I have 3 dataframes:
dput(head(nSOS_VI_GPR_05,20))
structure(list(ID = c("AUR", "AUR", "AUR", "AUR", "AUR", "AUR",
"LAM", "LAM", "LAM", "LAM", "LAM", "LAM", "P0", "P01", "P02",
"P1", "P13", "P18", "P19", "P2"), N_D_SOS = c(129, 349, 256,
319, 306, 128, 309, 244, 134, 356, 131, 302, 276, 296, 294, 310,
295, 337, 295, 291), N_EVI_SOS = c(134, 337, 212, 331, 296, 134,
309, 334, 112, 352, 108, 302, 260, 303, 295, 287, 648, 384, 424,
283), N_NDVI_SOS = c(7, 302, 259, 300, 297, 139, 302, 346, 111,
358, 137, 298, 269, 303, 296, 289, 484, 328, 436, 287), N_NIRv_SOS = c(133,
297, 266, 285, 293, 130, 312, 335, 115, 363, 140, 302, 264, 306,
298, 290, 645, 340, 423, 293), N_kNDVI_SOS = c(132, 314, 268,
319, 297, 139, 308, 334, 111, 356, 135, 301, 271, 294, 297, 296,
419, 331, 436, 294)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
> dput(head(nSOS_VI_GPR_10,20))
structure(list(ID = c("AUR", "AUR", "AUR", "AUR", "AUR", "AUR",
"LAM", "LAM", "LAM", "LAM", "LAM", "LAM", "P0", "P01", "P02",
"P1", "P13", "P18", "P19", "P2"), N_D_SOS = c(129, 349, 256,
319, 306, 128, 309, 244, 134, 356, 131, 302, 276, 296, 294, 310,
295, 337, 295, 291), N_EVI_SOS = c(139, 342, 271, 336, 339, 141,
316, 338, 119, 362, 144, 308, 267, 317, 304, 293, 657, 406, 428,
290), N_NDVI_SOS = c(1, 314, 266, 317, 307, 143, 306, 350, 118,
363, 144, 303, 274, 309, 302, 294, 487, 339, 440, 293), N_NIRv_SOS = c(139,
334, 271, 327, 341, 139, 318, 339, 124, 370, 149, 308, 271, 319,
306, 296, 655, 382, 427, 302), N_kNDVI_SOS = c(137, 335, 272,
325, 319, 144, 314, 340, 119, 362, 143, 305, 277, 306, 303, 300,
425, 349, 440, 299)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
> dput(head(nSOS_VI_GPR_15,20))
structure(list(ID = c("AUR", "AUR", "AUR", "AUR", "AUR", "AUR",
"LAM", "LAM", "LAM", "LAM", "LAM", "LAM", "P0", "P01", "P02",
"P1", "P13", "P18", "P19", "P2"), N_D_SOS = c(129, 349, 256,
319, 306, 128, 309, 244, 134, 356, 131, 302, 276, 296, 294, 310,
295, 337, 295, 291), N_EVI_SOS = c(144, 347, 274, 340, 346, 148,
322, 341, 125, 370, 151, 313, 272, 329, 312, 297, 665, 423, 431,
295), N_NDVI_SOS = c(6, 331, 269, 322, 316, 146, 310, 353, 124,
367, 149, 306, 278, 313, 306, 298, 490, 348, 443, 297), N_NIRv_SOS = c(143,
338, 274, 331, 347, 154, 324, 343, 130, 376, 155, 313, 276, 328,
313, 301, 662, 419, 430, 308), N_kNDVI_SOS = c(141, 343, 275,
328, 332, 148, 319, 344, 124, 366, 149, 309, 281, 313, 307, 303,
429, 374, 443, 303)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
I want to calculate the average of the columns N_EVI_SOS, N_NDVI_SOS, N_NIRv_SOS and N_kNDVI_SOS of the 3 dataframes by row.
For example, the first row of the column N_EVI_SOS would be average (134; 139; 144) = 139.
In the end, I would have 20 averages for each of the correspondent columns.
I've looking for a solution where I don't have to join the dataframes. Any help will be much appreciated.
tidyvrse
l <- mget(x = ls(pattern = "nSOS_VI_GPR_"))
VARS <- c("N_EVI_SOS", "N_NDVI_SOS", "N_NIRv_SOS")
library(tidyverse)
l_VARS <- map(VARS, function(x) map_dfc(l, function(y) y[x]))
map_dfc(l_VARS, rowMeans) %>%
set_names(nm = paste0(VARS, "_mean"))
result
#> # A tibble: 20 × 3
#> N_EVI_SOS_mean N_NDVI_SOS_mean N_NIRv_SOS_mean
#> <dbl> <dbl> <dbl>
#> 1 139 4.67 138.
