因此，我想计算每个数字列的平均值并将结果放在该列下方的行中。让我们从数据开始：
> 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。
用途rbind和colMeans在：
> 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（例如“说明”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sapply(df, is.numeric)用来获取数字列，然后在其上进行计算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，则可以通过以下方式取消选择该列df[, -1]：
suppressWarnings(rbind(df, colMeans = colMeans(df[, -1])))
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