如何复制整个数据帧并将其添加到R中的原始数据帧中？
可以使用sapply函数在R中创建数据帧的副本，以使用rep.int，times参数设置要重复数据帧的次数。例如，如果我们有一个数据帧df，并且想要创建df的5个副本并将它们添加到原始副本中，则可以使用sapply（df，rep.int，times = 5）。
示例
请看以下数据帧-
set.seed(151)x1<-rnorm(5,21,3)
x2<-rnorm(5,8,1.9)
x3<-rnorm(5,3,0.08)
x4<-rnorm(5,1008,32.4)
df<-data.frame(x1,x2,x3,x4)
df
输出结果
x1 x2 x3 x41 20.84538 9.486324 2.961236 967.9296
2 23.29721 5.344792 3.044849 960.2204
3 20.55978 6.064207 3.005293 1086.9639
4 20.66044 8.436004 2.892010 1029.8222
5 19.81347 9.277129 2.980567 1018.0453
复制df两次-
sapply(df,rep.int,times=2)
输出结果
x1 x2 x3 x4[1,] 20.84538 9.486324 2.961236 967.9296
[2,] 23.29721 5.344792 3.044849 960.2204
[3,] 20.55978 6.064207 3.005293 1086.9639
[4,] 20.66044 8.436004 2.892010 1029.8222
[5,] 19.81347 9.277129 2.980567 1018.0453
[6,] 20.84538 9.486324 2.961236 967.9296
[7,] 23.29721 5.344792 3.044849 960.2204
[8,] 20.55978 6.064207 3.005293 1086.9639
[9,] 20.66044 8.436004 2.892010 1029.8222
[10,] 19.81347 9.277129 2.980567 1018.0453
复制df 3次-
sapply(df,rep.int,times=3)
输出结果
x1 x2 x3 x4[1,] 20.84538 9.486324 2.961236 967.9296
[2,] 23.29721 5.344792 3.044849 960.2204
[3,] 20.55978 6.064207 3.005293 1086.9639
[4,] 20.66044 8.436004 2.892010 1029.8222
[5,] 19.81347 9.277129 2.980567 1018.0453
[6,] 20.84538 9.486324 2.961236 967.9296
[7,] 23.29721 5.344792 3.044849 960.2204
[8,] 20.55978 6.064207 3.005293 1086.9639
[9,] 20.66044 8.436004 2.892010 1029.8222
[10,] 19.81347 9.277129 2.980567 1018.0453
[11,] 20.84538 9.486324 2.961236 967.9296
[12,] 23.29721 5.344792 3.044849 960.2204
[13,] 20.55978 6.064207 3.005293 1086.9639
[14,] 20.66044 8.436004 2.892010 1029.8222
[15,] 19.81347 9.277129 2.980567 1018.0453
复制df四次-
示例
sapply(df,rep.int,times=4)
输出结果
x1 x2 x3 x4[1,] 20.84538 9.486324 2.961236 967.9296
[2,] 23.29721 5.344792 3.044849 960.2204
[3,] 20.55978 6.064207 3.005293 1086.9639
[4,] 20.66044 8.436004 2.892010 1029.8222
[5,] 19.81347 9.277129 2.980567 1018.0453
[6,] 20.84538 9.486324 2.961236 967.9296
[7,] 23.29721 5.344792 3.044849 960.2204
[8,] 20.55978 6.064207 3.005293 1086.9639
[9,] 20.66044 8.436004 2.892010 1029.8222
[10,] 19.81347 9.277129 2.980567 1018.0453
[11,] 20.84538 9.486324 2.961236 967.9296
[12,] 23.29721 5.344792 3.044849 960.2204
[13,] 20.55978 6.064207 3.005293 1086.9639
[14,] 20.66044 8.436004 2.892010 1029.8222
[15,] 19.81347 9.277129 2.980567 1018.0453
[16,] 20.84538 9.486324 2.961236 967.9296
[17,] 23.29721 5.344792 3.044849 960.2204
[18,] 20.55978 6.064207 3.005293 1086.9639
[19,] 20.66044 8.436004 2.892010 1029.8222
[20,] 19.81347 9.277129 2.980567 1018.0453
复制df五次-
示例
sapply(df,rep.int,times=5)
输出结果
x1 x2 x3 x4[1,] 20.84538 9.486324 2.961236 967.9296
[2,] 23.29721 5.344792 3.044849 960.2204
[3,] 20.55978 6.064207 3.005293 1086.9639
[4,] 20.66044 8.436004 2.892010 1029.8222
[5,] 19.81347 9.277129 2.980567 1018.0453
[6,] 20.84538 9.486324 2.961236 967.9296
[7,] 23.29721 5.344792 3.044849 960.2204
[8,] 20.55978 6.064207 3.005293 1086.9639
[9,] 20.66044 8.436004 2.892010 1029.8222
[10,] 19.81347 9.277129 2.980567 1018.0453
[11,] 20.84538 9.486324 2.961236 967.9296
[12,] 23.29721 5.344792 3.044849 960.2204
[13,] 20.55978 6.064207 3.005293 1086.9639
[14,] 20.66044 8.436004 2.892010 1029.8222
[15,] 19.81347 9.277129 2.980567 1018.0453
[16,] 20.84538 9.486324 2.961236 967.9296
[17,] 23.29721 5.344792 3.044849 960.2204
[18,] 20.55978 6.064207 3.005293 1086.9639
[19,] 20.66044 8.436004 2.892010 1029.8222
[20,] 19.81347 9.277129 2.980567 1018.0453
[21,] 20.84538 9.486324 2.961236 967.9296
[22,] 23.29721 5.344792 3.044849 960.2204
[23,] 20.55978 6.064207 3.005293 1086.9639
[24,] 20.66044 8.436004 2.892010 1029.8222
[25,] 19.81347 9.277129 2.980567 1018.0453
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