# Organizing big dataframe - move values according to line and column

Hi !

I am trying to organise gigantic tables and get kinda stuck.

I have a dataframe such as :

v1 <- c('D7','X',23)
v2 <- c('D7','Y',56)
v3 <- c('D7','Z',84)
v4 <- c('D8','X',11)
v5 <- c('D8','Y',12)
v6 <- c('D8','Z',35)
book <- data.frame(v1,v2,v3,v4,v5,v6)

and I have the uniqued values of column 1:

lvl <- unique(book[,1])

> lvl
[1] "D7" "D8"

I am able to creat a matrix with the levels (D7, D8 here)

I want to add X, Y and Z as columns, and the values in the matching lines.

I guess I'll need to use some homemade functions, but I'll definitly need help to get started.

Thank you so much!

D

The data frame you define does not give the values of lvl that you show. In the code below, I demonstrate that and I take a guess at what you did mean to do. Does that help?

v1 <- c('D7','X',23)
v2 <- c('D7','Y',56)
v3 <- c('D7','Z',84)
v4 <- c('D8','X',11)
v5 <- c('D8','Y',12)
v6 <- c('D8','Z',35)
book <- data.frame(v1,v2,v3,v4,v5,v6)
lvl <- unique(book[,1])
#The values of lvl do not match what you show
lvl
#> [1] "D7" "X"  "23"

#Is this what you intended to have as the initial data?
book2 <- as.data.frame(t(book))
book2
#>    V1 V2 V3
#> v1 D7  X 23
#> v2 D7  Y 56
#> v3 D7  Z 84
#> v4 D8  X 11
#> v5 D8  Y 12
#> v6 D8  Z 35

#Does this give you the result you want?
library(tidyr)
book2_wide <- pivot_wider(book2, names_from = V2, values_from = V3)
book2_wide
#> # A tibble: 2 × 4
#>   V1    X     Y     Z
#>   <chr> <chr> <chr> <chr>
#> 1 D7    23    56    84
#> 2 D8    11    12    35

Created on 2023-01-05 with reprex v2.0.2

Thank you!
I obtained the levels from a list that extracted only the first column, but it really does not matter, I think your method works, great thanks!

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