Before we can analyze a text in R, we first need to get its digital representation, a sequence of ones and zeros. In practice this works by first choosing an encoding for the text that assigns each character a numerical value, and then translating the sequence of characters in the text to the corresponding sequence of numbers specified by the encoding. Today, most new text is encoded according to the Unicode standard, specifically the 8-bit block Unicode Transfer Format, UTF-8. Joel Spolsky gives a good overview of the situation in an essay from 2003.
The software community has mostly moved to UTF-8 as a standard for text storage and interchange, but there is still a large volume of text in other encodings. Whenever you read a text file into R, you need to specify the encoding. If you don’t, R will try to guess the encoding, and if it guesses incorrectly, it will wrongly interpret the sequence of ones and zeros.
We will demonstrate the difficulties of encodings with the text of Jane Austen’s novel, Mansfield Park provided by Project Gutenberg. We will download the text, then read in the lines of the novel.
# download the zipped text from a Project Gutenberg mirror
url <- "http://mirror.csclub.uwaterloo.ca/gutenberg/1/4/141/141.zip"
tmp <- tempfile()
download.file(url, tmp)
# read the text from the zip file
con <- unz(tmp, "141.txt", encoding = "UTF-8")
lines <- readLines(con)
close(con)The unz function and other similar file connection
functions have encoding arguments which, if left
unspecified default to assuming that text is encoded in your operating
system’s native encoding. To ensure consistent behavior across all
platforms (Mac, Windows, and Linux), you should set this option
explicitly. Here, we set encoding = "UTF-8". This is a
reasonable default, but it is not always appropriate. In general, you
should determine the appropriate encoding value by looking
at the file. Unfortunately, the file extension ".txt" is
not informative, and could correspond to any encoding. However, if we
read the first few lines of the file, we see the following:
lines[11:20] [1] "Author: Jane Austen"
[2] ""
[3] "Release Date: June, 1994 [Etext #141]"
[4] "Posting Date: February 11, 2015"
[5] ""
[6] "Language: English"
[7] ""
[8] "Character set encoding: ASCII"
[9] ""
[10] "*** START OF THIS PROJECT GUTENBERG EBOOK MANSFIELD PARK ***"The character set encoding is reported as ASCII, which is a subset of UTF-8. So, we should be in good shape.
Unfortunately, we run into trouble as soon as we try to process the text:
corpus::term_stats(lines) # produces an errorError in corpus::term_stats(lines): argument entry 15252 is incorrectly marked as "UTF-8": invalid leading byte (0xA3) at position 36The error message tells us that line 15252 contains an invalid byte.
lines[15252][1] "the command of her beauty, and her \xa320,000, any one who could satisfy the"We might wonder if there are other lines with invalid data. We can
find all such lines using the utf8_valid function:
lines[!utf8_valid(lines)][1] "the command of her beauty, and her \xa320,000, any one who could satisfy the"So, there are no other invalid lines.
The offending byte in line 15252 is displayed as \xa3,
an escape code for hexadecimal value 0xa3, decimal value 163. To
understand why this is invalid, we need to learn more about UTF-8
encoding.
The smallest unit of data transfer on modern computers is the byte, a sequence of eight ones and zeros that can encode a number between 0 and 255 (hexadecimal 0x00 and 0xff). In the earliest character encodings, the numbers from 0 to 127 (hexadecimal 0x00 to 0x7f) were standardized in an encoding known as ASCII, the American Standard Code for Information Interchange. Here are the characters corresponding to these codes:
codes <- matrix(0:127, 8, 16, byrow = TRUE,
dimnames = list(0:7, c(0:9, letters[1:6])))
ascii <- apply(codes, c(1, 2), intToUtf8)
# replace control codes with ""
ascii["0", c(0:6, "e", "f")] <- ""
ascii["1",] <- ""
ascii["7", "f"] <- ""
utf8_print(ascii, quote = FALSE) 0 1 2 3 4 5 6 7 8 9 a b c d e f
0 \a \b \t \n \v \f \r
1
2 ! " # $ % & ' ( ) * + , - . /
3 0 1 2 3 4 5 6 7 8 9 : ; < = > ?
4 @ A B C D E F G H I J K L M N O
5 P Q R S T U V W X Y Z [ \\ ] ^ _
6 ` a b c d e f g h i j k l m n o
7 p q r s t u v w x y z { | } ~ The first 32 codes (the first two rows of the table) are special
control codes, the most common of which, 0x0a denotes a new
line (\n). The special code 0x00 often denotes
the end of the input, and R does not allow this value in character
strings. Code 0x7f corresponds to a “delete” control.
