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Summarize and check for abnormal feed & water intake

Source: R/feed_water_summary.R
feed_water_summary.Rd

This function summarizes daily feed and water intake, visit duration, and counts, and updates intake warnings (if input warning dataframe warn is not NULL). If you don't want to update warnings, set warn = NULL, and only the summary will be returned.

Usage

feed_water_summary(
  feed = NULL,
  water = NULL,
  warn = NULL,
  cfg = qc_config(),
  id_col = id_col2(),
  intake_col = intake_col2(),
  dur_col = duration_col2()
)

Arguments

feed

Either a data frame containing all feed visits across days, or a list of data frames grouped by date. If providing a list, each data frame must have a 'date' column.

water

Either a data frame containing all water visits across days, or a list of data frames grouped by date. If providing a list, each data frame must have a 'date' column.

warn

Warning data frame to update

cfg

A configuration list created by qc_config().

id_col

Animal ID column name (default current global value from id_col2())

intake_col

Intake column name (default current global value from intake_col2())

dur_col

Duration column name (default current global value from duration_col2())

Value

A list of:

  • summary: merged data frame of daily intake, duration, and visit counts

  • warn: updated warnings

Examples

# Example with single data frames
feed_df <- tibble::tibble(
  date = as.Date(c("2024-01-01", "2024-01-01")),
  cow = c("A", "B"),
  intake = c(20, 80),
  duration = c(200, 300)
)

water_df <- tibble::tibble(
  date = as.Date(c("2024-01-01", "2024-01-01")),
  cow = c("A", "B"),
  intake = c(50, 200),
  duration = c(100, 150)
)

# Example with lists of data frames
feed_list <- list(
  "2024-01-01" = tibble::tibble(
    date = as.Date("2024-01-01"),
    cow = c("A", "B"),
    intake = c(20, 80),
    duration = c(200, 300)
  ),
  "2024-01-02" = tibble::tibble(
    date = as.Date("2024-01-02"),
    cow = c("A", "C"),
    intake = c(25, 85),
    duration = c(210, 310)
  )
)

water_list <- list(
  "2024-01-01" = tibble::tibble(
    date = as.Date("2024-01-01"),
    cow = c("A", "B"),
    intake = c(50, 200),
    duration = c(100, 150)
  ),
  "2024-01-02" = tibble::tibble(
    date = as.Date("2024-01-02"),
    cow = c("A", "C"),
    intake = c(55, 210),
    duration = c(110, 160)
  )
)

warn <- tibble::tibble(
  date = as.Date(c("2024-01-01", "2024-01-02")),
  low_daily_feed_intake_cows = NA_character_,
  high_daily_feed_intake_cows = NA_character_,
  low_daily_water_intake_cows = NA_character_,
  high_daily_water_intake_cows = NA_character_
)

cfg <- qc_config()

# Using single data frames
feed_water_summary(feed_df, 
                  water_df, 
                  warn, 
                  cfg, 
                  id_col = "cow", 
                  intake_col = "intake", 
                  dur_col = "duration")
#> $summary
#> # A tibble: 2 × 8
#>   date       cow   feed_intake feed_duration feed_visits water_intake
#>   <date>     <chr>       <dbl>         <dbl>       <int>        <dbl>
#> 1 2024-01-01 A              20           200           1           50
#> 2 2024-01-01 B              80           300           1          200
#> # ℹ 2 more variables: water_duration <dbl>, water_visits <int>
#> 
#> $warn
#> # A tibble: 2 × 5
#>   date       low_daily_feed_intake_cows high_daily_feed_intake_cows
#>   <date>     <chr>                      <chr>                      
#> 1 2024-01-01 A, 20                      B, 80                      
#> 2 2024-01-02 NA                         NA                         
#> # ℹ 2 more variables: low_daily_water_intake_cows <chr>,
#> #   high_daily_water_intake_cows <chr>
#> 
                  
# Using lists of data frames
feed_water_summary(feed_list, 
                  water_list, 
                  warn, 
                  cfg, 
                  id_col = "cow", 
                  intake_col = "intake", 
                  dur_col = "duration")
#> $summary
#> # A tibble: 4 × 8
#>   date       cow   feed_intake feed_duration feed_visits water_intake
#>   <date>     <chr>       <dbl>         <dbl>       <int>        <dbl>
#> 1 2024-01-01 A              20           200           1           50
#> 2 2024-01-01 B              80           300           1          200
#> 3 2024-01-02 A              25           210           1           55
#> 4 2024-01-02 C              85           310           1          210
#> # ℹ 2 more variables: water_duration <dbl>, water_visits <int>
#> 
#> $warn
#> # A tibble: 2 × 5
#>   date       low_daily_feed_intake_cows high_daily_feed_intake_cows
#>   <date>     <chr>                      <chr>                      
#> 1 2024-01-01 A, 20                      B, 80                      
#> 2 2024-01-02 A, 25                      C, 85                      
#> # ℹ 2 more variables: low_daily_water_intake_cows <chr>,
#> #   high_daily_water_intake_cows <chr>
#>