Omid - Challenge 295

data-challenges
advanced-exercises
🔰 : Consecutive Character Matching!
Published

March 24, 2026

Illustration for Omid - Challenge 295

Challenge Description

🔰 : Consecutive Character Matching!

Solutions

library(tidyverse)
library(readxl)

path = "files/200-299/295/CH-295 Text Matching.xlsx"
input = read_excel(path, range = "B2:B9")
test  = read_excel(path, range = "D2:E9")

get_substrings <- function(id, min_length = 3, max_length = NULL) {
  id1 = unlist(strsplit(id, ""))
  n = length(id1)
  if (is.null(max_length)) max_length = n
  purrr::flatten_chr(
    purrr::map(min_length:min(max_length, n), function(len) {
      purrr::map_chr(1:(n - len + 1), function(start) {
        paste(id1[start:(start + len - 1)], collapse = "")
      })
    })
  )
}

result = expand.grid(`ID 1` = input$ID, `ID 2` = input$ID) %>%
  mutate_all(as.character) %>%
  filter(`ID 1` != `ID 2`,`ID 1` < `ID 2`) %>%
  rowwise() %>%
  mutate(substrings = list(get_substrings(`ID 1`))) %>%
  unnest(substrings) %>%
  ungroup() %>%
  filter(str_detect(`ID 2`, substrings))

# # A tibble: 10 × 3
# `ID 1`      `ID 2`   substrings
# <chr>       <chr>    <chr>     
# 1 MA-210      MX-21551 -21       
# 2 MX-21551    MX-21F   MX-       
# 3 MX-21551    MX-21F   X-2       
# 4 MX-21551    MX-21F   -21       
# 5 MA-210      MX-21F   -21       
# 6 MX-21551    MX-M5512 MX-       
# 7 MX-21551    MX-M5512 551       
# 8 MX-21F      MX-M5512 MX-       
# 9 FF-512      MX-M5512 512       
# 10 BN-8213F2  RF_821   821       


r2 = result %>%
  select(-substrings) %>%
  distinct()

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Builds the intermediate columns that drive the final result

    • Parses the text patterns directly instead of relying on manual cleanup

  • 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
input = pd.read_excel("200-299/295/CH-295 Text Matching.xlsx", usecols="B", skiprows=1, nrows=8)

ids = input['ID'].astype(str).tolist()
def subs(s): return [s[i:j] for i in range(len(s)) for j in range(i+3, len(s)+1)]
result = pd.DataFrame([
    {'ID 1': a, 'ID 2': b, 'substrings': sub}
    for i, a in enumerate(ids) for j, b in enumerate(ids)
    if a != b and a < b
    for sub in subs(a) if sub in b
])

print(result)

# r2: distinct id1/id2 pairs where a substring match exists
r2 = result[['ID 1', 'ID 2']].drop_duplicates().reset_index(drop=True)
print(r2)

#          ID 1      ID 2 substrings
# 0    MX-21551    MX-21F        MX-
# 1    MX-21551    MX-21F       MX-2
# 2    MX-21551    MX-21F      MX-21
# 3    MX-21551    MX-21F        X-2
# 4    MX-21551    MX-21F       X-21
# 5    MX-21551    MX-21F        -21
# 6    MX-21551  MX-M5512        MX-
# 7    MX-21551  MX-M5512        551
# 8      MX-21F  MX-M5512        MX-
# 9   BN-8213F2    RF_821        821
# 10     MA-210  MX-21551        -21
# 11     MA-210    MX-21F        -21
# 12     FF-512  MX-M5512        512

# r2: distinct id1/id2 pairs where a substring match exists
r2 = result[['ID 1', 'ID 2']].drop_duplicates().reset_index(drop=True)
print(r2)

#          ID 1      ID 2
# 0    MX-21551    MX-21F
# 1    MX-21551  MX-M5512
# 2      MX-21F  MX-M5512
# 3   BN-8213F2    RF_821
# 4     MA-210   MX-21551
# 5     MA-210     MX-21F
# 6     FF-512   MX-M5512

  • 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 core logic is clear, but the correct transformation pattern is not obvious from the raw input.

  • The challenge combines multiple reshaping, grouping, or parsing steps.