removed URIs invalid for CRAN

.Rbuildignore

@@ -1,6 +1,5 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
-^NEWS\.md$
 ^tools*$
 ^\.travis\.yml$
 ^appveyor\.yml$
@@ -9,3 +8,4 @@
 ^\.lintr$
 ^opensensmapr_.*\.tar\.gz$
 ^cran-comments\.md$
+^CRAN-SUBMISSION$

NEWS.md

@@ -4,7 +4,7 @@ This project does its best to adhere to semantic versioning.
 ### 2023-02-20: v0.6.0
 - fix package bugs to pass CRAN tests after 4 years of maintenance break 
   - updated hyperlinks
-  - dont throw error for empty sensors
+  - don't throw error for empty sensors
   - updated tests
 - updated maintainer
 - updated vignettes
@@ -24,7 +24,7 @@ This project does its best to adhere to semantic versioning.
 - add sensor-IDs to `box$phenomena`
 
 ### 2018-09-21: v0.4.3
-- dynamically export S3 methods of forgeign generics
+- dynamically export S3 methods of foreign generics
   for compatibility with upcoming R 3.6.0
 - add `readr` as default dependency
 
@@ -74,7 +74,7 @@ This project does its best to adhere to semantic versioning.
 ### 2017-08-23: v0.2.0
 - add auto paging for `osem_measurements()`, allowing data retrieval for arbitrary time intervals (#2)
 - improve plots for `osem_measurements` & `sensebox` (#1)
-- add `sensorId` & `unit` colummn to `get_measurements()` output by default
+- add `sensorId` & `unit` column to `get_measurements()` output by default
 - show download progress info, hide readr output
 - shorten vignette `osem-intro`
 

README.md

@@ -59,16 +59,16 @@ devtools::install_github('sensebox/opensensmapr@development') # bleeding edge ve
 
 ## Changelog
 
-This project adheres to semantic versioning, for changes in recent versions please consult [CHANGES.md](CHANGES.md).
+This project adheres to semantic versioning, for changes in recent versions please consult [NEWS.md](NEWS.md).
 
 ## Contributing & Development
 
 Contributions are very welcome!
-When submitting a patch, please follow the existing [code style](.lintr),
+When submitting a patch, please follow the existing code stlye,
 and run `R CMD check --no-vignettes .` on the package.
 Where feasible, also add tests for the added / changed functionality in `tests/testthat`.
 
-Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md).
+Please note that this project is released with a Contributor Code of Conduct.
 By participating in this project you agree to abide by its terms.
 
 ### development environment
@@ -103,10 +103,10 @@ R CMD check --no-vignettes ../opensensmapr_*.tar.gz
 
 To create a release:
 
-0. make shure you are on master branch
+0. make sure you are on master branch
 1. run the tests and checks as described above
 2. bump the version in `DESCRIPTION`
-3. update `CHANGES.md`
+3. update `NEWS.md`
 3. rebuild the documentation: `R -e 'devtools::document()'`
 4. build the package again with the new version: `R CMD build . --no-build-vignettes`
 5. tag the commit with the new version: `git tag v0.5.0`

inst/doc/osem-history.R

@@ -1,4 +1,4 @@
-## ----setup, results='hide', message=FALSE, warning=FALSE-----------------
+## ----setup, results='hide', message=FALSE, warning=FALSE----------------------
 # required packages:
 library(opensensmapr) # data download
 library(dplyr)        # data wrangling
@@ -6,12 +6,12 @@ library(ggplot2)      # plotting
 library(lubridate)    # date arithmetic
 library(zoo)          # rollmean()
 
-## ----download------------------------------------------------------------
+## ----download-----------------------------------------------------------------
 # if you want to see results for a specific subset of boxes,
 # just specify a filter such as grouptag='ifgi' here
 boxes = osem_boxes()
 
