R - 合并 2 个数据框，其中一列不同

Question

我有 2 个列大小为 5 的数据框。前 4 个列名相同，最后一列不同。我在最后一列中报告了值 (T)，表明相应数据帧中的每个平均值和 sigma 都存在异常值。

我的第一个数据框 - df1

    TimeStamp <- c("2015-04-01 11:40:13", "2015-04-03 02:54:45")
    ID <- c("DL1X8", "DL202")
    Avg <- c(38.1517, 0.7131)
    Sig <- c(11.45880000, 0.01257816)
    Outlier_Avg <- c("T","T")
    df1 <- data.frame(TimeStamp, ID, Avg, Sig,Outlier_Avg)


    +---------------------+-------+---------+-------------+-------------+
    |      TimeStamp      |  ID   |   Avg   |     Sig     | Outlier_Avg |
    +---------------------+-------+---------+-------------+-------------+
    | 2015-04-01 11:40:13 | DL1X8 | 38.1517 | 11.45880000 | T           |
    | 2015-04-03 02:54:45 | DL202 | 0.7131  | 0.01257816  | T           |
    +---------------------+-------+---------+-------------+-------------+

我的第二个数据框 - df2

TimeStamp <- c("2015-04-01 11:40:13", "2015-04-04 02:57:45", "2015-04-06 09:54:45")
ID <- c("DL1X8", "DP308","DM3X8")
Avg <- c(38.1517, 24.7131, 0.0234)
Sig <- c(11.4588, 6.0175,0.0665)
Outlier_Sig <- c("T","T","T")
df2 <- data.frame(TimeStamp, ID, Avg, Sig,Outlier_Sig)

+---------------------+-------+---------+---------+-------------+
|      TimeStamp      |  ID   |   Avg   |   Sig   | Outlier_Sig |
+---------------------+-------+---------+---------+-------------+
| 2015-04-01 11:40:13 | DL1X8 | 38.1517 | 11.4588 | T           |
| 2015-04-04 02:57:45 | DP308 | 24.7131 | 6.0175  | T           |
| 2015-04-06 09:54:45 | DM3X8 | 0.0234  | 0.0665  | T           |
+---------------------+-------+---------+---------+-------------+

期望的输出：

我正在尝试获得一个看起来像这样的 df3

+---------------------+-------+---------+-------------+-------------+-------------+
|      TimeStamp      |  ID   |   Avg   |     Sig     | Outlier_Avg | Outlier_Sig |
+---------------------+-------+---------+-------------+-------------+-------------+
| 2015-04-01 11:40:13 | DL1X8 | 38.1517 | 11.45880000 | T           | T           |
| 2015-04-03 02:54:45 | DL202 | 0.7131  | 0.01257816  | T           | N/A         |
| 2015-04-04 02:57:45 | DP308 | 24.7131 | 6.0175      | N/A         | T           |
| 2015-04-06 09:54:45 | DM3X8 | 0.0234  | 0.0665      | N/A         | T           |
+---------------------+-------+---------+-------------+-------------+-------------+

我尝试使用合并（df1，df2）。它只返回匹配的行，因此只返回 1 行。我需要返回所有行并输入 N/A，如上所示。你能帮我解决这个问题吗？

Answer 1

使用all 参数：

merge(df1, df2, all = TRUE)
#             TimeStamp    ID     Avg         Sig Outlier_Avg Outlier_Sig
# 1 2015-04-01 11:40:13 DL1X8 38.1517 11.45880000           T           T
# 2 2015-04-03 02:54:45 DL202  0.7131  0.01257816           T        <NA>
# 3 2015-04-04 02:57:45 DP308 24.7131  6.01750000        <NA>           T
# 4 2015-04-06 09:54:45 DM3X8  0.0234  0.06650000        <NA>           T

这是使用all.x = TRUE 和all.y = TRUE 的简写，它们是单独的参数，可让您控制来自x（在您的情况下为df1）和y（在您的情况下为df2）的哪些观察结果包含在合并的data.frame。参见，例如：

merge(df1, df2, all.x = TRUE)
#             TimeStamp    ID     Avg         Sig Outlier_Avg Outlier_Sig
# 1 2015-04-01 11:40:13 DL1X8 38.1517 11.45880000           T           T
# 2 2015-04-03 02:54:45 DL202  0.7131  0.01257816           T        <NA>

merge(df1, df2, all.y = TRUE)
#             TimeStamp    ID     Avg     Sig Outlier_Avg Outlier_Sig
# 1 2015-04-01 11:40:13 DL1X8 38.1517 11.4588           T           T
# 2 2015-04-04 02:57:45 DP308 24.7131  6.0175        <NA>           T
# 3 2015-04-06 09:54:45 DM3X8  0.0234  0.0665        <NA>           T