Menu
For example, I have a data like below.
dataA=structure(list(variety = c("CV1", "CV1", "CV1", "CV1", "CV1",
"CV1", "CV1", "CV1", "CV1", "CV1", "CV1", "CV1", "CV1", "CV1",
"CV1", "CV1", "CV1", "CV1", "CV1", "CV1", "CV1", "CV1", "CV1",
"CV1", "CV1", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2",
"CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2",
"CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2", "CV2",
"CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3",
"CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3",
"CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV3", "CV4", "CV4",
"CV4", "CV4", "CV4", "CV4", "CV4", "CV4", "CV4", "CV4", "CV4",
"CV4", "CV4", "CV4", "CV4", "CV4", "CV4", "CV4", "CV4", "CV4",
"CV4", "CV4", "CV4", "CV4", "CV4"), KN = c(3150, 2646, 3024,
3402, 3260.25, 3276, 3150, 3685.5, 3260.25, 3402, 4672, 4234,
4599, 4526, 4599, 4526, 4234, 4088, 3504, 3942, 3550, 3550, 3124,
4437.5, 3550, 4313.25, 4118, 4153.5, 4473, 3851.75, 4260, 4952.25,
5680, 5112, 5431.5, 3976, 5112, 4828, 4544, 5112, 4632.75, 5271.75,
3976, 4792.5, 4544, 4313.25, 4952.25, 4792.5, 4260, 4952.25,
3192.75, 2580, 2999.25, 2580, 3096, 2902.5, 2805.75, 2332.75,
2999.25, 2666, 3240, 3648, 3360, 3564, 3360, 3360, 3552, 3648,
3456, 4320, 3256, 3564, 2992, 3663, 3168, 3861, 3663, 3861, 3564,
3465, 2886, 3042, 2886, 2886, 3412.5, 2886, 3510, 3246.75, 3159,
3159, 3384, 3760, 4018.5, 3572, 3912.75, 4018.5, 4230, 3572,
3478, 3760), GY = c(9729.7744491255, 8562.20151523044, 9885.45084031151,
10741.6709918346, 9729.7744491255, 10118.9654270905, 9963.28903590451,
10975.1855786136, 10118.9654270905, 10041.1272314975, 12266.3112039261,
11454.5700213133, 12356.5046686608, 12627.0850628651, 13889.7935691516,
11995.7308097218, 11364.3765565786, 12085.9242744566, 11725.1504155176,
10552.6353739658, 10000.3548433298, 12368.8599378026, 10438.9668978618,
11316.1910069258, 10614.4117196746, 12632.0271705218, 13421.5288686794,
12456.582348709, 12368.8599378026, 12105.6927050834, 17281.3149485611,
17281.3149485611, 16404.090839497, 17719.9270030931, 18158.5390576251,
15877.7563740586, 19825.2648648467, 18333.9838794379, 17105.8701267483,
19123.4855775955, 14035.5857450242, 15351.4219086202, 14474.1977995562,
15702.3115522458, 15351.4219086202, 11930.2478832706, 15702.3115522458,
13860.1409232114, 13947.8633341178, 8859.96350154653, 8712.93579875975,
8075.40391104562, 8553.55282683122, 8394.16985490268, 9137.95705723583,
9403.59534378339, 8606.68048414073, 7969.1485964266, 8819.19111337877,
8606.68048414073, 11268.005457273, 13106.4695055649, 10437.7313709476,
10674.9525384691, 9844.67845214374, 10971.478997871, 11623.8372085553,
11327.3107491533, 10852.8684141103, 11149.3948735122, 11959.9005292108,
14134.4278981582, 11851.1741607634, 13101.5273979082, 12068.6268976581,
13373.3433190266, 12286.0796345529, 12394.8060030003, 12449.1691872239,
13427.7065032503, 11516.3463670221, 10745.3775725771, 11275.418618758,
11660.9030159805, 11805.4596649389, 11660.9030159805, 12287.3151614671,
12865.5417573008, 11564.5319166749, 12046.387413203, 14691.650536451,
14807.7900663834, 15504.6272459779, 14517.4412415523, 14923.9295963158,
14807.7900663834, 14923.9295963158, 13936.7435918902, 14459.3714765861,
14517.4412415523)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-100L))
Now, I'd like to normalize data per variety about KN and GY values respectively.