When you call utf8_print, it uses the low level
utf8_encode subroutine format control codes; they format as
\uXXXX for four hexadecimal digits XXXX or as
\UXXXXYYYY for eight hexadecimal digits
XXXXYYYY:
utf8_print(intToUtf8(1:0x0f), quote = FALSE)[1] \u0001\u0002\u0003\u0004\u0005\u0006\a\b\t\n\v\f\r\u000e\u000fCompare utf8_print output with the output with the base
R print function:
[1] \001\002\003\004\005\006\a\b\t\n\v\f\r\016\017Base R format control codes below 128 using octal escapes. There are some other differences between the function which we will highlight below.
ASCII works fine for most text in English, but not for other languages. The Latin-1 encoding extends ASCII to Latin languages by assigning the numbers 128 to 255 (hexadecimal 0x80 to 0xff) to other common characters in Latin languages. We can see these characters below.
codes <- matrix(128:255, 8, 16, byrow = TRUE,
dimnames = list(c(8:9, letters[1:6]), c(0:9, letters[1:6])))
latin1 <- apply(codes, c(1, 2), intToUtf8)
# replace control codes with ""
latin1[c("8", "9"),] <- ""
utf8_print(latin1, quote = FALSE) 0 1 2 3 4 5 6 7 8 9 a b c d e f
8
9
a ¡ ¢ £ ¤ ¥ ¦ § ¨ © ª « ¬ ® ¯
b ° ± ² ³ ´ µ ¶ · ¸ ¹ º » ¼ ½ ¾ ¿
c À Á Â Ã Ä Å Æ Ç È É Ê Ë Ì Í Î Ï
d Ð Ñ Ò Ó Ô Õ Ö × Ø Ù Ú Û Ü Ý Þ ß
e à á â ã ä å æ ç è é ê ë ì í î ï
f ð ñ ò ó ô õ ö ÷ ø ù ú û ü ý þ ÿAs with ASCII, the first 32 numbers are control codes. The others are
characters common in Latin languages. Note that 0xa3, the
invalid byte from Mansfield Park, corresponds to a pound sign
in the Latin-1 encoding. Given the context of the byte:
lines[15252][1] "the command of her beauty, and her \xa320,000, any one who could satisfy the"this is probably the right symbol. The text is probably encoded in Latin-1, not UTF-8 or ASCII as claimed in the file.
If you run into an error while reading text that claims to be ASCII,
it is probably encoded as Latin-1. Note, however, that this is not the
only possibility, and there are many other encodings. The
iconvlist function will list the ones that R knows how to
process:
[1] "437" "850" "852" "855"
[5] "857" "860" "861" "862"
[9] "863" "865" "866" "869"
[13] "ANSI_X3.4-1968" "ANSI_X3.4-1986" "ARABIC" "ARMSCII-8"
[17] "ASCII" "ASMO-708" "ATARI" "ATARIST" With only 256 unique values, a single byte is not enough to encode every character. Multi-byte encodings allow for encoding more. UTF-8 encodes characters using between 1 and 4 bytes each and allows for up to 1,112,064 character codes. Most of these codes are currently unassigned, but every year the Unicode consortium meets and adds new characters. You can find a list of all of the characters in the Unicode Character Database. A listing of the Emoji characters is available separately.
Say you want to input the Unicode character with hexadecimal code 0x2603. You can do so in one of three ways:
"\u2603" # with \u + 4 hex digits[1] "☃"
"\U00002603" # with \U + 8 hex digits[1] "☃"
intToUtf8(0x2603) # from an integer[1] "☃"For characters above 0xffff, the first method won’t
work. On Windows, a bug in the current version of R (fixed in R-devel)
prevents using the second method.
