如何自动循环调用case_importer函数遍历澳高院年度判例

Great question—let's streamline your process so you never have to manually adjust loop counts again, while also cleaning up how you store your data (goodbye scattered global lists!).

First: Fix the cases_in_year Function for Reliability #

Your current version uses a hardcoded index (year - 1947) which will break if your Excel file ever has non-consecutive years. Let's make it more robust with dplyr:

cases_in_year <- function(year) {
  hc_cases_per_year %>%
    filter(year == .env$year) %>%
    pull(num_cases) %>%
    as.integer()
}

Option 1: Base R Approach (No Extra Packages Needed) #

Instead of creating individual global lists for each year, use a single named list to store all your data. This keeps your environment tidy and makes it easier to iterate over:

# Initialize a single named list to hold all year-specific case data
all_hc_cases <- list()

# Loop through every year in your Excel dataset
for (year in hc_cases_per_year$year) {
  # Get the number of cases for the current year
  total_cases <- cases_in_year(year)
  
  # Use lapply to import all cases for this year
  all_hc_cases[[as.character(year)]] <- lapply(1:total_cases, function(case_num) {
    case_importer(year, case_num)
  })
}

Option 2: Tidyverse/Purrr Approach (More Concise) #

If you prefer the tidyverse style, purrr::map2 lets you pair years with their case counts and import everything in a single pipeline:

library(purrr)
library(tibble)

# Create a named list of case data, where names are years
all_hc_cases <- hc_cases_per_year %>%
  mutate(
    # Import all cases for each year using map2 to pair year + case count
    case_data = map2(year, num_cases, ~lapply(1:.y, case_importer, year = .x))
  ) %>%
  select(year, case_data) %>%
  deframe() # Convert to a named list (year names -> case data lists)

Convert Lists to Dataframes (Automated) #

To turn each year's case list into a dataframe (using your list_to_df function), just add one more step:

# Base R version
all_hc_cases_dfs <- lapply(all_hc_cases, list_to_df)

# Tidyverse version
all_hc_cases_dfs <- map(all_hc_cases, list_to_df)

Why This Works Better #

• No manual loop adjustments: The code automatically pulls case counts from your Excel file, so you never have to update numbers manually.
• Cleaner environment: Instead of 70+ global lists (1948-2020), you have one or two centralized lists to manage.
• Robustness: The updated cases_in_year function works even if your Excel file has missing years or is out of order.

内容的提问来源于stack exchange，提问作者Jordan Rothwell