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法律研究如何在 R 中複製整個資料框並在原始資料框中新增它？
R 中資料框的複製可以透過 sapply 函式建立，為了設定我們想要重複資料框的次數，我們可以使用 rep.int，times 引數。例如，如果我們有一個數據框 df，並且我們想要建立 5 個 df 的副本並在原始資料框中新增它們，則可以使用 sapply(df,rep.int,times=5)。
示例
考慮以下資料框 -
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
輸出
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
複製 df 兩次 -
sapply(df,rep.int,times=2)
輸出
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
複製 df 三次 -
sapply(df,rep.int,times=3)
輸出
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
複製 df 四次 -
示例
sapply(df,rep.int,times=4)
輸出
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
複製 df 五次 -
示例
sapply(df,rep.int,times=5)
輸出
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
更新於: 2020年10月17日
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