regextable

Introduction

regextable extracts regex-based pattern matches from a data frame or character vector using a pattern lookup table. For each input row, all matching patterns are returned, along with the matched substring, an internal row identifier, and additional columns specified in data_return_cols and regex_return_cols. Optional metadata from the pattern table can also be included. Multiple rows may be returned for a single text if it matches multiple patterns.

Install and load the package:

library(regextable)
library(kableExtra)

Data

For demonstration, we use two included datasets:

• members: A lookup table of regex patterns for member names.
• cr2007_03_01: A sample text dataset to search.

data("members")
kable(members)

data("cr2007_03_01")
kable(subset(cr2007_03_01, select = -c(url, url_txt)))

text <- "  HELLO---WORLD  "
clean_text(text)
#> [1] "hello world"

Basic Extraction

The simplest use of extract():

result <- extract(
  data = cr2007_03_01,
  regex_table = members,
  data_return_cols = c("text"),
  regex_return_cols = c("icpsr")
)

kable(head(result))

Explanation: - data: the text dataset to search. - col_name: which column contains the text. - regex_table: the lookup table of patterns. - data_return_cols: additional columns from data to include in the result. - regex_return_cols: additional columns from the pattern table to attach. Each row in the output corresponds to a detected match, and includes both the original text and the matching pattern. —

Advanced Usage

extract() can also filter data by date, remove acronyms (all-uppercase patterns with 2+ characters), and select specific output columns. This is useful for more controlled extraction.

Explanation: - date_col, date_start, date_end: filter rows by date. - remove_acronyms: skip patterns like “NASA” or “USA”. You can combine these filters with any subset of columns for flexible outputs. —

library(parallel)
clust <- makeCluster(2)
result_parallel <- extract(
  data = cr2007_03_01,
  regex_table = members,
  cl = clust,
  data_return_cols = c("text"),
  regex_return_cols = c("icpsr")
)
stopCluster(clust)
head(result_parallel)