-## ----exposure_counts, message=FALSE--------------------------------------
+## ----exposure_counts, message=FALSE-------------------------------------------
 exposure_counts = boxes %>%
   group_by(exposure) %>%
   mutate(count = row_number(createdAt))
@@ -22,7 +22,7 @@ ggplot(exposure_counts, aes(x = createdAt, y = count, colour = exposure)) +
   scale_colour_manual(values = exposure_colors) +
   xlab('Registration Date') + ylab('senseBox count')
 
-## ----exposure_summary----------------------------------------------------
+## ----exposure_summary---------------------------------------------------------
 exposure_counts %>%
   summarise(
     oldest = min(createdAt),
@@ -31,11 +31,11 @@ exposure_counts %>%
   ) %>%
   arrange(desc(count))
 
-## ----grouptag_counts, message=FALSE--------------------------------------
+## ----grouptag_counts, message=FALSE-------------------------------------------
 grouptag_counts = boxes %>%
   group_by(grouptag) %>%
   # only include grouptags with 8 or more members
-  filter(length(grouptag) >= 8 && !is.na(grouptag)) %>%
+  filter(length(grouptag) >= 8 & !is.na(grouptag)) %>%
   mutate(count = row_number(createdAt))
 
 # helper for sorting the grouptags by boxcount
@@ -49,7 +49,7 @@ ggplot(grouptag_counts, aes(x = createdAt, y = count, colour = grouptag)) +
   geom_line(aes(group = grouptag)) +
   xlab('Registration Date') + ylab('senseBox count')
 
-## ----grouptag_summary----------------------------------------------------
+## ----grouptag_summary---------------------------------------------------------
 grouptag_counts %>%
   summarise(
     oldest = min(createdAt),
@@ -58,7 +58,7 @@ grouptag_counts %>%
   ) %>%
   arrange(desc(count))
 
-## ----growthrate_registered, warning=FALSE, message=FALSE, results='hide'----
+## ----growthrate_registered, warning=FALSE, message=FALSE, results='hide'------
 bins = 'week'
 mvavg_bins = 6
 
@@ -68,7 +68,7 @@ growth = boxes %>%
   summarize(count = length(week)) %>%
   mutate(event = 'registered')
 
-## ----growthrate_inactive, warning=FALSE, message=FALSE, results='hide'----
+## ----growthrate_inactive, warning=FALSE, message=FALSE, results='hide'--------
 inactive = boxes %>%
   # remove boxes that were updated in the last two days,
   # b/c any box becomes inactive at some point by definition of updatedAt
@@ -78,7 +78,7 @@ inactive = boxes %>%
   summarize(count = length(week)) %>%
   mutate(event = 'inactive')
 
-## ----growthrate, warning=FALSE, message=FALSE, results='hide'------------
+## ----growthrate, warning=FALSE, message=FALSE, results='hide'-----------------
 boxes_by_date = bind_rows(growth, inactive) %>% group_by(event)
 
 ggplot(boxes_by_date, aes(x = as.Date(week), colour = event)) +
@@ -89,7 +89,7 @@ ggplot(boxes_by_date, aes(x = as.Date(week), colour = event)) +
   # moving average, make first and last value NA (to ensure identical length of vectors)
   geom_line(aes(y = rollmean(count, mvavg_bins, fill = list(NA, NULL, NA))))
 
-## ----exposure_duration, message=FALSE------------------------------------
+## ----exposure_duration, message=FALSE-----------------------------------------
 duration = boxes %>%
   group_by(exposure) %>%
   filter(!is.na(updatedAt)) %>%
@@ -99,11 +99,11 @@ ggplot(duration, aes(x = exposure, y = duration)) +
   geom_boxplot() +
   coord_flip() + ylab('Duration active in Days')
 
