Return String Pattern Match Plus Text Before and After Pattern

Introduction

In this article, we will explore how to extract a specific pattern from a text while including context before and after the pattern. We will use R programming language with the tidyverse package for data manipulation and the stringr package for string operations.

Problem Statement

Suppose you have diary entries from 5 people and you want to determine if they mention any food-related key words. You want an output of the key word with a window of one word before and after to provide context before determining if they are food-related.

For example, if a key word is “rice”, you want to output to include “price”. The search should be case-insensitive, and it’s ok if the key word is embedded in another word.

Solution Overview

The solution involves the following steps:

Split each phrase into its individual words.
Use regular expressions to extract the specified pattern from each word.
Include context before and after the pattern by finding the maximum and minimum word indices for the pattern.
Filter out empty strings and group the results by ID.

Function Implementation

We will implement a function extract3 that takes two arguments: txt (the input text) and word (the pattern to extract). This function will perform the following operations:

Split the input text into individual words using \W as the delimiter.
Use regular expressions to extract the specified pattern from each word, ignoring case.
Find the maximum and minimum word indices for the pattern.
Create a list of words within the context window (i.e., one word before and after the pattern).
Join these words into a single string with commas as separators.

Code Implementation

library(tidyverse)

extract3 <- function(txt, word) {
  # Split text into individual words
  str_split(txt, "\\W") %>% 
    unlist() %>% 
    {. -&gt;&gt; w} %>%
  
  # Extract pattern from each word using regular expressions
  map(~ str_extract(.x, regex(paste0("(.)*", word, "(.)*"), ignore_case = T))) %>%
  
  # Find maximum and minimum word indices for the pattern
  unlist() %>% 
    is.na() %&gt;% 
    `!` %&gt;% 
    which() %&gt;% 
    map_chr(~ paste(
      w[unique(c(max(c(.x-1, 1)), .x, min(c(.x+1, length(w))))), collapse = " ")) %>%
  
  # Join words into a single string with commas as separators
  paste(collapse = ", ")
}

# Create sample data frame
foods <- c("corn", "hot dog", "ham", "rice")
df <- tibble(
  id = 1:5,
  diary = c("I ate rice and corn today", "Sue ate my corn.", "He just hammed it up",
            "Corny jokes are my fave", "What is the price of milk")
)

# Apply extract3 function to each row
df_out <- tibble()
for (i in 1:nrow(df)) {
  for (j in 1:length(foods)) {
    df_out <- rbind(df_out,
                  tibble(
                    id = df$id[i],
                    diary = df$diary[i],
                    output = extract3(df$diary[i], foods[j])
                  ))
}

# Filter out empty strings and group results by ID
df_out %>% 
  filter(output != "") %>% 
  group_by(id) %>% 
  mutate(output = paste(output, collapse = ", ")) %>% 
  ungroup() %>% 
  distinct()

Output

The output of the extract3 function will be a list of strings, each containing a food-related key word with context before and after it. The final code snippet filters out empty strings and groups the results by ID to produce the desired output.

Example Use Case

Suppose you have a diary entry from person A that reads: “I ate rice and corn today”. You want to extract the words “rice” and “corn” with context before and after them. The extract3 function will return:

"ate rice and" (with 1 word before “rice”)
"and corn" (with no context, as it’s at the end of the sentence)
"I ate corn" (with 1 word before “corn”)

This output provides context for each food-related key word, allowing you to better understand the mention of these words in the diary entry.

Conclusion

In this article, we explored how to extract a specific pattern from a text while including context before and after the pattern. We implemented a function extract3 using regular expressions and string operations, which takes two arguments: input text and a pattern to extract. The output of this function is a list of strings containing food-related key words with context before and after them.

Last modified on 2023-08-17