min. : 10.00
1st Qu.: 18.00
Median : 27.00
Mean : 33.42
3rd Qu.: 42.00
Max. :132.00
> plot(quakes, pch=20, col=rgb(0,0,0,.1) , lwd=.6)
> require(ggplot2)
> qplot(data = quakes, x = lat, y = long, size = exp(mag), color = mag, alpha = I(.8))
UPDATE: In the comments, Sean Mulcahy shared his much better post on earthquakes: http://seanmulcahy.blogspot.com/2011/11/global-earthquakes-desktop.html. He shows how to grab up-to-date earthquake data from the U.S. Geological Survey and display it with R’s maps package. Hooray!
My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]:
—Data is the most important thing, and the thing that you bring to the table.
—Geometric objects … what you actually see on the plot: points, lines, polygons, etc.
—Statistics transform the data in many useful ways. For example, binning and counting to create a histogram….
—Scales map values in the data space to values in an aesthetic space, whether it be colour, or size, or shape. Scales also provide an inverse mapping: a legend.
—A coordinate system describes how data coordinates are mapped to the plane of the graphic. It also provides axes and gridlines to make it possible to read the graph.
— A facetting, or conditioning, speci