-## ----grouptag_duration, message=FALSE------------------------------------
+## ----grouptag_duration, message=FALSE-----------------------------------------
 duration = boxes %>%
   group_by(grouptag) %>%
   # only include grouptags with 8 or more members
-  filter(length(grouptag) >= 8 && !is.na(grouptag) && !is.na(updatedAt)) %>%
+  filter(length(grouptag) >= 8 & !is.na(grouptag) & !is.na(updatedAt)) %>%
   mutate(duration = difftime(updatedAt, createdAt, units='days'))
   
 ggplot(duration, aes(x = grouptag, y = duration)) +
@@ -119,7 +119,7 @@ duration %>%
   ) %>%
   arrange(desc(duration_avg))
 
-## ----year_duration, message=FALSE----------------------------------------
+## ----year_duration, message=FALSE---------------------------------------------
 # NOTE: boxes older than 2016 missing due to missing updatedAt in database
 duration = boxes %>%
   mutate(year = cut(as.Date(createdAt), breaks = 'year')) %>%

inst/doc/osem-history.Rmd

@@ -68,7 +68,7 @@ ggplot(exposure_counts, aes(x = createdAt, y = count, colour = exposure)) +
 Outdoor boxes are growing *fast*!
 We can also see the introduction of `mobile` sensor "stations" in 2017. While
 mobile boxes are still few, we can expect a quick rise in 2018 once the new
-[senseBox MCU with GPS support is released](https://sensebox.de/blog/2018-03-06-senseBox_MCU).
+senseBox MCU with GPS support is released.
 