When you try to print Unicode in R, the system will first try to
determine whether the code is printable or not. Non-printable codes
include control codes and unassigned codes. On Mac OS, R uses an
outdated function to make this determination, so it is unable to print
most emoji. The utf8_print function uses the most recent
version (10.0.0) of the Unicode standard, and will print all Unicode
characters supported by your system:
[1] "\U0001f600\U0001f601\U0001f602\U0001f603\U0001f604\U0001f605\U0001f606\U0001f607\U0001f608\U0001f609\U0001f60a\U0001f60b\U0001f60c\U0001f60d\U0001f60e\U0001f60f\U0001f610\U0001f611\U0001f612\U0001f613\U0001f614\U0001f615\U0001f616\U0001f617\U0001f618\U0001f619\U0001f61a\U0001f61b\U0001f61c\U0001f61d\U0001f61e\U0001f61f\U0001f620\U0001f621\U0001f622\U0001f623\U0001f624\U0001f625\U0001f626\U0001f627\U0001f628\U0001f629\U0001f62a\U0001f62b\U0001f62c\U0001f62d\U0001f62e\U0001f62f\U0001f630\U0001f631\U0001f632\U0001f633\U0001f634\U0001f635\U0001f636\U0001f637\U0001f638\U0001f639\U0001f63a\U0001f63b\U0001f63c\U0001f63d\U0001f63e\U0001f63f\U0001f640\U0001f641\U0001f642\U0001f643\U0001f644\U0001f645\U0001f646\U0001f647\U0001f648\U0001f649\U0001f64a\U0001f64b\U0001f64c\U0001f64d\U0001f64e\U0001f64f"
utf8_print(intToUtf8(0x1f600 + 0:79)) # truncates to line width[1] "😀😁😂😃😄😅😆😇😈😉😊😋😌😍😎😏😐😑😒😓😔😕😖😗😘😙😚😛😜😝😞😟😠😡😢😣…"
utf8_print(intToUtf8(0x1f600 + 0:79), chars = 500) # increase character limit[1] "😀😁😂😃😄😅😆😇😈😉😊😋😌😍😎😏😐😑😒😓😔😕😖😗😘😙😚😛😜😝😞😟😠😡😢😣😤😥😦😧😨😩😪😫😬😭😮😯😰😱😲😳😴😵😶😷😸😹😺😻😼😽😾😿🙀🙁🙂🙃🙄🙅🙆🙇🙈🙉🙊🙋🙌🙍🙎🙏"(Characters with codes above 0xffff, including most emoji, are not supported on Windows.)
The utf8 package provides the following utilities for validating, formatting, and printing UTF-8 characters:
as_utf8() attempts to convert character data to
UTF-8, throwing an error if the data is invalid;
utf8_valid() tests whether character data is valid
according to its declared encoding;
utf8_normalize() converts text to Unicode composed
normal form (NFC), optionally applying case-folding and compatibility
maps;
utf8_encode() encodes a character string, escaping
all control characters, so that it can be safely printed to the
screen;
utf8_format() formats a character vector by
truncating to a specified character width limit or by left, right, or
center justifying;
utf8_print() prints UTF-8 character data to the
screen;
utf8_width() measures the display with of UTF-8
character strings (many emoji and East Asian characters are twice as
wide as other characters).
The package does not provide a method to translate from another
encoding to UTF-8 as the iconv() function from base R
already serves this purpose.
Back to our original problem: getting the text of Mansfield Park into R. Our first attempt failed:
corpus::term_stats(lines)Error in corpus::term_stats(lines): argument entry 15252 is incorrectly marked as "UTF-8": invalid leading byte (0xA3) at position 36We discovered a problem on line 15252:
lines[15252][1] "the command of her beauty, and her \xa320,000, any one who could satisfy the"The text is likely encoded in Latin-1, not UTF-8 (or ASCII) as we had
originally thought. We can test this by attempting to convert from
Latin-1 to UTF-8 with the iconv() function and inspecting
the output:
lines2 <- iconv(lines, "latin1", "UTF-8")
lines2[15252][1] "the command of her beauty, and her £20,000, any one who could satisfy the"It worked! Now we can analyze our text.
f <- corpus::text_filter(drop_punct = TRUE, drop = corpus::stopwords_en)
corpus::term_stats(lines2, f) term count support
1 fanny 816 806
2 must 508 492
3 crawford 493 488
4 mr 482 466
5 much 459 450
6 miss 432 419
7 said 406 400
8 mrs 408 399
9 sir 372 366
10 edmund 364 364
11 one 370 358
12 think 349 346
13 now 333 331
14 might 324 320
15 time 310 307
16 little 309 300
17 nothing 301 291
18 well 299 286
19 thomas 288 285
20 good 280 275
⋮ (8450 rows total)If you need more than reading in a single text file, the readtext package supports reading in text in a variety of file formats and encodings. Beyond just plain text, that package can read in PDFs, Word documents, RTF, and many other formats. (Unfortunately, that package currently fails when trying to read in Mansfield Park; the authors are aware of the issue and are working on a fix.)
Text comes in a variety of encodings, and you cannot analyze a text
without first knowing its encoding. Many functions for reading in text
assume that it is encoded in UTF-8, but this assumption sometimes fails
to hold. If you get an error message reporting that your UTF-8 text is
invalid, use utf8_valid to find the offending texts. Try
printing the data to the console before and after using
iconv to convert between character encodings. You can use
utf8_print to print UTF-8 characters that R refuses to
display, including emoji characters. For reading in exotic file formats
like PDF or Word, try the readtext package.