12  Text Manipulation

Besides default R functionality (paste(), nchar(), substr() …) , there is one contributed package to deal with character data, which is more user friendly and intuitive: stringr package.

Strings can be arranged into vectors and matrices just like numbers. We can also paste strings together using paste(..., sep). Here sep is an optional input, with default value ” “, that determines which padding character is to be placed between the strings (which are input where … appears).

Example:

x <- "Citroen SM"
y <- "Jaguar XK150"
z <- "Ford Falcon GT-HO"
(wish.list <- paste(x, y, z, sep = ", "))
[1] "Citroen SM, Jaguar XK150, Ford Falcon GT-HO"

Special characters can be included in strings using the escape character \:

str_c() is very similar to the base paste0(), but is designed to be used with mutate() by obeying the usual tidyverse rules for recycling and propagating missing values:

Example:

df <- tibble(name = c("Flora", "David", "Terra", NA))
df |> mutate(greeting = str_c("Hi ", name, "!"))
# A tibble: 4 × 2
  name  greeting 
  <chr> <chr>    
1 Flora Hi Flora!
2 David Hi David!
3 Terra Hi Terra!
4 <NA>  <NA>

Text data can be used to retrieve information in sentiment analysis and even entity recognition.

12.1 Sources of Text Data

Text data can be found on tweets from any individual, or from any company, Facebook status updates, RSS feeds from any news site, Blog articles, Journal articles, Newspapers, Verbatim transcripts of an in-depth interview.

For example, t extract Twitter data, we can use tweetR() and, to extract data from Facebook, we could use facebookR().

12.2 Getting Text Data

The easiest way to get text data is to import from a .csv file where some of the variables contain character data. We have to protect automatic factor conversion by specifying the stringsAsFactors = FALSE argument

Example 1: The tweets.txt file is the plain text file. We will import this file using the generic readLines() function. It is a vector of characters (not a data.frame).

Example 2: Html (this is also a character string):

conURL <- "http://en.wikipedia.org/wiki/R_%28programming_language%29"
# Establish the connection with the URL 
link2URL <- url(conURL) 
# Reading html code
htmlCode <- readLines(link2URL)
# Closing the connection
close(link2URL)
# Printing the result 
htmlCode

The tm text mining library has some other functions to import text data from various files such as PDF files, plain text files, and even from doc files.