R 按前几行上的多个条件填充NAs

我有一个包含事务的大数据框。字段包括id（用户id）、间隔（0->的整数）、创建（交易日期）、到期（订阅到期日期）和订阅（字符为“一年”或“两年”） 我需要根据基于同一行或前一行的几个条件修改到期时缺少的值

df <- data.frame(id = id,
                 interval = interval,
                 creation = creation,
                 expiry = expiry,
                 subscription = subscription)
df <- df[order(df[, 1], df[, 3]),]

#loop all rows of ordered df (by subsID and payment date)
for (i in 2:nrow(df)) {
    # check NA of expiry
    if (is.na(df[i, 4])) { 
        #if previous row ID and interval match, we treat this as change to subscription
        if (df[i-1, 1] == df[i, 1] & df[i-1, 2] == df[i, 2]) {
            df[i, 4] <- df[i-1, 4]
        # otherwise it's one or two year new subscription so we add days to creation date
        } else if (df[i, 5] == "one year") {
            df[i, 4] <- df[i, 3] + 365
        } else if (df[i, 5] == "two years") {
            df[i, 4] <- df[i, 3] + 720
        }
     }
}

---

df我想它可能会帮助您：

df <- data.frame(id = id,
                 interval = interval,
                 creation = creation,
                 expiry = expiry,
                 subscription = subscription)
df <- df[order(df[, 1], df[, 3]),]

library(dplyr)
df$match_previous <- (df[, 1] == lag(df[, 1]) & df[, 2] == lag(df[, 2]))
df$match_previous[1] <- FALSE
df[, 4] <- ifelse(!is.na(df[, 4]), 
                  df[, 4],
                  ifelse(df$match_previous,
                         lag(df[, 4]),
                         ifelse(df[, 5] == "one year",
                                df[, 3] + 365, df[, 3] + 730)))

df您能否提供数据的模拟以及它的外观以及您希望它的外观？谢谢Kevin，您的解决方案最终成功了，但在某些情况下，一行中有多个NAs，并且match_previous=TRUE脚本会留下一些NAs。然而，通过循环ifelse片段，它摆脱了所有这些。