r - 计算每个数字列的平均值并将结果添加为行

Question

所以，我想计算每个数字列的平均值，并将结果放在列下方的行中。让我们从一个数据开始:

> head(tbl_mut)

     timetE4_1  timetE1_2  timetE2_2  timetE3_2  timetE4_2   eve_mean   mor_mean  tot_mean
    1   4048.605   59094.48   27675.59   26374.06   43310.01   7774.442   39113.53  23443.99
    2  45729.986  139889.21  111309.64  129781.17   96924.62  43374.117  119476.16  81425.14
    3 639686.154 1764684.16 1117027.29 1147967.45 1156442.48 585562.724 1296530.34 941046.53
    4   4466.153   26250.32   20320.08   18413.54   29061.25   3866.547   23511.30  13688.92

这就是我想要实现的目标:

timetE4_1  timetE1_2  timetE2_2  timetE3_2  timetE4_2   eve_mean   mor_mean  tot_mean
    1   4048.605   59094.48   27675.59   26374.06   43310.01   7774.442   39113.53  23443.99
    2  45729.986  139889.21  111309.64  129781.17   96924.62  43374.117  119476.16  81425.14
    3 639686.154 1764684.16 1117027.29 1147967.45 1156442.48 585562.724 1296530.34 941046.53
    4   4466.153   26250.32   20320.08   18413.54   29061.25   3866.547   23511.30  13688.92
    .....
    445    X          X          X          X          X         X           X          X

X - 列中值的平均值。
请注意，数据可能包含其他非数字列。

Answer 1

使用 rbind 和 colMeans 如下:

> rbind(tbl_mut, colMeans = colMeans(tbl_mut))
          timetE4_1  timetE1_2  timetE2_2  timetE3_2  timetE4_2   eve_mean   mor_mean  tot_mean
1          4048.605   59094.48   27675.59   26374.06   43310.01   7774.442   39113.53  23443.99
2         45729.986  139889.21  111309.64  129781.17   96924.62  43374.117  119476.16  81425.14
3        639686.154 1764684.16 1117027.29 1147967.45 1156442.48 585562.724 1296530.34 941046.53
4          4466.153   26250.32   20320.08   18413.54   29061.25   3866.547   23511.30  13688.92
colMeans 173482.724  497479.54  319083.15  330634.05  331434.59 160144.458  369657.83 264901.15

编辑
假设您的数据框同时包含数字和非数字列(如“描述”列):

> df
  Description  timetE4_1  timetE1_2  timetE2_2  timetE3_2  timetE4_2   eve_mean   mor_mean  tot_mean
1           A   4048.605   59094.48   27675.59   26374.06   43310.01   7774.442   39113.53  23443.99
2           B  45729.986  139889.21  111309.64  129781.17   96924.62  43374.117  119476.16  81425.14
3           C 639686.154 1764684.16 1117027.29 1147967.45 1156442.48 585562.724 1296530.34 941046.53
4           D   4466.153   26250.32   20320.08   18413.54   29061.25   3866.547   23511.30  13688.92

...然后您可以使用 sapply(df, is.numeric) 获取数字列，然后在其上计算 colmeans 。

> suppressWarnings(rbind(df, colMeans = colMeans(df[, sapply(df, is.numeric)])))
         Description  timetE4_1  timetE1_2  timetE2_2  timetE3_2  timetE4_2   eve_mean   mor_mean  tot_mean
1                  A   4048.605   59094.48   27675.59   26374.06   43310.01   7774.442   39113.53  23443.99
2                  B  45729.986  139889.21  111309.64  129781.17   96924.62  43374.117  119476.16  81425.14
3                  C 639686.154 1764684.16 1117027.29 1147967.45 1156442.48 585562.724 1296530.34 941046.53
4                  D   4466.153   26250.32   20320.08   18413.54   29061.25   3866.547   23511.30  13688.92
colMeans        <NA> 497479.542  319083.15  330634.05  331434.59  160144.46 369657.833  264901.15 173482.72

或者，如果您知道非数字变量的索引，例如第一列，您可以使用 df[, -1] 取消选择该列:

suppressWarnings(rbind(df, colMeans = colMeans(df[, -1])))