如何通过R中的行创建数据帧值的向量？
要按行创建数据帧值的向量，我们可以在将数据帧与t换位后使用c函数。例如，如果我们有一个包含许多列的数据帧df，则可以使用c（t(df)）将df值转换为向量，这将逐行打印数据帧的值。
例1
set.seed(798)x1<−rnorm(20,5,2)
x2<−rnorm(20,5,3)
df1<−data.frame(x1,x2)
df1
输出结果
x1 x21 2.786103 −3.098242
2 8.533086 5.943967
3 10.291147 5.841057
4 5.449163 3.989173
5 5.810170 6.463880
6 4.479613 8.594108
7 7.569711 2.420207
8 8.058095 4.875600
9 3.827098 5.239763
10 5.807293 6.416752
11 4.431298 5.827411
12 4.140034 4.705993
13 6.643332 1.450062
14 1.787068 11.405792
15 5.356992 5.258035
16 5.027659 6.665030
17 3.617873 4.955072
18 8.190755 2.514271
19 4.675561 6.849762
20 10.532212 6.050328
Vector_df1<−c(t(df1))
Vector_df1
[1] 2.786103 −3.098242 8.533086 5.943967 10.291147 5.841057 5.449163
[8] 3.989173 5.810170 6.463880 4.479613 8.594108 7.569711 2.420207
[15] 8.058095 4.875600 3.827098 5.239763 5.807293 6.416752 4.431298
[22] 5.827411 4.140034 4.705993 6.643332 1.450062 1.787068 11.405792
[29] 5.356992 5.258035 5.027659 6.665030 3.617873 4.955072 8.190755
[36] 2.514271 4.675561 6.849762 10.532212 6.050328
is.vector(Vector_df1)
[1] TRUE
例2
y1<−rpois(20,10)y2<−rpois(20,5)
y3<−rpois(20,3)
df2<−data.frame(y1,y2,y3)
df2
输出结果
y1 y2 y31 6 7 1
2 7 7 4
3 16 6 3
4 12 4 4
5 9 4 3
6 10 3 4
7 8 4 1
8 12 4 0
9 9 4 4
10 15 4 5
11 4 6 5
12 10 4 2
13 8 9 2
14 7 4 5
15 9 7 3
16 8 3 7
17 9 6 3
18 6 3 3
19 11 6 7
20 7 2 0
Vector_df2<−c(t(df2))
Vector_df2
[1] 6 7 1 7 7 4 16 6 3 12 4 4 9 4 3 10 3 4 8 4 1 12 4 0 9
[26] 4 4 15 4 5 4 6 5 10 4 2 8 9 2 7 4 5 9 7 3 8 3 7 9 6
[51] 3 6 3 3 11 6 7 7 2 0
is.vector(Vector_df2)
[1] TRUE
例子3
z1<−letters[1:20]z2<−rexp(20,1.98)
z3<−runif(20,1,5)
df3<−data.frame(z1,z2,z3)
df3
输出结果
z1 z2 z31 a 0.30649942 2.581508
2 b 0.49573688 1.005800
3 c 0.32632915 1.582261
4 d 0.16866850 2.364847
5 e 0.49920925 4.822604
6 f 0.48753521 2.516127
7 g 1.11453076 1.369764
8 h 0.03852521 3.055764
9 i 0.43320666 4.336745
10 j 1.53110506 1.253256
11 k 1.02885841 3.401008
12 l 0.93749136 1.272466
13 m 0.05544727 1.839311
14 n 0.06982751 3.857567
15 o 0.03554147 2.816643
16 p 0.27870340 4.920266
17 q 0.30576924 1.781030
18 r 0.13628651 2.365232
19 s 1.23068290 4.879601
20 t 0.31617628 1.026273
Vector_df3<−c(t(df3))
Vector_df3
[1] "a" "0.30649942" "2.581508" "b" "0.49573688"
[6] "1.005800" "c" "0.32632915" "1.582261" "d"
[11] "0.16866850" "2.364847" "e" "0.49920925" "4.822604"
[16] "f" "0.48753521" "2.516127" "g" "1.11453076"
[21] "1.369764" "h" "0.03852521" "3.055764" "i"
[26] "0.43320666" "4.336745" "j" "1.53110506" "1.253256"
[31] "k" "1.02885841" "3.401008" "l" "0.93749136"
[36] "1.272466" "m" "0.05544727" "1.839311" "n"
[41] "0.06982751" "3.857567" "o" "0.03554147" "2.816643"
[46] "p" "0.27870340" "4.920266" "q" "0.30576924"
[51] "1.781030" "r" "0.13628651" "2.365232" "s"
[56] "1.23068290" "4.879601" "t" "0.31617628" "1.026273"
is.vector(Vector_df3)
[1] TRUE
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