PurpleAir

Lifecycle: stable CRAN status R-CMD-check

The goal of PurpleAir is to provide read access to the PurpleAir API to retrieve real-time and historical data from PurpleAir sensors.

Please note that usage of this package must abide by the requirements of the PurpleAir API. From their website:

PurpleAir was founded on principles of openness, sharing, and community. It is to strengthen these principles and ensure the success of our entire community that we put together updated terms of service, data license, and data attribution requirements when using PurpleAir data and this API. Please take a moment to review them and note the attribution guide and data license agreement. If you have any questions or need more information, we have an excellent resource at https://community.purpleair.com/c/data/api/18.

Installation

Install PurpleAir from CRAN with:

install.packages("PurpleAir")

Install the latest development version of PurpleAir from GitHub with:

pak::pak("cole-brokamp/PurpleAir")

Usage

library(PurpleAir)

Querying data from the PurpleAir API requires a free PurpleAir Developer API key linked to a Google account. Functions in the package each take a purple_air_api_key argument or your key can be stored in an environment variable called PURPLE_AIR_API_KEY. To check your key, use:

check_api_key(Sys.getenv("PURPLE_AIR_API_KEY"))
#> ✔ Using valid 'READ' key with version V1.0.14-0.0.57 of the PurpleAir API on 1720399876

Get the latest data from a single PurpleAir sensor, defined by its sensor key:

get_sensor_data(sensor_index = 175413,
                fields = c("name", "last_seen", "pm2.5_cf_1", "pm2.5_atm"))
#> $last_seen
#> [1] "2024-07-07 20:50:13 EDT"
#> 
#> $name
#> [1] "JN-Clifton,OH"
#> 
#> $pm2.5_atm
#> [1] 9.5
#> 
#> $pm2.5_cf_1
#> [1] 9.5

Get the latest data from many PurpleAir sensors, defined by their sensor keys,

get_sensors_data(x = as.integer(c(175257, 175413)),
                 fields = c("name", "last_seen", "pm2.5_cf_1", "pm2.5_atm"))
#> # A tibble: 2 × 5
#>   sensor_index last_seen           name          pm2.5_atm pm2.5_cf_1
#>          <int> <dttm>              <chr>             <dbl>      <dbl>
#> 1       175257 2024-07-07 20:50:30 Lillard             9.9        9.9
#> 2       175413 2024-07-07 20:50:13 JN-Clifton,OH       9.5        9.5

a geographic bounding box,

sf::st_bbox(
  c(
    "xmin" = -84.82030,
    "ymin" = 39.02153,
    "xmax" = -84.25633,
    "ymax" = 39.31206
  ),
  crs = 4326
) |>
  get_sensors_data(fields = c("name"))
#> # A tibble: 45 × 2
#>    sensor_index name              
#>           <int> <chr>             
#>  1        30303 아가페_실내       
#>  2        30561 lineblock_outside2
#>  3        30571 amlok_inside      
#>  4        36325 807d3a616167      
#>  5        36681 68c63a8e59a       
#>  6        42623 KMI_041           
#>  7        49191 BCDDC264D0B1      
#>  8        49193 ECFABCB88583      
#>  9        49199 ECFABC59A4F4      
#> 10        49213 807D3A615D1E      
#> # ℹ 35 more rows

or a date from which sensors must have been modified since.

get_sensors_data(as.POSIXct(Sys.time()) - 60, fields = "name")
#> # A tibble: 5,299 × 2
#>    sensor_index name                  
#>           <int> <chr>                 
#>  1          314 Parker                
#>  2          749 Agia                  
#>  3          928 Cobble Hill El        
#>  4          934 Glenmohr Drive        
#>  5          978 Hillerød f989         
#>  6         1006 Platani               
#>  7         1030 Trion Navarchon Old   
#>  8         1090 Nicola Street West    
#>  9         1128 USCEHC Lincoln Heights
#> 10         1248 UNBC-PA13             
#> # ℹ 5,289 more rows

Get historical data from a single PurpleAir sensor:

my_history <-
  get_sensor_history(
    sensor_index = 175413,
    fields = c("pm1.0_cf_1", "pm1.0_atm", "pm2.5_cf_1", "pm2.5_atm"),
    start_timestamp = as.POSIXct("2024-07-02"),
    end_timestamp = as.POSIXct("2024-07-05")
  )

my_history
#> # A tibble: 432 × 5
#>    time_stamp          pm1.0_cf_1 pm1.0_atm pm2.5_atm pm2.5_cf_1
#>    <dttm>                   <dbl>     <dbl>     <dbl>      <dbl>
#>  1 2024-07-03 23:40:00    2503.     1670.      1671.      2505. 
#>  2 2024-07-04 06:50:00    2504.     1670.      1671.      2505. 
#>  3 2024-07-03 22:10:00    2505.     1672.      1673.      2507. 
#>  4 2024-07-04 07:10:00    2503.     1670.      1671.      2504. 
#>  5 2024-07-04 09:40:00    2504.     1671.      1672.      2505. 
#>  6 2024-07-04 11:30:00    2504.     1671.      1673.      2506. 
#>  7 2024-07-04 03:40:00    2501.     1668.      1669.      2502. 
#>  8 2024-07-03 22:20:00    2504.     1671.      1673.      2506. 
#>  9 2024-07-04 03:00:00    2502.     1669.      1669.      2503. 
#> 10 2024-07-04 18:50:00       8.32      8.32      10.1       10.1
#> # ℹ 422 more rows

and plot it:

my_history |>
  tidyr::pivot_longer(cols = tidyr::starts_with("pm"), names_to = "pollutant", values_to = "concentration") |>
  ggplot2::ggplot(ggplot2::aes(time_stamp, concentration, color = pollutant)) +
  ggplot2::geom_line()

By default, the PurpleAir R package retries failed API requests related to an underlying HTTP error (e.g., network is down) or a transient API error (i.e., 429, 503). Before retrying each failed request, it waits about 2 seconds. Successive failed requests result in exponentially longer waiting times (httr2::req_retry()). Specify the maximum number of seconds to wait (by default 45) with the environment variable PURPLE_AIR_API_RETRY_MAX_TIME.