R语言新手求助：如何生成含各列最大值对应Food的vector

Hey there! Let's break this down into simple, actionable steps. First, let's make sure we have your data loaded into an R data frame correctly:

# Create the data frame
food_df <- data.frame(
  Food = c("Apple", "Apricot", "Avocado", "Blueberry", "Blackberry"),
  energy = c(207, 153, 523, 204, 170),
  water = c(84, 87, 81, 80, 85),
  fiber = c(2.3, 2.1, 0.2, 8.4, 8.7),
  stringsAsFactors = FALSE
)

Now, here are two solid approaches to get your desired Food vector—one using base R (great for learning core concepts) and another using the tidyverse (cleaner for data manipulation tasks).

Base R Approach #

We can use sapply() to iterate over the columns we care about, find the row index where the maximum value occurs, then pull the corresponding Food name:

# Define the columns we want to check
target_cols <- c("energy", "water", "fiber")

# Extract Food names for each column's maximum
max_foods <- sapply(target_cols, function(col) {
  food_df$Food[which.max(food_df[[col]])]
})

# Convert to a plain vector (optional, since sapply returns a named vector)
max_foods_vector <- unname(max_foods)

# View the result
max_foods_vector
# Output: "Avocado" "Apricot" "Blackberry"

How this works: #

• which.max() finds the first occurrence of the maximum value in a column (perfect here since all maxima are unique).
• sapply() applies our function to each column in target_cols, returning a named vector. We use unname() if we want an unnamed vector.

Tidyverse Approach #

If you're open to using the dplyr and tidyr packages (super popular for data wrangling), this method is more readable for complex tasks:

First, install and load the packages if you haven't already:

install.packages("tidyverse")
library(tidyverse)

Then:

max_foods_tidy <- food_df %>%
  # Convert wide data to long format (easier to group by nutrient)
  pivot_longer(cols = -Food, names_to = "nutrient", values_to = "value") %>%
  # Group by each nutrient
  group_by(nutrient) %>%
  # Keep only the row with the maximum value for each nutrient
  filter(value == max(value)) %>%
  # Extract just the Food names as a vector
  pull(Food)

# View the result
max_foods_tidy
# Output: "Avocado" "Apricot" "Blackberry"

How this works: #

• pivot_longer() reshapes the data so each row is a Food-nutrient-value combination.
• group_by(nutrient) lets us handle each nutrient separately.
• filter(value == max(value)) keeps only the row where the value is the maximum for that nutrient.
• pull(Food) extracts the Food column into a vector.

Both methods will give you exactly the vector you need. For a beginner, starting with the base R approach can help you build a strong foundation, while the tidyverse approach is great to learn as you tackle more complex data tasks!

内容的提问来源于stack exchange，提问作者Rajendra Warke