RStudio中汇总gapminder数据GDP最值后缺失对应年份的解决方法

Hey there, great question! When you use summarize() with min() and max(), you're only aggregating the gdpPercap values, which is why the corresponding year gets lost. Here are a few clean, dplyr-native ways to get both the min/max gdpPercap AND their associated years for each country:

Method 1: Use slice_min() and slice_max() (Most Intuitive) #

This approach pulls the full rows containing the min and max values, then combines them into a single result:

library(dplyr)

# Load your data (adjust path if needed)
gapminder <- read.csv("gapminder_data.csv")

# Get rows with minimum gdpPercap per country
min_gdp_data <- gapminder %>%
  group_by(country) %>%
  slice_min(gdpPercap, n = 1) %>%  # n=1 keeps only one row (adjust if ties exist)
  select(country, year, gdpPercap) %>%
  rename(min_year = year, min_gdpPercap = gdpPercap)

# Get rows with maximum gdpPercap per country
max_gdp_data <- gapminder %>%
  group_by(country) %>%
  slice_max(gdpPercap, n = 1) %>%
  select(country, year, gdpPercap) %>%
  rename(max_year = year, max_gdpPercap = gdpPercap)

# Combine results into one dataframe
final_result <- min_gdp_data %>%
  inner_join(max_gdp_data, by = "country")

# View the output
head(final_result)

Note: If a country has multiple years with the same min/max gdpPercap, change n = 1 to n = Inf to keep all tied rows, then adjust the join or pivot as needed.

Method 2: Single Pipeline with filter() + pivot_wider() #

This keeps everything in one chain by filtering for min/max values first, then reshaping the data:

gapminder %>%
  group_by(country) %>%
  filter(gdpPercap == min(gdpPercap) | gdpPercap == max(gdpPercap)) %>%
  mutate(value_type = ifelse(gdpPercap == min(gdpPercap), "min", "max")) %>%
  pivot_wider(
    names_from = value_type,
    values_from = c(year, gdpPercap),
    names_sep = "_"
  ) %>%
  ungroup()

This will give you a single row per country with columns like year_min, gdpPercap_min, year_max, gdpPercap_max.

Method 3: Direct summarize() with Indexing #

If you prefer to stick close to your original code structure, you can use which.min() and which.max() to pull the corresponding year directly in summarize():

gapminder %>%
  group_by(country) %>%
  summarize(
    min_gdpPercap = min(gdpPercap),
    min_year = year[which.min(gdpPercap)],
    max_gdpPercap = max(gdpPercap),
    max_year = year[which.max(gdpPercap)]
  ) %>%
  ungroup()

Tip: If you need to handle ties (multiple years with the same min/max), replace year[which.min(gdpPercap)] with paste(year[gdpPercap == min(gdpPercap)], collapse = ", ") to list all relevant years as a single string.

内容的提问来源于stack exchange，提问作者Maerkli