 Let's have a quick summary:
 ```{r exposure_summary}
@@ -93,7 +93,7 @@ inconsistent (`Luftdaten`, `luftdaten.info`, ...)
 grouptag_counts = boxes %>%
   group_by(grouptag) %>%
   # only include grouptags with 8 or more members
-  filter(length(grouptag) >= 8 && !is.na(grouptag)) %>%
+  filter(length(grouptag) >= 8 & !is.na(grouptag)) %>%
   mutate(count = row_number(createdAt))
 
 # helper for sorting the grouptags by boxcount
@@ -163,7 +163,7 @@ ggplot(boxes_by_date, aes(x = as.Date(week), colour = event)) +
 
 We see a sudden rise in early 2017, which lines up with the fast growing grouptag `Luftdaten`.
 This was enabled by an integration of openSenseMap.org into the firmware of the
-air quality monitoring project [luftdaten.info](https://luftdaten.info).
+air quality monitoring project [luftdaten.info](https://sensor.community/de/).
 The dips in mid 2017 and early 2018 could possibly be explained by production/delivery issues
 of the senseBox hardware, but I have no data on the exact time frames to verify.
 
@@ -192,7 +192,7 @@ spanning a large chunk of openSenseMap's existence.
 duration = boxes %>%
   group_by(grouptag) %>%
   # only include grouptags with 8 or more members
-  filter(length(grouptag) >= 8 && !is.na(grouptag) && !is.na(updatedAt)) %>%
+  filter(length(grouptag) >= 8 & !is.na(grouptag) & !is.na(updatedAt)) %>%
   mutate(duration = difftime(updatedAt, createdAt, units='days'))
   
 ggplot(duration, aes(x = grouptag, y = duration)) +

inst/doc/osem-history_revised.R

@@ -0,0 +1,162 @@
+## ----setup, results='hide', message=FALSE, warning=FALSE----------------------
+# required packages:
+library(opensensmapr) # data download
+library(dplyr)        # data wrangling
+library(ggplot2)      # plotting
+library(lubridate)    # date arithmetic
+library(zoo)          # rollmean()
+
+## ----download, results='hide', message=FALSE, warning=FALSE-------------------
+# if you want to see results for a specific subset of boxes,
+# just specify a filter such as grouptag='ifgi' here
+boxes_all = osem_boxes()
+boxes = boxes_all
+
+## -----------------------------------------------------------------------------
+boxes = filter(boxes, locationtimestamp >= "2022-01-01" & locationtimestamp <="2022-12-31")
+summary(boxes) -> summary.data.frame
+
+## ----message=F, warning=F-----------------------------------------------------
+if (!require('maps'))     install.packages('maps')
+if (!require('maptools')) install.packages('maptools')
+if (!require('rgeos'))    install.packages('rgeos')
+
+plot(boxes)
+
+## -----------------------------------------------------------------------------
+phenoms = osem_phenomena(boxes)
+str(phenoms)
+
+## -----------------------------------------------------------------------------
+phenoms[phenoms > 50]
+
+## ----exposure_counts, message=FALSE-------------------------------------------
+exposure_counts = boxes %>%
+  group_by(exposure) %>%
+  mutate(count = row_number(locationtimestamp))
+
+exposure_colors = c(indoor = 'red', outdoor = 'lightgreen', mobile = 'blue', unknown = 'darkgrey')
+ggplot(exposure_counts, aes(x = locationtimestamp, y = count, colour = exposure)) +
+  geom_line() +
+  scale_colour_manual(values = exposure_colors) +
+  xlab('Registration Date') + ylab('senseBox count')
+
+## ----exposure_summary---------------------------------------------------------
+exposure_counts %>%
+  summarise(
+    oldest = min(locationtimestamp),
+    newest = max(locationtimestamp),
+    count = max(count)
+  ) %>%
+  arrange(desc(count))
+
+## ----grouptag_counts, message=FALSE-------------------------------------------
+grouptag_counts = boxes %>%
+  group_by(grouptag) %>%
+  # only include grouptags with 15 or more members
+  filter(length(grouptag) >= 15 & !is.na(grouptag) & grouptag != '') %>%
+  mutate(count = row_number(locationtimestamp))
+
+# helper for sorting the grouptags by boxcount
+sortLvls = function(oldFactor, ascending = TRUE) {
+  lvls = table(oldFactor) %>% sort(., decreasing = !ascending) %>% names()
+  factor(oldFactor, levels = lvls)
+}
+grouptag_counts$grouptag = sortLvls(grouptag_counts$grouptag, ascending = FALSE)
+
+ggplot(grouptag_counts, aes(x = locationtimestamp, y = count, colour = grouptag)) +
+  geom_line(aes(group = grouptag)) +
