将数据集的行与R中的另一个数据集进行比较

我有数据集1，有1400行25列，数据集2，有400行5列。两个数据集都有一个名为ID的列。作为一个小示例，我可以如下所示说明它们：

数据集1：

ID  c1  c2  c3    c4
12   m   n   5   1/2/2015
5    c   x   4   2/3/2015
45   g   t   47  4/23/2015
45   j   t   3   1/1/2016
61   t   y   12  7/3/2015
3    r   n   18  3/3/2015

数据集2：

 ID  a1    a2
 45   1    1/1/2015
 3    5    2/2/2016
 12   12   4/29/2016

（如您所见，dataset2中的ID是dataset1中ID的子集）

我想要的是：对于dataset1的每一行，如果列ID中的值等于dataset2的列ID中的值，则将该行dataset2的列a2的相应值复制到dataset1的新列中，如下所示：

  ID  c1  c2  c3     c4           c5
  12   m   n   5   1/2/2015    4/29/2016
  5    c   x   4   2/3/2015       NA
  45   g   t   47  4/23/2015   1/1/2015
  45   j   t   3   1/1/2016    1/1/2015
  61   t   y   12  7/3/2015       NA
  3    r   n   18  3/3/2015    2/2/2016

---

我感谢你的帮助

如@42所述，您可以使用match

这是match的一个示例：

# match the ID of df1 with that of df2
# then returns the index of df2 that
# matches df1
# then subset the a2 column using the above index
# then store in a new column in df1
df1$c5 <- df2$a2[match(df1$ID, df2$ID)]

#将df1的ID与df2的ID匹配
#然后返回df2的索引
#匹配df1
#然后使用上述索引对a2列进行子集划分
#然后存储在df1中的新列中
df1$c5 df1
ID c1 c2 c3 c4 c5
112M n 5 01/02/2015 4/29/2016
2 5 c x 4 01/02/2015
3 45 g t 47 01/02/2015 01/01/2015
4 45 j t 3 01/02/2015 01/01/2015
5 61 t y 12 01/02/2015
6 3 r n 18 01/02/2015 02/02/2016

din的答案是完美的。另一种考虑方法是合并到数据帧

数据准备

ex_data1 <- data.frame(ID = c(12, 5, 45, 45, 61, 3),
                       c1 = c("m", "c", "g", "j", "t", "r"),
                       c2 = c("n", "x", "t", "t", "y", "n"),
                       c3 = c(5, 4, 47, 3, 12, 8), 
                       c4 = c("1/2/2015", "2/3/2015", "4/23/2015",
                              "1/1/2016", "7/3/2015", "3/3/2015"),
                       stringsAsFactors = FALSE)

ex_data2 <- data.frame(ID = c(45, 3, 12),
                       a1 = c(1, 5, 12),
                       a2 = c("1/1/2015", "2/2/2016", "4/29/2016"), stringsAsFactors = FALSE)

---

欢迎来到StackOverflow！请阅读相关信息以及如何给出建议。这将使其他人更容易帮助您。可能需要

匹配

或

哪个

，但我通常不会回答，除非添加了示例。请帮我回答！

ex_data1 <- data.frame(ID = c(12, 5, 45, 45, 61, 3),
                       c1 = c("m", "c", "g", "j", "t", "r"),
                       c2 = c("n", "x", "t", "t", "y", "n"),
                       c3 = c(5, 4, 47, 3, 12, 8), 
                       c4 = c("1/2/2015", "2/3/2015", "4/23/2015",
                              "1/1/2016", "7/3/2015", "3/3/2015"),
                       stringsAsFactors = FALSE)

ex_data2 <- data.frame(ID = c(45, 3, 12),
                       a1 = c(1, 5, 12),
                       a2 = c("1/1/2015", "2/2/2016", "4/29/2016"), stringsAsFactors = FALSE)

ex_data3 <- ex_data2[, c("ID", "a2")]
names(ex_data3) <- c("ID", "c5")

m_data <- merge(ex_data1, ex_data3, by = "ID", all = TRUE)

library(dplyr)

m_data <- ex_data1 %>%
  left_join(ex_data2, by = "ID") %>%
  select(-a1, c5 = a2)