decentlabr is an R interface to the Decentlab API. decentlabr uses a collection of provided functions and formats the returns for rapid data analysis and use.
To gain access to the API, credentials are needed in the form of a domain and key.
To install the development version the remotes package will need to be installed first. Then:
# Install decentlabr
remotes::install_github("skgrange/decentlabr")
decentlabr has two primary functions: get_decentlab_last_values and get_decentlab_time_series. get_decentlab_last_values returns a table that contains the devices and sensors that are available for a given domain (user). For example, using demo credentials, there are 105 time series (device-sensor pairs) that can be downloaded:
# Load packages
library(dplyr)
library(decentlabr)
# Get all device-sensor time series for a domain/user
get_decentlab_last_values(
domain = "demo.decentlab.com",
key = "eyJrIjoiclhMRFFvUXFzQXpKVkZydm52b0VMRVg3M3U2b3VqQUciLCJuIjoiZGF0YS1xdWVyeS1hcGktZGVtby0yIiwiaWQiOjF9"
)
#> # A tibble: 105 × 8
#> date device sensor unit value channel locat…¹ uqk
#> <dttm> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
#> 1 2021-12-12 09:22:42 1404 battery V 1.86e0 <NA> <NA> 1404…
#> 2 2018-02-22 16:40:53 1404 battery V 3.02e0 <NA> dlr13-… 1404…
#> 3 2021-12-12 09:22:42 1404 bosch-bmp280-p… Pa 9.90e4 <NA> <NA> 1404…
#> 4 2018-02-22 16:40:53 1404 bosch-bmp280-p… Pa 9.63e4 <NA> dlr13-… 1404…
#> 5 2021-12-12 09:22:42 1404 bosch-bmp280-t… °C 1.96e1 <NA> <NA> 1404…
#> 6 2018-02-22 16:40:53 1404 bosch-bmp280-t… °C 2.22e1 <NA> dlr13-… 1404…
#> 7 2021-12-12 09:22:42 1404 senseair-lp8-c… ppm 1.38e3 <NA> <NA> 1404…
#> 8 2018-02-22 16:40:53 1404 senseair-lp8-c… ppm 1.42e3 <NA> dlr13-… 1404…
#> 9 2021-12-12 09:22:42 1404 senseair-lp8-c… ppm 1.38e3 <NA> <NA> 1404…
#> 10 2018-02-22 16:40:53 1404 senseair-lp8-c… ppm 1.43e3 <NA> dlr13-… 1404…
#> # … with 95 more rows, and abbreviated variable name ¹location
#> # ℹ Use `print(n = ...)` to see more rowsTo get the observations for a time series, the device must be known. Say a user was interested in CO2 concentrations, a low-cost sensor with the device number of 1404 can be accessed with the demo credentials like so:
# Get time series for a particular device
get_decentlab_last_values(
domain = "demo.decentlab.com",
key = "eyJrIjoiclhMRFFvUXFzQXpKVkZydm52b0VMRVg3M3U2b3VqQUciLCJuIjoiZGF0YS1xdWVyeS1hcGktZGVtby0yIiwiaWQiOjF9"
) %>%
filter(device == "1404") %>%
select(date,
device,
sensor,
uqk)
#> # A tibble: 26 × 4
#> date device sensor uqk
#> <dttm> <chr> <chr> <chr>
#> 1 2021-12-12 09:22:42 1404 battery 1404.battery
#> 2 2018-02-22 16:40:53 1404 battery 1404.battery
#> 3 2021-12-12 09:22:42 1404 bosch-bmp280-pressure 1404.bosch-bmp280-press…
#> 4 2018-02-22 16:40:53 1404 bosch-bmp280-pressure 1404.bosch-bmp280-press…
#> 5 2021-12-12 09:22:42 1404 bosch-bmp280-temperature 1404.bosch-bmp280-tempe…
#> 6 2018-02-22 16:40:53 1404 bosch-bmp280-temperature 1404.bosch-bmp280-tempe…
#> 7 2021-12-12 09:22:42 1404 senseair-lp8-co2 1404.senseair-lp8-co2
#> 8 2018-02-22 16:40:53 1404 senseair-lp8-co2 1404.senseair-lp8-co2
#> 9 2021-12-12 09:22:42 1404 senseair-lp8-co2-filtered 1404.senseair-lp8-co2-f…