+  xlab('Registration Date') + ylab('senseBox count')
+
+## ----grouptag_summary---------------------------------------------------------
+grouptag_counts %>%
+  summarise(
+    oldest = min(locationtimestamp),
+    newest = max(locationtimestamp),
+    count = max(count)
+  ) %>%
+  arrange(desc(count))
+
+## ----growthrate_registered, warning=FALSE, message=FALSE, results='hide'------
+bins = 'week'
+mvavg_bins = 6
+
+growth = boxes %>%
+  mutate(week = cut(as.Date(locationtimestamp), breaks = bins)) %>%
+  group_by(week) %>%
+  summarize(count = length(week)) %>%
+  mutate(event = 'registered')
+
+## ----growthrate_inactive, warning=FALSE, message=FALSE, results='hide'--------
+inactive = boxes %>%
+  # remove boxes that were updated in the last two days,
+  # b/c any box becomes inactive at some point by definition of updatedAt
+  filter(lastMeasurement < now() - days(2)) %>%
+  mutate(week = cut(as.Date(lastMeasurement), breaks = bins)) %>%
+  filter(as.Date(week) > as.Date("2021-12-31")) %>%
+  group_by(week) %>%
+  summarize(count = length(week)) %>%
+  mutate(event = 'inactive')
+
+## ----growthrate, warning=FALSE, message=FALSE, results='hide'-----------------
+boxes_by_date = bind_rows(growth, inactive) %>% group_by(event)
+
+ggplot(boxes_by_date, aes(x = as.Date(week), colour = event)) +
+  xlab('Time') + ylab(paste('rate per ', bins)) +
+  scale_x_date(date_breaks="years", date_labels="%Y") +
+  scale_colour_manual(values = c(registered = 'lightgreen', inactive = 'grey')) +
+  geom_point(aes(y = count), size = 0.5) +
+  # moving average, make first and last value NA (to ensure identical length of vectors)
+  geom_line(aes(y = rollmean(count, mvavg_bins, fill = list(NA, NULL, NA))))
+
+## ----table_mostregistrations--------------------------------------------------
+boxes_by_date %>%
+  filter(count > 50) %>%
+  arrange(desc(count))
+
+## ----exposure_duration, message=FALSE-----------------------------------------
+durations = boxes %>%
+  group_by(exposure) %>%
+  filter(!is.na(lastMeasurement)) %>%
+  mutate(duration = difftime(lastMeasurement, locationtimestamp, units='days')) %>%
+  filter(duration >= 0)
+
+ggplot(durations, aes(x = exposure, y = duration)) +
+  geom_boxplot() +
+  coord_flip() + ylab('Duration active in Days')
+
+## ----grouptag_duration, message=FALSE-----------------------------------------
+durations = boxes %>%
+  filter(!is.na(lastMeasurement)) %>%
+  group_by(grouptag) %>%
+  # only include grouptags with 20 or more members
+  filter(length(grouptag) >= 15 & !is.na(grouptag) & !is.na(lastMeasurement)) %>%
+  mutate(duration = difftime(lastMeasurement, locationtimestamp, units='days')) %>%
+  filter(duration >= 0)
+  
+ggplot(durations, aes(x = grouptag, y = duration)) +
+  geom_boxplot() +
+  coord_flip() + ylab('Duration active in Days')
+
+durations %>%
+  summarize(
+    duration_avg = round(mean(duration)),
+    duration_min = round(min(duration)),
+    duration_max = round(max(duration)),
+    oldest_box = round(max(difftime(now(), locationtimestamp, units='days')))
+  ) %>%
+  arrange(desc(duration_avg))
+
+## ----year_duration, message=FALSE---------------------------------------------
+# NOTE: boxes older than 2016 missing due to missing updatedAt in database
+duration = boxes %>%
+  mutate(year = cut(as.Date(locationtimestamp), breaks = 'year')) %>%
+  group_by(year) %>%
+  filter(!is.na(lastMeasurement)) %>%
+  mutate(duration = difftime(lastMeasurement, locationtimestamp, units='days')) %>%
+  filter(duration >= 0)
+
+ggplot(duration, aes(x = substr(as.character(year), 0, 4), y = duration)) +
+  geom_boxplot() +
+  coord_flip() + ylab('Duration active in Days') + xlab('Year of Registration')
+

inst/doc/osem-history_revised.Rmd

@@ -1,5 +1,5 @@
 ---
-title: "Visualising the Develpment of openSenseMap.org in 2022"
+title: "Visualising the Development of openSenseMap.org in 2022"
 author: "Jan Stenkamp"
 date: '`r Sys.Date()`'
 output:
@@ -15,7 +15,7 @@ output:
     fig_width: 7
     toc: yes
 vignette: >
-  %\VignetteIndexEntry{Visualising the History of openSenseMap.org}
+  %\VignetteIndexEntry{Visualising the Development of openSenseMap.org in 2022}
   %\VignetteEncoding{UTF-8}
   %\VignetteEngine{knitr::rmarkdown}
 ---
@@ -25,9 +25,7 @@ vignette: >
 