Simply, what I did is
CV1=subset(dataA, variety=="CV1")
CV2=subset(dataA, variety=="CV2")
CV3=subset(dataA, variety=="CV3")
CV1$CV1_KN=scale(CV1$KN, center=TRUE, scale=TRUE)
CV2$CV2_KN=scale(CV2$KN, center=TRUE, scale=TRUE)
CV3$CV3_KN=scale(CV3$KN, center=TRUE, scale=TRUE)
CV1$CV1_GY=scale(CV1$GY, center=TRUE, scale=TRUE)
CV2$CV2_GY=scale(CV2$GY, center=TRUE, scale=TRUE)
CV3$CV3_GY=scale(CV3$GY, center=TRUE, scale=TRUE)
Then I download each data and match it to each variety in an Excel file. But in my actual data, I have more than 30 varieties, and it's impossible to manually match. I believe there are simple ways to automatically obtain normalized data per group in R.
Could you let me know how to do it?
Always many thanks!!
624
asked Feb 02 '26 21:02
Here we will get a list of the different variety:
library(dplyr)
dataA_normalized <- dataA %>%
group_by(variety) %>%
mutate(KN_scaled = scale(KN, center = TRUE, scale = TRUE),
GY_scaled = scale(GY, center = TRUE, scale = TRUE)) %>%
group_split()
<list_of<
tbl_df<
variety : character
KN : double
GY : double
KN_scaled: double[,1]
GY_scaled: double[,1]
>
>[4]>
[[1]]
# A tibble: 25 × 5
variety KN GY KN_scaled[,1] GY_scaled[,1]
<chr> <dbl> <dbl> <dbl> <dbl>
1 CV1 3150 9730. -0.980 -1.05
2 CV1 2646 8562. -1.82 -2.01
3 CV1 3024 9885. -1.19 -0.919
4 CV1 3402 10742. -0.558 -0.211
5 CV1 3260. 9730. -0.795 -1.05
6 CV1 3276 10119. -0.769 -0.726
7 CV1 3150 9963. -0.980 -0.854
8 CV1 3686. 10975. -0.0839 -0.0180
9 CV1 3260. 10119. -0.795 -0.726
10 CV1 3402 10041. -0.558 -0.790
# … with 15 more rows
# ℹ Use `print(n = ...)` to see more rows
[[2]]
# A tibble: 25 × 5
variety KN GY KN_scaled[,1] GY_scaled[,1]
<chr> <dbl> <dbl> <dbl> <dbl>
1 CV2 4313. 12632. -0.703 -0.962
2 CV2 4118 13422. -1.10 -0.663
3 CV2 4154. 12457. -1.03 -1.03
4 CV2 4473 12369. -0.376 -1.06
5 CV2 3852. 12106. -1.65 -1.16
6 CV2 4260 17281. -0.813 0.798
7 CV2 4952. 17281. 0.607 0.798
8 CV2 5680 16404. 2.10 0.466
9 CV2 5112 17720. 0.935 0.964
10 CV2 5432. 18159. 1.59 1.13
# … with 15 more rows
# ℹ Use `print(n = ...)` to see more rows
[[3]]
# A tibble: 25 × 5
variety KN GY KN_scaled[,1] GY_scaled[,1]
<chr> <dbl> <dbl> <dbl> <dbl>
1 CV3 3193. 8713. -0.0445 -0.978
2 CV3 2580 8075. -1.45 -1.34
3 CV3 2999. 8554. -0.487 -1.07
4 CV3 2580 8394. -1.45 -1.16
5 CV3 3096 9138. -0.266 -0.736
6 CV3 2902. 9404. -0.708 -0.584
7 CV3 2806. 8607. -0.930 -1.04
8 CV3 2333. 7969. -2.01 -1.40
9 CV3 2999. 8819. -0.487 -0.918
10 CV3 2666 8607. -1.25 -1.04
# … with 15 more rows
# ℹ Use `print(n = ...)` to see more rows
[[4]]
# A tibble: 25 × 5
variety KN GY KN_scaled[,1] GY_scaled[,1]
<chr> <dbl> <dbl> <dbl> <dbl>
1 CV4 3861 13373. 0.949 0.162
2 CV4 3663 12286. 0.446 -0.587
3 CV4 3861 12395. 0.949 -0.512
4 CV4 3564 12449. 0.194 -0.475
5 CV4 3465 13428. -0.0578 0.200
6 CV4 2886 11516. -1.53 -1.12
7 CV4 3042 10745. -1.13 -1.65
8 CV4 2886 11275. -1.53 -1.28
9 CV4 2886 11661. -1.53 -1.02
10 CV4 3412. 11805. -0.191 -0.919
# … with 15 more rows
# ℹ Use `print(n = ...)` to see more rows
We may use across
library(dplyr)# version >= 1.1.0
dataA %>%
mutate(across(c(KN, GY), ~ scale(.x, center = TRUE, scale = TRUE)[,1]
, .names = "{.col}_scaled"), .by = variety)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
