How to read a coplot() graph - r

Question

I cannot warp my mind arround reading the plots generated by coplot().
For example from the help(coplot)
## Tonga Trench Earthquakes
coplot(lat ~ long | depth, data = quakes)
What do the gray bars above represent? Why are there 2 rows or lat/long boxes?
How do I read this graph?

Answer 1

I can shed some more light on the second chart's interpretation. The gray bars for both mag and depth represent intervals of the their respective variables. Andy gave a nice description of how they are created above.
When you are reading them keep in mind that they are meant to show you the range of the observations for the respective conditioning variable (mag or depth) represented in each column or row. Therefore, in Andy's example the largest mag bar is just showing that the topmost row contains observations for earthquakes of approx. 4.6 to 7. It makes sense that this bar is the largest, since as Andy mentioned, they are created to have roughly similar numbers of observations and stronger earthquakes are not as common as weaker ones. The same logic holds true for depth where a larger range of depths was required to get a roughly proportional number of observations.
Regarding reading the chart, you would read the columns as representing the three depth groups (left to right) and the rows as representing the four mag groups (bottom to top). Thus, as you read up the chart you're progressively slicing the data into groups of observations with increasing magnitudes. So, for example, the bottom row represents earthquakes with magnitudes of 4 to 4.5 with each column representing a different range of depths. Similarly, you read the columns as holding depth constant while allowing you to see various ranges of magnitudes.
Putting it all together, as mentioned by Andy, we can see that as we read up the rows (progressing up in magnitude) the distribution of earthquakes remains relatively unchanged. However, when reading across the columns (progressing up in depth) we see that the distribution does slightly change. Specifically, the grouping of quakes on the right, between longitudes 180 and 185, grows tighter and more clustered towards the top of the cell.

Answer 2

This is a method for visualizing interactions in your dataset. More specifically, it lets you see how some set of variables are conditional on some other set of variables.
In the example given, you're asking to visualize how lat and long vary with depth. Because you didn't specify number, and the formula indicates you're interested in only one conditional variable, the function assumes you want number=6 depth cuts (passed to co.intervals, which tries to make the number of data points approximately equal within each interval) and is simply maximizing the data-to-ink ratio by stacking individual plot frames; the value of depth increases to the right, starting with the lowest row and moving up (hence the top-right frame represents the largest depth interval). You can set rows or columns to change this behavior, e.g.:
coplot(lat ~ long | depth, data = quakes, columns=6)
but I think the power of this tool becomes more apparent when you inspect two or more conditioning variables. For example:
coplot(lat ~ long | depth * mag, data = quakes, number=c(3,4))
gives a rich view of how earthquakes vary in space, and demonstrates that there is some interaction with depth (the pattern changes from left to right), and little-to-no interaction with magnitude (the pattern does not change from top to bottom).
Finally, I would highly recommend reading Cleveland's Visualizing Data -- a classic text.