library(tidyverse)
library(readxl)
path <- "Excel/800-899/881/881 Completion of Words.xlsx"
input <- read_excel(path, range = "A1:B38")
test <- read_excel(path, range = "C1:C38")
is_subsequence <- function(s, l) {
purrr::map2_lgl(s, l, function(s1, l1) {
pat <- str_c(str_split(s1, "", simplify = TRUE), collapse = ".*")
str_detect(l1, pat)
})
}
result = input %>%
mutate(`Answer Expected` = is_subsequence(`Inout Word`, `Target Word`))
all.equal(result$`Answer Expected`, test$`Answer Expected`)
# [1] TRUEExcel BI - Excel Challenge 881
excel-challenges
excel-formulas
🔰 Inout Word Target Word Answer Expected docu documentation doto tent dcmd butl beautiful

Challenge Description
🔰 Inout Word Target Word Answer Expected docu documentation doto tent dcmd butl beautiful
Solutions
- Logic: Read the workbook ranges needed for the challenge; Derive the required intermediate columns; Parse the packed text or string structure.
- Strengths: The code maps the workbook rule into a compact, reproducible pipeline.
- Areas for Improvement: The solution assumes the workbook layout and selected ranges remain stable, so any structural change in the sheet would require small adjustments.
- Gem: The elegant part is how little code is needed once the correct intermediate representation is chosen.
import pandas as pd
import re
path = "Excel\\800-899\\881\\881 Completion of Words.xlsx"
input = pd.read_excel(path, usecols="A:B", nrows = 37)
test = pd.read_excel(path, usecols="C", nrows = 37)
def is_subsequence(short, long):
return bool(re.search(".*".join(map(re.escape, short)), long))
result = input.apply(
lambda row: is_subsequence(row['Inout Word'], row['Target Word']),
axis=1
)
print(result.equals(test['Answer Expected'])) # TrueThe Python version expresses the core extraction rule directly and keeps the pattern matching easy to review.
Difficulty Level
Easy / Medium
The business rule is clear, though the workbook still needs a few transformation steps to reach the expected output.