如何基于查找表多次执行R函数以修正时间戳

First, ensure your break records are sorted by their occurrence date—this is critical to apply adjustments in the correct chronological order:

# Sort df2 by break date
df2_sorted <- df2[order(df2$date), ]

Method 1: For Loop (Straightforward) #

Use a loop to sequentially apply your break_function to each row of the sorted break records, updating the dataframe incrementally:

# Initialize with original df1
updated_df1 <- df1

# Iterate over each row in sorted df2
for (row_idx in seq_len(nrow(df2_sorted))) {
  updated_df1 <- break_function(updated_df1, df2_sorted, row_idx)
}

Method 2: Functional Approach with Reduce #

For a more concise, functional-style solution, use Reduce to cumulatively apply the function across all break records:

# Apply break_function cumulatively using Reduce
updated_df1 <- Reduce(
  function(current_df, row_idx) break_function(current_df, df2_sorted, row_idx),
  seq_len(nrow(df2_sorted)),
  init = df1
)

Verification #

To confirm the adjustments work, compare original and updated timestamps. For example:

# Original timestamp sample
head(df1)
# Updated timestamp sample
head(updated_df1)

Both methods will correctly add the sum of all applicable break durations to each timestamp that occurs after the corresponding break times.

内容的提问来源于stack exchange，提问作者Baddevs