 ```{r setup, results='hide', message=FALSE, warning=FALSE}
 # required packages:
-# library(opensensmapr) # data download
+library(opensensmapr) # data download
-library(devtools)
-load_all(".")
 library(dplyr)        # data wrangling
 library(ggplot2)      # plotting
 library(lubridate)    # date arithmetic
@@ -140,7 +138,7 @@ inconsistent (`Luftdaten`, `luftdaten.info`, ...)
 grouptag_counts = boxes %>%
   group_by(grouptag) %>%
   # only include grouptags with 15 or more members
-  filter(length(grouptag) >= 15 && !is.na(grouptag) && grouptag != '') %>%
+  filter(length(grouptag) >= 15 & !is.na(grouptag) & grouptag != '') %>%
   mutate(count = row_number(locationtimestamp))
 
 # helper for sorting the grouptags by boxcount

inst/doc/osem-intro.R

@@ -1,41 +1,41 @@
-## ----setup, include=FALSE------------------------------------------------
+## ----setup, include=FALSE-----------------------------------------------------
 knitr::opts_chunk$set(echo = TRUE)
 
-## ----results = F---------------------------------------------------------
+## ----results = F--------------------------------------------------------------
 library(magrittr)
 library(opensensmapr)
 
 all_sensors = osem_boxes()
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 summary(all_sensors)
 
-## ----message=F, warning=F------------------------------------------------
+## ----message=F, warning=F-----------------------------------------------------
 if (!require('maps'))     install.packages('maps')
 if (!require('maptools')) install.packages('maptools')
 if (!require('rgeos'))    install.packages('rgeos')
 
 plot(all_sensors)
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 phenoms = osem_phenomena(all_sensors)
 str(phenoms)
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 phenoms[phenoms > 20]
 
-## ----results = F---------------------------------------------------------
+## ----results = F--------------------------------------------------------------
 pm25_sensors = osem_boxes(
   exposure = 'outdoor',
   date = Sys.time(), # ±4 hours
   phenomenon = 'PM2.5'
 )
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 summary(pm25_sensors)
 plot(pm25_sensors)
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 library(sf)
 library(units)
 library(lubridate)
@@ -49,25 +49,25 @@ berlin = st_point(c(13.4034, 52.5120)) %>%
   st_transform(4326) %>% # the opensensemap expects WGS 84
   st_bbox()
 
-## ----results = F---------------------------------------------------------
+## ----results = F--------------------------------------------------------------
 pm25 = osem_measurements(
   berlin,
   phenomenon = 'PM2.5',
-  from = now() - days(20), # defaults to 2 days
+  from = now() - days(3), # defaults to 2 days
   to = now()
 )
 
 plot(pm25)
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 outliers = filter(pm25, value > 100)$sensorId
 bad_sensors = outliers[, drop = T] %>% levels()
 
 pm25 = mutate(pm25, invalid = sensorId %in% bad_sensors)
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 st_as_sf(pm25) %>% st_geometry() %>% plot(col = factor(pm25$invalid), axes = T)
 
-## ------------------------------------------------------------------------
+## -----------------------------------------------------------------------------
 pm25 %>% filter(invalid == FALSE) %>% plot()
 