#> 10 2018-02-22 16:40:53 1404 senseair-lp8-co2-filtered 1404.senseair-lp8-co2-f…
#> # … with 16 more rows
#> # ℹ Use `print(n = ...)` to see more rowsAfter the device is known, this is simply passed to the get_decentlab_time_series function that will get/import/fetch the data that is available for the device. To get data for the device for the first day of 2021, get_decentlab_time_series is used like this:
# Get the time series for a device for a short time period
get_decentlab_time_series(
domain = "demo.decentlab.com",
key = "eyJrIjoiclhMRFFvUXFzQXpKVkZydm52b0VMRVg3M3U2b3VqQUciLCJuIjoiZGF0YS1xdWVyeS1hcGktZGVtby0yIiwiaWQiOjF9",
device = "1404",
start = "2021-01-01",
end = "2021-01-02"
)
#> # A tibble: 1,352 × 5
#> date date_unix device sensor value
#> <dttm> <dbl> <int> <chr> <dbl>
#> 1 2021-01-01 00:09:28 1609459769. 1404 battery 2.54
#> 2 2021-01-01 00:19:31 1609460371. 1404 battery 2.54
#> 3 2021-01-01 00:29:31 1609460971. 1404 battery 2.54
#> 4 2021-01-01 00:39:26 1609461566. 1404 battery 2.54
#> 5 2021-01-01 00:49:29 1609462169. 1404 battery 2.54
#> 6 2021-01-01 01:09:29 1609463370. 1404 battery 2.54
#> 7 2021-01-01 01:19:29 1609463970. 1404 battery 2.54
#> 8 2021-01-01 01:29:28 1609464569. 1404 battery 2.54
#> 9 2021-01-01 01:39:31 1609465171. 1404 battery 2.54
#> 10 2021-01-01 01:49:31 1609465771. 1404 battery 2.54
#> # … with 1,342 more rows
#> # ℹ Use `print(n = ...)` to see more rowsCurrently, all sensors' data will be returned for each device when using get_decentlab_time_series, but this will likely change in the future. By default, the observations are provided in "long" format, but to reshape these data to wide format, use the as_wide argument:
get_decentlab_time_series(
domain = "demo.decentlab.com",
key = "eyJrIjoiclhMRFFvUXFzQXpKVkZydm52b0VMRVg3M3U2b3VqQUciLCJuIjoiZGF0YS1xdWVyeS1hcGktZGVtby0yIiwiaWQiOjF9",
device = "1404",
start = "2021-01-01",
end = "2021-01-02",
as_wide = TRUE
)
#> # A tibble: 104 × 16
#> date date_unix device battery bosch…¹ bosch…² sense…³ sense…⁴
#> <dttm> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2021-01-01 00:09:28 1.61e9 1404 2.54 95518 22.3 532 537
#> 2 2021-01-01 00:19:31 1.61e9 1404 2.54 95520 22.3 531 537
#> 3 2021-01-01 00:29:31 1.61e9 1404 2.54 95530 22.3 530 535
#> 4 2021-01-01 00:39:26 1.61e9 1404 2.54 95540 22.3 534 535
#> 5 2021-01-01 00:49:29 1.61e9 1404 2.54 95544 22.3 533 534
#> 6 2021-01-01 01:09:29 1.61e9 1404 2.54 95548 22.2 542 537
#> 7 2021-01-01 01:19:29 1.61e9 1404 2.54 95554 22.2 576 560
#> 8 2021-01-01 01:29:28 1.61e9 1404 2.54 95568 22.2 569 577
#> 9 2021-01-01 01:39:31 1.61e9 1404 2.54 95570 22.2 550 555
#> 10 2021-01-01 01:49:31 1.61e9 1404 2.54 95578 22.2 539 542
#> # … with 94 more rows, 8 more variables: senseair_lp8_ir <dbl>,
#> # senseair_lp8_ir_filtered <dbl>, senseair_lp8_status <dbl>,
#> # senseair_lp8_temperature <dbl>, senseair_lp8_vcap1 <dbl>,
#> # senseair_lp8_vcap2 <dbl>, sensirion_sht21_humidity <dbl>,
#> # sensirion_sht21_temperature <dbl>, and abbreviated variable names
#> # ¹bosch_bmp280_pressure, ²bosch_bmp280_temperature, ³senseair_lp8_co2,
#> # ⁴senseair_lp8_co2_filtered
#> # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable namesThese data can now be used for analysis.