This function tidies Hanwell Environmental Monitoring System (EMS) data from either Excel sheets or CSV files.
- Default mode (MinMax = FALSE): Reads raw date, temperature, and humidity data. - Min-Max mode (MinMax = TRUE): Under development to read min-max average data (CSV only).
Arguments
- EMS_datapath
Character string specifying the file path to the Hanwell EMS data file.
- Site
Character string specifying site name to add as a column. Default is "Site".
- MinMax
Logical flag; if TRUE, reads Min-Max format, otherwise reads raw data. Default is FALSE.
- sheet
Optional, Excel sheet name for reading Excel files. The default is "Hanwell"
- ...
Additional arguments passed to
readxl::read_excel
for Excel reading.
Value
A tibble containing tidied Hanwell EMS data, with columns including:
- Site
Character, site name as specified by
Site
argument.- Sensor
Character, sensor identifier extracted from the file or metadata.
- Date
POSIXct datetime of the measurement.
- Temp
Numeric temperature measurement in °C (average for MinMax).
- RH
Numeric relative humidity measurement in % (average for MinMax).
- TempMin, TempMax, RHMin, RHMax
(Only for MinMax reports) Numeric min/max values of Temp and RH.
Examples
# \donttest{
# Example usage: hanwell_data <- tidy_Hanwell("path/to/your/hanwell_data.csv")
# }
# mydata file
filepath <- data_file_path("mydata.xlsx")
tidy_Hanwell(filepath, sheet = "Hanwell", Site = "London") |> head()
#> Warning: Expecting logical in D7090 / R7090C4: got 'Maximum'
#> Warning: Expecting logical in E7090 / R7090C5: got 'Standard Deviation'
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
#> • `` -> `...3`
#> • `` -> `...4`
#> • `` -> `...5`
#> # A tibble: 6 × 5
#> Site Sensor Date Temp RH
#> <chr> <chr> <dttm> <dbl> <dbl>
#> 1 London External 2025-08-12 00:06:03 22.8 60.2
#> 2 London External 2025-08-12 00:11:00 22.6 60.2
#> 3 London External 2025-08-12 00:16:04 22.6 61.6
#> 4 London External 2025-08-12 00:21:05 22.6 62.4
#> 5 London External 2025-08-12 00:26:03 22.6 62.8
#> 6 London External 2025-08-12 00:31:07 22.4 63.5