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How to replicate whole data frame and add it in the original one in R?
The replicates of a data frame in R can be created with the help of sapply function, to set the number of times we want to repeat the data frame we can use rep.int,times argument. For example, if we have a data frame df and we want to create 5 replicates of df and add them in the original then sapply(df,rep.int,times=5) can be used.
Example
Consider the below data frame −
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
Output
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
Replicating df two times −
sapply(df,rep.int,times=2)
Output
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
Replicating df three times −
sapply(df,rep.int,times=3)
Output
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
Replicating df four times −
Example
sapply(df,rep.int,times=4)
Output
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
Replicating df five times −
Example
sapply(df,rep.int,times=5)
Output
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
Updated on: 17-Oct-2020
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