library(tidyverse)
library(readxl)
path = "Excel/700-799/729/729 Extract Text Between Delimiters.xlsx"
input = read_excel(path, range = "A1:A10")
test = read_excel(path, range = "B1:B10") %>%
replace_na(list(`Answer Expected` = ""))
result = input %>%
rowwise() %>%
mutate(
`Answer Expected` = list(str_match_all(Text, "(?<=~)\\w+(?=~)")[[1]]) %>%
unlist() %>%
paste(collapse = ", ")
)
all.equal(result$`Answer Expected`, test$`Answer Expected`)
#> TRUEExcel BI - Excel Challenge 729
excel-challenges
excel-formulas
π° Extract texts between delimiter ~ (tilde) only if it is a single word.

Challenge Description
π° Extract texts between delimiter ~ (tilde) only if it is a single word. Hence, if text extracted is βhail Maryβ, then this should not be extracted as this is not a single word.
Solutions
- Logic: Read the workbook ranges needed for the challenge; Derive the required intermediate columns.
- 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 = "700-799/729/729 Extract Text Between Delimiters.xlsx"
input_df = pd.read_excel(path, usecols="A", nrows=10)
test_df = pd.read_excel(path, usecols="B", nrows=10).fillna({"Answer Expected": ""})
input_df["Answer Expected"] = input_df.iloc[:,0].astype(str).apply(lambda x: ", ".join(re.findall(r"(?<=~)\w+(?=~)", x)))
print(input_df["Answer Expected"].equals(test_df["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.