Find Coordinates of Specific Values in a data.frame

This function locates the row and column coordinates of values in a data.frame that satisfy a given condition. It's particularly useful for identifying the positions of specific or problematic values in large datasets.

Usage

valueCoordinates(df, value = NA, eq_fun = value_check)

Arguments

df: A data.frame to be searched.
value: The value to search for. Default is NA.
eq_fun: A function used to check equality. It should take two arguments: the current value in the data.frame and the `value` parameter. Default is the internal `eq_fun` function that uses `identical()` for non-NA values and `is.na()` for NA.

Value

A data.frame with two columns:

column: The column numbers where the specified condition was met
row: The row numbers where the specified condition was met

The returned data.frame is sorted first by column, then by row.

Details

The function performs the following steps: 1. Creates a logical matrix where TRUE indicates values meeting the specified condition. 2. Finds the row and column indices of TRUE values. 3. Combines these indices into a data.frame. 4. Sorts the results by column, then by row.

If no custom equality function is provided, the function uses the internal `eq_fun` which checks for NA values with `is.na()` and uses `identical()` for all other values.

Examples

# Create a sample data.frame
df <- data.frame(
  a = c(1, NA, 3),
  b = c(NA, 2, NA),
  c = c(3, 2, 1)
)

# Find coordinates of NA values
valueCoordinates(df)
#>   column row
#> 2      1   1
#> 1      2   2
#> 3      2   3

# Find coordinates of the value 2
valueCoordinates(df, 2)
#>   column row
#> 1      2   2
#> 2      3   2

# Find coordinates of values greater than 2
valueCoordinates(df, 2, function(x, y) x > y)
#>   column row
#> 2      1   1
#> 1      3   3

# Find coordinates of values within a range
valueCoordinates(df, c(1, 3), function(x, y) x >= y[1] & x <= y[2])
#>   column row
#> 1      1   1
#> 5      1   2
#> 3      2   2
#> 4      3   1
#> 2      3   3
#> 6      3   3