remove note about #3, fix typos

R/box_utils.R

@@ -41,7 +41,7 @@ print.sensebox = function(x, ...) {
 
 #' @export
 summary.sensebox = function(object, ...) {
-  cat('box total:', nrow(object), fill = T)
+  cat('boxes total:', nrow(object), fill = T)
   cat('\nboxes by exposure:')
   table(object$exposure) %>% print()
   cat('\nboxes by model:')

vignettes/osem-intro.Rmd

@@ -26,11 +26,6 @@ Its main goals are to provide means for:
 - big data analysis of the measurements stored on the platform
 - sensor metadata analysis (sensor counts, spatial distribution, temporal trends)
 
-> *Please note:* The openSenseMap API is sometimes a bit unstable when streaming
-long responses, which results in `curl` complaining about `Unexpected EOF`. This
-bug is being worked on upstream. Meanwhile you have to retry the request when
-this occurs.
-
 ### Exploring the dataset
 Before we look at actual observations, lets get a grasp of the openSenseMap
 datasets' structure.
@@ -45,14 +40,14 @@ all_sensors = osem_boxes()
 summary(all_sensors)
 ```
 
-This gives a good overview already: As of writing this, there are more than 600
+This gives a good overview already: As of writing this, there are more than 700
 sensor stations, of which ~50% are currently running. Most of them are placed
 outdoors and have around 5 sensors each.
 The oldest station is from May 2014, while the latest station was registered a
 couple of minutes ago.
 
-Another feature of interest is the spatial distribution of the boxes. `plot()`
-can help us out here. This function requires a bunch of optional dependcies though.
+Another feature of interest is the spatial distribution of the boxes: `plot()`
+can help us out here. This function requires a bunch of optional dependencies though.
 
 ```{r message=F, warning=F}
 if (!require('maps'))     install.packages('maps')
@@ -117,7 +112,7 @@ library(lubridate)
 berlin = st_point(c(13.4034, 52.5120)) %>%
   st_sfc(crs = 4326) %>%
   st_transform(3857) %>% # allow setting a buffer in meters
-  st_buffer(units::set_units(12, km)) %>%
+  st_buffer(set_units(12, km)) %>%
   st_transform(4326) %>% # the opensensemap expects WGS 84
   st_bbox()
 ```