data exploration tables/ggplot

inbo / camtraptor

Camtraptor is an R package to read, explore and visualize Camera Trap Data Packages (Camtrap DP)

https://inbo.github.io/camtraptor/

MIT License

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data exploration tables/ggplot #38

Open jimcasaer opened 3 years ago

jimcasaer commented 3 years ago

similar to the geographical data visualization based on deployments, most features used in map_dep() are also interesting to explore data based on timescales (day, week, month, year, period (from - till)) visualization is possible using timescale as x-axis /

possible features:

effort (different units)
number of cameras active
number of deployments
number of observed species
number of observations (a subset of species)
rai

possible timescales day week month year period (from - till))

possible output

table or dataframe
ggplot

** seems to be logical to make again use of predicates for this data exploration functions

damianooldoni commented 3 years ago

I suppose you have histograms in mind, right? No lines or points...

jimcasaer commented 3 years ago

yep !

although when the timescale is the day the histograms will resemble lines :-)

damianooldoni commented 3 years ago

A little overview with some questions about the list of features you would like to plot.

The following can be indeed plot with time on the x-axis and using different scales:

number of cameras active
number of observed species
number of observations (a subset of species)

This one I don't understand:

number of deployments

If I well understand a deployment is linked to a camera, so the number of active cameras is equal to the number of active deployments at a certain moment? One of the two is therefore redundant?

The following ones I think I need more explanation:

effort
RAI

Do you mean a cumulative effort RAI over all deployments as function of time?

jimcasaer commented 3 years ago

@damianooldoni

[ ] the number of active camera's and the number of deployments do indeed coincide
[ ] effort from xx till yy equals the number of days (24 hours) cameras were active between xx en yy * 24 hours (or start/end hours)
[ ] RAI is based on the number of observations (for a species) between xx and yy divided by the effort between xx and yy

<= the camOps table can play a role as input for the effort calculation <= the number of observations is calculated directly from the datapackage$observations table or from record.table