如何在纯dplyr/tidyverse环境中计算各洲人口相对于1952年的增长率？

Absolutely, you can do this entirely within the tidyverse/dplyr ecosystem! Here are two clean approaches to get population growth rates relative to 1952:

Approach 1: Calculate growth rates in long format first #

This method computes relative growth while your data is still in long format (flexible for further analysis), then spreads to wide format:

library(tidyverse)

gapminder <- readr::read_csv("https://raw.githubusercontent.com/OHI-Science/data-science-training/master/data/gapminder.csv")

gapminder %>% 
  # Get total population per continent and year
  group_by(continent, year) %>% 
  summarize(cont_pop = sum(pop), .groups = "drop") %>%
  # For each continent, grab the 1952 population as our reference
  group_by(continent) %>%
  mutate(
    ref_pop_1952 = cont_pop[year == 1952],
    # Calculate growth rate: (current year pop / 1952 pop) - 1 (decimal)
    growth_rate_rel_1952 = (cont_pop / ref_pop_1952) - 1,
    # Optional: Convert to percentage instead of decimal
    # growth_rate_pct = ((cont_pop / ref_pop_1952) - 1) * 100
  ) %>%
  ungroup() %>%
  # Keep only columns needed for wide format
  select(continent, year, growth_rate_rel_1952) %>%
  # Spread to wide format with years as columns
  spread(year, value = growth_rate_rel_1952)

Approach 2: Spread first, then compute growth rates #

If you prefer to work with wide format immediately, spread the absolute population values first, then use across() to apply the growth calculation to all year columns:

gapminder %>% 
  group_by(continent, year) %>% 
  summarize(cont_pop = sum(pop), .groups = "drop") %>%
  # Spread to wide format with absolute populations
  spread(year, value = cont_pop) %>%
  # Calculate growth rate relative to 1952 for all year columns
  mutate(
    across(-continent, ~ (. / `1952`) - 1),
    # Optional: For percentage instead of decimal
    # across(-continent, ~ ((. / `1952`) - 1) * 100)
  )

Key Notes: #

• Both methods return growth rates relative to 1952 (e.g., a value of 0.5 equals 50% growth since 1952).
• Use the optional percentage line if you want results formatted as percentages rather than decimals.
• The across() function in Approach 2 avoids manually listing every year column, making the code concise and scalable.

内容的提问来源于stack exchange，提问作者ECII