Excel BI - Excel Challenge 813

🔰 Generate X and Y axes of all 4 quadrants for value given in A1.

Illustration for Excel BI - Excel Challenge 813

Challenge Description

🔰 Generate X and Y axes of all 4 quadrants for value given in A1. Example shown is for value 4 & 5.

Solutions

R Solution

size = 5
M = matrix(NA_integer_, 2*size + 1, 2*size + 1)
M[size + 1, ] = c(-size:-1, 0, 1:size)
M[, size + 1] = c(size:1, 0, -1:-size)
idx = which(is.na(M), arr.ind = TRUE)
M[idx] = ifelse(idx[,1] + idx[,2] == size + 1 | idx[,1] - idx[,2] == size + 1, -size,
         ifelse(idx[,1] + idx[,2] == 3 * (size + 1) | idx[,2] - idx[,1] == size + 1, size, NA))
M

R Analysis

• Logic: Apply the business rule conditions explicitly.
• Strengths: The code maps the workbook rule into a compact, reproducible pipeline.
• Areas for Improvement: The approach is compact, but it depends on the workbook following the same input structure as the supplied challenge file.
• Gem: The elegant part is how little code is needed once the correct intermediate representation is chosen.

Python Solution

import numpy as np

size = 8
M = np.full((2 * size + 1, 2 * size + 1), np.nan, dtype=float)

M[size, :] = np.arange(-size, size + 1)
M[:, size] = np.concatenate((np.arange(size, 0, -1), [0], np.arange(-1, -size - 1, -1)))

idx = np.argwhere(np.isnan(M))

for i, j in idx:
    if i + j == size or i - j == size:
        M[i, j] = -size
    elif i + j == 3 * size or j - i == size:
        M[i, j] = size

print(M)

Python

The Python version keeps the algorithm explicit, which helps when the challenge depends on a greedy or iterative rule.

Difficulty Level

Easy / Medium

The business rule is clear, though the workbook still needs a few transformation steps to reach the expected output.

Related Challenges

• Excel Challenge 814
• Excel Challenge 815
• Excel Challenge 816