**dylan's blog**, and kindly contributed to R-bloggers)

Several recent articles appeared on the R-bloggers feed aggregator that demonstrated an interesting visualization of time series data using color. This style of visualization was readily adapted for the time series data I regularly collect (soil moisture and temperature), and quickly implemented with the `levelplot()` function from the lattice package. I hadn't previously considered using a mixture of factor (categorical) and continuous variables within a call to `levelplot()`, however the resulting figure was more useful than expected (see above). A single day's observation is represented by a colored strip (redder hues are higher temperature values, and lower soil moisture values), placed along the x-axis according to the date of that observation, and in a row defined by the location where that observation was collected from. Paneling of the data can be used to represent a more complex hierarchy, such as sensor depth or landscape position. At the expense of *quantitative data retrieval* (which is better supported be scatter plots), *qualitative patterns* are quickly identified within the new graphic.

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**dylan's blog**.

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