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So I have this dataset The main transition is pivoting the table, so the population names are on the first column, the names are the headers for each column (and they are renamed, so Chlorophyll is renamed to CHLa for example). The other alteration after the table is pivoted and renamed, is each row is duplicated to a specified amount, so in the preview if you notice, AK is duplicated 8 times, NU is duplicated twice, and so on and so forth. Can anyone help me accomplish this? Thank you!

Daniel.Payter
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  • What would be the value for `Present.Surface.Cloud.cover.Max` or `Present.Surface.Current.Velocity.Lt.max` – akrun Feb 27 '20 at 19:03

2 Answers2

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We can convert to long format with pivot_longer and then do the pivot_wider

library(tidyr)
library(dplyr)
library(stringr)
df1 %>% 
  filter(str_detect(name, 'Chlorophyll')) %>%
  pivot_longer(cols = -name, names_to = "POP") %>%      
  pivot_wider(names_from = name, values_from = value)

data

df1 <- structure(list(AK = c(2.06938085, 0.06230826, 2.48330742, 0.77990199, 
0.05352413, 2.42978332, 0.32111359, -0.31824945, -0.76257673, 
0.21244649), NU = c(0.94342952, 0.06967302, 1.18308591, 0.24512465, 
0.05954595, 1.12353996, 0.3282527, 0.0332011, 0.10143732, 0.01747852
), GR = c(2.02611122, 0.04936086, 2.41093187, 0.45293345, 0.04685186, 
2.36408, -0.2601983, -0.5992214, -0.53467979, 0.07776527), LB = c(1.54587253, 
0.26267895, 1.74803992, 0.67839487, 0.22805005, 1.51998983, -0.25436427, 
-0.07033478, 0.09848198, 0.07864418), NF = c(1.63438226, 0.19021245, 
1.81304267, 0.69796724, 0.1629694, 1.65007327, 0.21143971, 0.32577614, 
0.29918981, 0.08665113), ST = c(2.40265686, 1.16806181, 2.66182316, 
1.7417354, 0.89450362, 1.76731954, -0.38944296, -0.31842728, 
-0.27451047, 0.09962626), NS = c(1.143188447, 0.070796679, 1.393892288, 
0.447486223, 0.059898949, 1.333993367, 0.003421558, 0.020280698, 
-0.044788628, 0.086701809), NB = c(1.79361422, 0.23087077, 2.34315343, 
0.8995402, 0.16849883, 2.17465466, -0.30522065, -0.43764352, 
-0.64518845, 0.07564453), ME = c(1.6936173, 0.1307856, 2.0172089, 
0.7113195, 0.1135671, 1.9036418, -0.9033899, -0.7945115, -0.8507709, 
0.1036442), IC = c(2.28296799, 0.14749662, 2.51693005, 0.89241081, 
0.13475936, 2.38217072, 0.48013856, 0.59088701, 0.60322486, 0.05169639
), FI = c(0.55358516, 0.05694769, 0.75707975, 0.20722915, 0.04236526, 
0.71471448, 0.42658058, -0.01849223, -0.22192967, 0.08643648), 
    name = c("Present.Surface.Chlorophyll.Lt.max", "Present.Surface.Chlorophyll.Lt.min", 
    "Present.Surface.Chlorophyll.Max", "Present.Surface.Chlorophyll.Mean", 
    "Present.Surface.Chlorophyll.Min", "Present.Surface.Chlorophyll.Range", 
    "Present.Surface.Cloud.cover.Max", "Present.Surface.Cloud.cover.Mean", 
    "Present.Surface.Cloud.cover.Min", "Present.Surface.Current.Velocity.Lt.max"
    )), class = "data.frame", row.names = c("1", "2", "3", "4", 
"5", "6", "7", "8", "9", "10"))
akrun
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  • Thanks for your reply! Is there a way to group the data instead of listing it out individually? I ask this because my actual dataset is much larger than this. – Daniel.Payter Feb 27 '20 at 18:23
  • @Daniel.Payter not clear about that grouping condition. I was looking at your 'Chla' etc., but was not sure about the logic you used in grouping – akrun Feb 27 '20 at 18:25
  • @Daniel.Payter i did a `filter` step in between as it is not clear – akrun Feb 27 '20 at 19:04
  • @Danile.Payter i see an edit on my post. Can you please clarify why you removed the data – akrun Apr 24 '20 at 02:19
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I think you can use the the pivot_wider and pivot_longer functions from the tidyverse: https://tidyr.tidyverse.org/articles/pivot.html

Orlando Sabogal
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