由于您希望按患者和药物进行计算，因此应该使用group_by，这样差异就不会错误地计算出不同组之间的差异。

library(dplyr) # 1.1.0 for .by=
df %>%
  mutate(date1 = as.POSIXct(date1)) %>% # may not be needed with your real data
  mutate(
    hours_output = as.numeric(c(diff(date1), 24), units="hours"),
    .by = c(pid, med)
  )
#   pid   med               date1 hours_output
# 1   1 drugA 2023-02-02 09:00:00      3 hours
# 2   1 drugA 2023-02-02 12:00:00      2 hours
# 3   1 drugA 2023-02-02 14:00:00     24 hours
# 4   1 drugB 2023-02-03 10:00:00      8 hours
# 5   1 drugB 2023-02-03 18:00:00     24 hours

我正在使用.by=，这是dplyr_1.1.0的新特性;如果您有更早版本，那么显式使用group_by：

df %>%
  mutate(date1 = as.POSIXct(date1)) %>%
  group_by(pid, med) %>%
  mutate(hours_output = as.numeric(c(diff(date1), 24), units="hours"))

我可以在Databricks中将其作为示例。
使用虚拟数据的工作示例

df <- df %>% arrange(datetime_col)

# Sample dataframe with datetime values
df <- data.frame(datetime_col = c("2023-02-02 09:00:00", "2023-02-02 12:00:00", "2023-02-02 14:00:00"))

# Convert datetime column to POSIXct object
df$datetime_col <- as.POSIXct(df$datetime_col, format = "%Y-%m-%d %H:%M:%S")
#df$datetime_col

# Calculate duration between consecutive datetime values, including last interval
durations <- c(diff(df$datetime_col, units = "hours"), 0)

# Convert durations to hours
durations <- as.numeric(durations, units = "hours")

# Replace last duration value with 24 hours
durations[length(durations)] <- 24

durations <- round(durations, 2)

df$duration <- durations

df_f <- df %>% select(datetime_col, duration)
df_f

下面的工作在虚拟数据（如在问题的顶部）时，在Databricks中使用。
提供所需的输出。
(Also，处理Databricks中的实际数据）

library(dplyr)
library(lubridate)

# Convert datetime column to POSIXct object
df$date1 <- ymd_hms(df$date1)

df <- df %>% arrange(date1)

# Calculate duration between consecutive datetime values, including last interval
durations <- c(diff(df$date1), 0)

# Convert durations to hours and round to 2 decimal places
durations <- round(as.numeric(durations, units = "hours"), 2)

# Replace any negative values with 0
durations[durations < 0] <- 0

# Find last timestamp for each date and replace duration with 24 hours
last_times <- dc_4 %>%
  group_by(Date = as.Date(date1)) %>%
  slice_tail(n = 1) %>%
  ungroup()

durations[df$date1 %in% last_times$date1] <- 24

df$duration <- durations

df1 <- df %>% select(date1, duration)

head(df1, 10)