Visualizations

[bpbond]

Hi @10aDing can you paste in some of your current data visualizations so we can discuss.

Also to-do from our call: join MAT/MAP with Q10 tables, and then graph MAT (x) versus MAP (y), coloring points by computed Q10.

[bpbond]

Re Q10 over time graphs:

• for day versus night, just use Rs because this is one we would expect might really vary
• try point instead of lines to reduce visual clutter
• a separate graph could show Rs versus Rh for daytime only
• all these facet by dataset probably

[bpbond]

Another great visualization would be plot the sites on a world map. For example:

library(sp)
library(leaflet)
df <- data.frame(label = paste(desc$CSR_DATASET, desc$CSR_SITE_NAME),
                 lon = desc$CSR_LONGITUDE, lat = desc$CSR_LATITUDE)
df <- subset(df, !is.na(lon) & !is.na(lat))
coordinates(df) <- ~lon + lat
lflt <- addMarkers(leaflet(df), label = df$label)
addTiles(lflt)

[CollinWoo]

Should I separate based on depth for the Q10 over time graphs?

[bpbond]

Hmm good question. I would try plotting all, but if that gets too busy, maybe just pick T5 for example.

[CollinWoo]

For the MAT vs. MAP plot with color by Q10, aren't there many different Q10s for each MAT/MAP pair (one for each month)? How would I show all the different colors? Should I average the Q10s for each site?

[CollinWoo]

Data visualizations

[bpbond]

Nice job! Are these for Rs, Rh, both combined?

[bpbond]

For the MAT vs. MAP plot with color by Q10, aren't there many different Q10s for each MAT/MAP pair (one for each month)? How would I show all the different colors? Should I average the Q10s for each site?

Good question. Maybe start by trying geom_jitter() instead of geom_point(), which will spread out the points around the MAT/MAP location.