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Tidy and Process Temperature and Relative Humidity data

Source: R/tidy_TRHdata.R
tidy_TRHdata.Rd

This function tidies and processes temperature, relative humidity, and date data from a given dataset. Dataset should minimally have "Date", "Temp" and "RH" columns.

It filters out rows with missing dates, attempts to parse dates, converts temperature and humidity to numeric types, and groups the data by Site, Sensor, and Date based on the averaging interval.

If the site or sensor columns are not present in the data, the function defaults to adding columns named "Site" and "Sensor". This can be changed in the arguments.

When an averaging option of "hour", "day", "month" is selected, it uses dplyr and lubridate functions to floor datetimes and calculate averages, the default is median average. See lubridate::floor_date() for rounding intervals.

  • Filters out rows with missing dates.

  • Renames columns for consistency.

  • Converts temperature and relative humidity to numeric.

  • Adds default columns "Site" and "Sensor" when missing or not supplied in args.

  • Rounds dates down to the nearest hour, day, or month as per avg_time.

  • Calculates averages for temperature and relative humidity according to avg_statistic.

  • Filters out implausible temperature and humidity values (outside -50-80°C and 0-100%RH).

Usage

tidy_TRHdata(
  mydata,
  Site = "Site",
  Sensor = "Sensor",
  Date = "Date",
  Temp = "Temp",
  RH = "RH",
  avg_time = "none",
  avg_statistic = "median",
  avg_groups = c("Site", "Sensor"),
  ...
)

Arguments

mydata

A data frame containing TRH data. Ideally, this should have columns for "Site", "Sensor", "Date", "Temp" (temperature), and "RH" (relative humidity). The function requires at least the date, temperature, and relative humidity columns to be present. Site and sensor columns are optional; if missing, the function will add default columns named "Site" and "Sensor" respectively with values below.

Site

A string specifying the name of the column in mydata that contains location information. If missing, defaults to "Site".

Sensor

A string specifying the name of the column in mydata that contains sensor information. If missing, defaults to "Sensor".

Date

A string specifying the name of the column in mydata that contains date information. Default is "Date". The column should ideally contain ISO 8601 date-time formatted strings (e.g. "2025-01-01 00:00:00"), but the function will try to parse a variety of common datetime formats.

Temp

A string specifying the name of the column in mydata that contains temperature data. Default is "Temp".

RH

A string specifying the name of the column in mydata that contains relative humidity data. Default is "RH".

avg_time

Character string specifying the averaging interval. One of "none" (no averaging), "hour", "day", or "month", etc. See lubridate::floor_date() for rounding intervals.

avg_statistic

Statistic for averaging; default is "median".

avg_groups

Character vector specifying grouping columns for time-averaging. These are then returned as factors. Default is c("Site", "Sensor").

...

Additional arguments (currently unused).

Value

A tidy data frame with processed TRH data. When averaging, date times are floored, temperature and humidity are averaged, groups are factored, and implausible values filtered.

Examples


# mydata file
filepath <- data_file_path("mydata.xlsx")
mydata <- readxl::read_excel(filepath, sheet = "mydata", n_max = 10)

tidy_TRHdata(mydata)
#> # A tibble: 10 × 5
#>    Site   Sensor Date                 Temp    RH
#>    <chr>  <chr>  <dttm>              <dbl> <dbl>
#>  1 London Room 1 2024-01-01 00:00:00  21.8  36.8
#>  2 London Room 1 2024-01-01 00:15:00  21.8  36.7
#>  3 London Room 1 2024-01-01 00:29:59  21.8  36.6
#>  4 London Room 1 2024-01-01 00:44:59  21.7  36.6
#>  5 London Room 1 2024-01-01 00:59:59  21.7  36.5
#>  6 London Room 1 2024-01-01 01:14:59  21.7  36.2
#>  7 London Room 1 2024-01-01 01:29:59  21.7  36.3
#>  8 London Room 1 2024-01-01 01:44:59  21.7  36.4
#>  9 London Room 1 2024-01-01 01:59:59  21.7  36  
#> 10 London Room 1 2024-01-01 02:14:59  21.6  36  

tidy_TRHdata(mydata, avg_time = "hour")
#> # A tibble: 3 × 5
#>   Date                Site   Sensor  Temp    RH
#>   <dttm>              <chr>  <chr>  <dbl> <dbl>
#> 1 2024-01-01 00:00:00 London Room 1  21.8  36.6
#> 2 2024-01-01 01:00:00 London Room 1  21.7  36.2
#> 3 2024-01-01 02:00:00 London Room 1  21.6  36  

mydata |> add_humidity_calcs() |> tidy_TRHdata(avg_time = "hour")
#> # A tibble: 3 × 13
#>   Date                Site   Sensor  Temp    RH   Pws    Pw    DP    AH    AD
#>   <dttm>              <chr>  <chr>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2024-01-01 00:00:00 London Room 1  21.8  36.6  26.1  9.56  6.30  7.01  1.19
#> 2 2024-01-01 01:00:00 London Room 1  21.7  36.2  26.0  9.41  6.08  6.91  1.19
#> 3 2024-01-01 02:00:00 London Room 1  21.6  36    25.8  9.29  5.89  6.82  1.19
#> # ℹ 3 more variables: MR <dbl>, SH <dbl>, Enthalpy <dbl>

# \donttest{
# Example usage: TRH_data <- tidy_TRHdata("path/to/your/TRHdata.csv")
# }