I would like some feedback on the functions introduced here and thoughts on whether they should be included in the base collar package.
We previously discussed how inclusive the base collar package should be and it seems we settled on a single broader package with function prefixes to differentiate groups of functions.
Here I introduce two new prefixes: collar::filter* and collar::produce*. Thoughts?
An example of how I envision using these functions (assuming the data is already formatted using the collar standard) is below. Once we have established a collar object class these functions can be simplified further, however, for the time being I have a number of assert_that statements to check the data input.
df %>%
collar::filter_last_loc() %>%
collar::filter_date_range(start = Sys.Date() - 30) %>%
collar::produce_gpx() %>% # Completely separate from the map below
collar::produce_map(save_html = T)
Is the utility provided here of value? General thoughts and suggestions for improvement?
I would like some feedback on the functions introduced here and thoughts on whether they should be included in the base collar package.
We previously discussed how inclusive the base collar package should be and it seems we settled on a single broader package with function prefixes to differentiate groups of functions.
Here I introduce two new prefixes: collar::filter* and collar::produce*. Thoughts?
An example of how I envision using these functions (assuming the data is already formatted using the collar standard) is below. Once we have established a collar object class these functions can be simplified further, however, for the time being I have a number of assert_that statements to check the data input.
Is the utility provided here of value? General thoughts and suggestions for improvement?
Thanks!