Omid - Challenge 278

data-challenges
advanced-exercises
🔰 CHallenge 278 - Pattern Recognition For each row in the table, count the number of times the sign changes consecutively, from positive to negative or negative to positiv…
Published

March 24, 2026

Illustration for Omid - Challenge 278

Challenge Description

🔰 CHallenge 278 - Pattern Recognition For each row in the table, count the number of times the sign changes consecutively, from positive to negative or negative to positiv…

Solutions

library(tidyverse)
library(readxl)
library(charcuterie)

path = "files/200-299/278/CH-278 Pattern Recognition.xlsx"
input = read_excel(path, range = "B2:C7")
test  = read_excel(path, range = "D2:D7")

result = input %>%
  mutate(`Pattern Length` = map_int(Pattern, \(x) length(rle(strsplit(x, "")[[1]])$lengths) - 1))

all.equal(result$`Pattern Length`, test$`Pattern Length`) 
# > [1] TRUE

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Builds the intermediate columns that drive the final result

  • Strengths:

    • The R solution stays close to the workbook rule and keeps the transformation compact.

  • Areas for Improvement:

    • The code assumes the sheet structure and source ranges remain stable.

  • Gem:

    • The strongest part of the solution is choosing the right intermediate representation before shaping the final output.
import pandas as pd
from itertools import groupby

path = "200-299/278/CH-278 Pattern Recognition.xlsx"
input = pd.read_excel(path, usecols="B:C", nrows=6, skiprows=1)
test = pd.read_excel(path, usecols="D", nrows=6, skiprows=1)

input['Pattern Length'] = input['Pattern'].apply(lambda s: len([k for k,_ in groupby(s)]) - 1)

print(input["Pattern Length"].equals(test['Pattern Length'])) # True

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Aggregates or ranks values at the relevant grouping level

    • Applies the rule iteratively until the output stabilizes

  • Strengths:

    • The Python version follows the same rule in a direct dataframe-oriented implementation.

  • Areas for Improvement:

    • The code assumes the workbook layout remains stable, so any sheet redesign would require small adjustments.

  • Gem:

    • The implementation stays close to the original workbook rule instead of adding unnecessary abstraction.

Difficulty Level

This task is moderate:

  • The business rule is readable, but the workbook still requires careful implementation to reach the expected layout.