Vigenere Cypher Grid

Numbers around us
Numbers around us
Published in
2 min readOct 12, 2023

Excel BI’s Excel Challenge #302— solved in R

Introduction

Today’s Excel BI puzzle is available here. It is pure generational work today. We have to create from scratch so called Vigenere grid. Exercise file today is purely for comparison reason: file.

Defining the Puzzle

The puzzle in question revolves around the Vigenere Cipher Grid, a cryptographic tool. The objective is to generate this grid, which appears to be a matrix of letters shifted in various ways.

Loading data from Excel

As I already mention we need test data only today.

library(tidyverse)
library(readxl)

test = read_excel(“Vigenere Cipher Grid.xlsx”, range = “A2:AA28”)
%>% column_to_rownames(‘…1’)

Tidyverse Approach

df <- tibble(base = LETTERS)

vigenere_grid <- bind_cols(df, map_dfc(0:24, ~ {
shifted <- LETTERS[(seq_along(LETTERS) + .x) %% 26 + 1]
tibble(!!LETTERS[.x + 1] := shifted)
}))

rownames(vigenere_grid) <- LETTERS
colnames(vigenere_grid) <- LETTERS

vigenere_grid = as.data.frame(vigenere_grid)

Base R Approach

vigenere_grid_base <- matrix(NA, 26, 26)
rownames(vigenere_grid_base) <- LETTERS
colnames(vigenere_grid_base) <- LETTERS

for (i in 1:26) {
vigenere_grid_base[i,] <- LETTERS[(seq_along(LETTERS) + (i — 2)) %% 26 + 1]
}

vigenere_grid_base = as.data.frame(vigenere_grid_base)

Data.table Approach

library(data.table)

vigenere_grid_dt <- data.table(base = LETTERS)

for (i in 0:24) {
shifted <- LETTERS[(seq_along(LETTERS) + i) %% 26 + 1]
vigenere_grid_dt[, LETTERS[i + 1] := shifted]
}

setDT(vigenere_grid_dt)[, LETTERS := LETTERS]

vigenere_grid_dt = as.data.frame(vigenere_grid_dt) %>%
column_to_rownames(“LETTERS”)

colnames(vigenere_grid_dt) <- LETTERS

Validating Solutions

identical(vigenere_grid, test)
# [1] TRUE

identical(vigenere_grid_base, test)
# [1] TRUE

identical(vigenere_grid_dt, test)
# [1] TRUE

Tips for possible optimization

Approach 1: Tidyverse with purrr

  1. Avoiding Repetitive Operations
  2. Vectorize

Approach 2: Base R

  1. Vectorize
  2. Avoid Growing Objects

Approach 3: Data.table

  1. Use .SD and .SDcols
  2. Use set Function
  3. Avoid Copying

Thank you for taking the time to explore these methodologies with me! I’d love to hear your thoughts on the puzzle, the solutions provided, or any optimizations you might have in mind. Feel free to share your solutions and insights!

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Numbers around us
Numbers around us

Self developed analyst. BI Developer, R programmer. Delivers what you need, not what you asked for.