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 with 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 using the readr package.
tmp <- tempfile()
url <- "http://www.gutenberg.org/files/141/141.txt"
download.file(url, tmp)
lines <- readr::read_lines(tmp)
The read_lines function has a locale argument which, if left unspecified
as here, defaults to assuming that text is encoded as “UTF-8”. Really, we
should specify the encoding ourselves. Unfortunately, the file
extension “.txt” does not tell us the 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 file claims to be ASCII, and we read in the text assuming that it was encoded as UTF-8. So, we should be in good shape. However, we run into trouble as soon as we try to process the text:
term_stats(lines) # produces an error
Error in term_stats(lines) :
argument entry 15252 is marked as "UTF-8" but contains an invalid byte in position 36 (\xa3)
The 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 aren't any 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)
utf8_print(ascii, quote = FALSE)
0 1 2 3 4 5 6 7 8 9 a b c d e f
0 \u0001 \u0002 \u0003 \u0004 \u0005 \u0006 \a \b \t \n \v \f \r \u000e \u000f
1 \u0010 \u0011 \u0012 \u0013 \u0014 \u0015 \u0016 \u0017 \u0018 \u0019 \u001a \u001b \u001c \u001d \u001e \u001f
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 { | } ~ \u007f
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. When utf8_print the low level utf8_encode
subroutine format control codes, they do so as \uXXXX for four hexadecimal
digits XXXX or as \UXXXXYYYY for eight hexadecimal digits XXXXYYYY.
Compare the output with the base R print function:
print(ascii, quote = FALSE)
0 1 2 3 4 5 6 7 8 9 a b c d e f
0 \001 \002 \003 \004 \005 \006 \a \b \t \n \v \f \r \016 \017
1 \020 \021 \022 \023 \024 \025 \026 \027 \030 \031 \032 \033 \034 \035 \036 \037
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 { | } ~ \177
Base 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)
utf8_print(latin1, quote = FALSE)
0 1 2 3 4 5 6 7 8 9 a b c d e f
8 \u0080 \u0081 \u0082 \u0083 \u0084 \u0085 \u0086 \u0087 \u0088 \u0089 \u008a \u008b \u008c \u008d \u008e \u008f
9 \u0090 \u0091 \u0092 \u0093 \u0094 \u0095 \u0096 \u0097 \u0098 \u0099 \u009a \u009b \u009c \u009d \u009e \u009f
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 ÿ
As 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]
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:
head(iconvlist(), n = 20)
[1] "437" "850" "852" "855" "857" "860"
[7] "861" "862" "863" "865" "866" "869"
[13] "ANSI_X3.4-1968" "ANSI_X3.4-1986" "ARABIC" "ARMSCII-8" "ASCII" "ASMO-708"
[19] "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:
print(intToUtf8(0x1f600 + 0:79)) # base R
[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.)
Corpus 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_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).
Corpus does not provide a method to translate from another encoding to
UTF-8 as the iconv() function from base R already serves this purpuse.
Back to our original problem: getting the text of Mansfield Park into R. Our first attempt failed:
term_stats(lines)
Error in term_stats(lines) :
argument entry 15252 is marked as "UTF-8" but contains an invalid byte in position 36 (\xa3)
We 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 <- text_filter(drop_punct = TRUE, drop = stopwords("english"))
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
⋮ (8457 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.