library(tidyverse)
library(readxl)
path = "files/300-399/315/CH-315 Consecutive numbers.xlsx"
input = read_excel(path, range = "B1:B14")
test = read_excel(path, range = "E1:E4")
result = as_tibble(embed(input$Question, 3)[,3:1]) %>%
filter(V2 - V1 == 1, V3 - V2 == 1) %>%
unite("Result", V1:V3, sep = ".")
print(result)Omid - Challenge 315
data-challenges
advanced-exercises
🔰 Identify and extract all subsequences of 3 or more consecutive numbers.

Challenge Description
🔰 Identify and extract all subsequences of 3 or more consecutive numbers.
Solutions
Logic:
- Reads the workbook ranges needed for the challenge
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
path = "300-399/315/CH-315 Consecutive numbers.xlsx"
numbers = pd.read_excel(path, usecols="B", nrows=14).iloc[:, 0].values
result = pd.DataFrame(
[(a, b, c) for a, b, c in zip(numbers, numbers[1:], numbers[2:]) if c - a == 2],
columns=['V1', 'V2', 'V3']
)
result['Result'] = result.apply(lambda r: f"{r.V1}.{r.V2}.{r.V3}", axis=1)
print(result[['Result']])Logic:
Reads the workbook ranges needed for the challenge
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.