Finding variables that occur only in one row in R can be done through various steps, depending on whether you mean “variables” (columns) or “values” (specific entries in the columns). Below, I’ll outline both interpretations and provide a corresponding R code for each.

Finding Columns with Unique Values in One Row

In R, you can identify variables (columns) that have unique values in a single row using a combination of functions such as apply, colSums, and logical indexing.

1. Create a Sample Data Frame: Let’s start with a sample data frame for demonstration purposes.
2. Identify Unique Values in Each Column: For each column, check if there is only one occurrence of any value.
3. Identify rows with these unique values: Filter out the columns based on the condition that only one row has a unique value.

Now we will discuss step by step to Find variables that occur only in ONE row in R Programming Language.

Step 1: Create a Sample Data Frame

First we will create a sample dataset.

# Create a sample dataset
data <- data.frame(
  A = c(1, 2, 3, 4, 1),
  B = c("x", "y", "x", "z", "w"),
  C = c(10, 20, 10, 30, 40)
)
data

Output:

  A B  C
1 1 x 10
2 2 y 20
3 3 x 10
4 4 z 30
5 1 w 40

Step 2: Identify Unique Values in Each Column

Now we will Identify Unique Values in Each Column.

# Count the occurrences of each unique value for each column
unique_counts <- lapply(data, function(column) {
  value_counts <- table(column)
  return(value_counts)
})

# Find columns with values that occur only once
columns_with_unique_values <- lapply(unique_counts, function(counts) {
  unique_values <- names(counts[counts == 1])
  return(unique_values)
})

# Print the columns with their unique values
print(columns_with_unique_values)

Output:

$A
[1] "2" "3" "4"

$B
[1] "w" "y" "z"

$C
[1] "20" "30" "40"

Step 3: Identify rows with these unique values

Now we will Identify rows with these unique values.

# Identify rows with these unique values
find_unique_rows <- function(data, unique_values) {
  unique_rows <- lapply(names(unique_values), function(col) {
    unique_vals <- unique_values[[col]]
    if (length(unique_vals) > 0) {
      row_indices <- which(data[[col]] %in% unique_vals)
      return(row_indices)
    } else {
      return(NULL)
    }
  })
  return(unique_rows)
}

# Get row indices with unique values
unique_rows <- find_unique_rows(data, columns_with_unique_values)
unique_rows

Output:

[[1]]
[1] 2 3 4

[[2]]
[1] 2 4 5

[[3]]
[1] 2 4 5

The columns_with_unique_values will give you a list of columns and the values that occur only once in those columns. The unique_rows will provide the row indices where these unique values are located.

In this example, column A has unique values 2, 3, and 4 which occur only in rows 2, 3, and 4, respectively. Column B has unique values y, z, and w in rows 2, 4, and 5, respectively. Similarly, column C has unique values 20, 30, and 40 in rows 2, 4, and 5.

Conclusion

In summary, the approach to finding variables that occur only in one row can be interpreted in different ways. If you are interested in values within columns that only appear once, you can use the table function and filter those values. If you want to find columns where all values are unique across rows, you can compare the number of unique values to the number of rows.