#> 2 342 316. 323
#> 3 252. 265. 270.
#> 4 336. 313 314.
#> 5 327 307. 327
#> 6 141 143. 141
#> 7 316. 306 318
#> 8 338. 350. 339
#> 9 119. 118. 123
#> 10 361. 363. 370.
#> 11 134. 143. 148
#> 12 308. 302. 308.
#> 13 266. 274. 270.
#> 14 316. 308. 318.
#> 15 304. 301. 306.
#> 16 292. 294. 296.
#> 17 657. 487 654
#> 18 404. 338. 380.
#> 19 428. 440. 427.
#> 20 289. 292. 301
data
nSOS_VI_GPR_05 <- structure(list(ID = c("AUR", "AUR", "AUR", "AUR", "AUR", "AUR",
"LAM", "LAM", "LAM", "LAM", "LAM", "LAM", "P0", "P01", "P02",
"P1", "P13", "P18", "P19", "P2"), N_D_SOS = c(129, 349, 256,
319, 306, 128, 309, 244, 134, 356, 131, 302, 276, 296, 294, 310,
295, 337, 295, 291), N_EVI_SOS = c(134, 337, 212, 331, 296, 134,
309, 334, 112, 352, 108, 302, 260, 303, 295, 287, 648, 384, 424,
283), N_NDVI_SOS = c(7, 302, 259, 300, 297, 139, 302, 346, 111,
358, 137, 298, 269, 303, 296, 289, 484, 328, 436, 287), N_NIRv_SOS = c(133,
297, 266, 285, 293, 130, 312, 335, 115, 363, 140, 302, 264, 306,
298, 290, 645, 340, 423, 293), N_kNDVI_SOS = c(132, 314, 268,
319, 297, 139, 308, 334, 111, 356, 135, 301, 271, 294, 297, 296,
419, 331, 436, 294)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
nSOS_VI_GPR_10 <- structure(list(ID = c("AUR", "AUR", "AUR", "AUR", "AUR", "AUR",
"LAM", "LAM", "LAM", "LAM", "LAM", "LAM", "P0", "P01", "P02",
"P1", "P13", "P18", "P19", "P2"), N_D_SOS = c(129, 349, 256,
319, 306, 128, 309, 244, 134, 356, 131, 302, 276, 296, 294, 310,
295, 337, 295, 291), N_EVI_SOS = c(139, 342, 271, 336, 339, 141,
316, 338, 119, 362, 144, 308, 267, 317, 304, 293, 657, 406, 428,
290), N_NDVI_SOS = c(1, 314, 266, 317, 307, 143, 306, 350, 118,
363, 144, 303, 274, 309, 302, 294, 487, 339, 440, 293), N_NIRv_SOS = c(139,
334, 271, 327, 341, 139, 318, 339, 124, 370, 149, 308, 271, 319,
306, 296, 655, 382, 427, 302), N_kNDVI_SOS = c(137, 335, 272,
325, 319, 144, 314, 340, 119, 362, 143, 305, 277, 306, 303, 300,
425, 349, 440, 299)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
nSOS_VI_GPR_15 <- structure(list(ID = c("AUR", "AUR", "AUR", "AUR", "AUR", "AUR",
"LAM", "LAM", "LAM", "LAM", "LAM", "LAM", "P0", "P01", "P02",
"P1", "P13", "P18", "P19", "P2"), N_D_SOS = c(129, 349, 256,
319, 306, 128, 309, 244, 134, 356, 131, 302, 276, 296, 294, 310,
295, 337, 295, 291), N_EVI_SOS = c(144, 347, 274, 340, 346, 148,
322, 341, 125, 370, 151, 313, 272, 329, 312, 297, 665, 423, 431,
295), N_NDVI_SOS = c(6, 331, 269, 322, 316, 146, 310, 353, 124,
367, 149, 306, 278, 313, 306, 298, 490, 348, 443, 297), N_NIRv_SOS = c(143,
338, 274, 331, 347, 154, 324, 343, 130, 376, 155, 313, 276, 328,
313, 301, 662, 419, 430, 308), N_kNDVI_SOS = c(141, 343, 275,
328, 332, 148, 319, 344, 124, 366, 149, 309, 281, 313, 307, 303,
429, 374, 443, 303)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))