inst/doc/osem-intro.Rmd

@@ -18,7 +18,7 @@ knitr::opts_chunk$set(echo = TRUE)
 ```
 
 This package provides data ingestion functions for almost any data stored on the
-open data platform for environemental sensordata <https://opensensemap.org>.
+open data platform for environmental sensordata <https://opensensemap.org>.
 Its main goals are to provide means for:
 
 - big data analysis of the measurements stored on the platform
@@ -97,7 +97,7 @@ Thats still more than 200 measuring stations, we can work with that.
 
 ### Analyzing sensor data
 Having analyzed the available data sources, let's finally get some measurements.
-We could call `osem_measurements(pm25_sensors)` now, however we are focussing on
+We could call `osem_measurements(pm25_sensors)` now, however we are focusing on
 a restricted area of interest, the city of Berlin.
 Luckily we can get the measurements filtered by a bounding box:
 
@@ -119,7 +119,7 @@ berlin = st_point(c(13.4034, 52.5120)) %>%
 pm25 = osem_measurements(
   berlin,
   phenomenon = 'PM2.5',
-  from = now() - days(20), # defaults to 2 days
+  from = now() - days(3), # defaults to 2 days
   to = now()
 )
 

inst/doc/osem-serialization.R

@@ -1,10 +1,10 @@
-## ----setup, results='hide'-----------------------------------------------
+## ----setup, results='hide'----------------------------------------------------
 # this vignette requires:
 library(opensensmapr)
 library(jsonlite)
 library(readr)
 
-## ----cache---------------------------------------------------------------
+## ----cache--------------------------------------------------------------------
 b = osem_boxes(grouptag = 'ifgi', cache = tempdir())
 
 # the next identical request will hit the cache only!
@@ -13,31 +13,31 @@ b = osem_boxes(grouptag = 'ifgi', cache = tempdir())
 # requests without the cache parameter will still be performed normally
 b = osem_boxes(grouptag = 'ifgi')
 
-## ----cachelisting--------------------------------------------------------
+## ----cachelisting-------------------------------------------------------------
 list.files(tempdir(), pattern = 'osemcache\\..*\\.rds')
 
-## ----cache_custom--------------------------------------------------------
+## ----cache_custom-------------------------------------------------------------
 cacheDir = getwd() # current working directory
 b = osem_boxes(grouptag = 'ifgi', cache = cacheDir)
 
 # the next identical request will hit the cache only!
 b = osem_boxes(grouptag = 'ifgi', cache = cacheDir)
 
-## ----clearcache----------------------------------------------------------
+## ----clearcache, results='hide'-----------------------------------------------
 osem_clear_cache()        # clears default cache
 osem_clear_cache(getwd()) # clears a custom cache
 
-## ----data, results='hide'------------------------------------------------
+## ----data, results='hide'-----------------------------------------------------
 # first get our example data:
-measurements = osem_measurements('Windrichtung')
+measurements = osem_measurements('Windgeschwindigkeit')
 
-## ----serialize_json------------------------------------------------------
+## ----serialize_json-----------------------------------------------------------
 # serializing senseBoxes to JSON, and loading from file again:
 write(jsonlite::serializeJSON(measurements), 'measurements.json')
 measurements_from_file = jsonlite::unserializeJSON(readr::read_file('measurements.json'))
 class(measurements_from_file)
 
-## ----serialize_attrs-----------------------------------------------------
+## ----serialize_attrs----------------------------------------------------------
 # note the toJSON call instead of serializeJSON
 write(jsonlite::toJSON(measurements), 'measurements_bad.json')
 measurements_without_attrs = jsonlite::fromJSON('measurements_bad.json')
@@ -46,6 +46,6 @@ class(measurements_without_attrs)
 measurements_with_attrs = osem_as_measurements(measurements_without_attrs)
 class(measurements_with_attrs)
 
-## ----cleanup, include=FALSE----------------------------------------------
+## ----cleanup, include=FALSE---------------------------------------------------
 file.remove('measurements.json', 'measurements_bad.json')
 

inst/doc/osem-serialization.Rmd

@@ -73,7 +73,7 @@ here's how:
 
 ```{r data, results='hide'}
 # first get our example data:
-measurements = osem_measurements('Windrichtung')
+measurements = osem_measurements('Windgeschwindigkeit')
 ```
 
 If you are paranoid and worry about `.rds` files not being decodable anymore

vignettes/osem-history_revised.Rmd

@@ -1,5 +1,5 @@
 ---
-title: "Visualising the Develpment of openSenseMap.org in 2022"
+title: "Visualising the Development of openSenseMap.org in 2022"
 author: "Jan Stenkamp"
 date: '`r Sys.Date()`'
 output:
@@ -15,7 +15,7 @@ output:
     fig_width: 7
     toc: yes
 vignette: >
-  %\VignetteIndexEntry{Visualising the Develpment of openSenseMap.org in 2022}
+  %\VignetteIndexEntry{Visualising the Development of openSenseMap.org in 2022}
   %\VignetteEncoding{UTF-8}
   %\VignetteEngine{knitr::rmarkdown}
 ---

vignettes/osem-intro.Rmd

@@ -18,7 +18,7 @@ knitr::opts_chunk$set(echo = TRUE)
 ```
 
 This package provides data ingestion functions for almost any data stored on the
-open data platform for environemental sensordata <https://opensensemap.org>.
+open data platform for environmental sensordata <https://opensensemap.org>.
 Its main goals are to provide means for:
 
 - big data analysis of the measurements stored on the platform