If you can remember back a month, you'll recall that I'd received a blessed e-mail from someone (hint, hint) asking:

I grabbed three books from the Project Gutenberg archive (gutenberg.org) to analyze and use as test input: Dracula by Bram Stoker, History of the United States by Charles A. Beard and Mary Ritter Beard, and Pride and Prejudice by Jane Austen.

The obvious way to analyze these text files is with the wc command, which reveals that, combined, we're looking at 497,663 words, 2.9 million characters.

We used the following to identify the most common words:

$ cat *txt | tr ' ' '\012' | \
     tr '[:upper:]' '[:lower:]' | \
     tr -d '[:punct:]' | grep -v '[^a-z]' | \
     sort | uniq -c | sort -rn | head

The results were sufficient to reveal that the top ten words that appear in our 500,000-word sample are, in order: the, of, and, to, in, a, i, was, that and it.

Now, let's go in a different direction and analyze letter frequency. Then, we'll go back to finding interesting and unusual words.

The question underlying calculating letter frequency is this: “how do you break down a word into individual letters so that you have one letter per line?” It turns out that the handy Linux tool fold can do exactly what we want:

$ echo hello | fold -w1
h
e
l
l
o

Neatly done! (Note that you can't use fmt or similar commands because even if you specify -w1 for width, it works with words, not characters.)

It's an easy leap from there to make fold break down every single word in a text file, sort the results, and use our power duo of uniq -c | sort -rn to get the results we seek:

$ fold -w1 < dracula.txt | sort | \
      uniq -c | sort -rn | head
157559
78409 e
56524 t
51608 a
50568 o
43453 n
41749 h
38150 s
37950 i
35001 r

A blank is the most common, but we can skip that visually rather than complicate our pipe with yet another process.

As I said in the beginning, E is the most common letter, but it's a surprise to see T as the second most common, frankly. Maybe it's because we're not compensating for upper-/lowercase? Let's try again:

$ fold -w1 < dracula.txt | sort | \
      tr '[:lower:]' '[:upper:]' | uniq -c | \
      sort -rn | head -5
157559
78409 E
56524 T
51608 A
50568 O

Wait a minute. We shouldn't get the same result! Hmmm...can you see what I've done wrong? Hint: look at the order of commands in the pipe.

Got it? The tr needs to appear before the first sort command, or it transforms the output, but after it already has been sorted separately. We also should strip out punctuation, which can be done with the tr command as well. Here's a better attempt:

$ fold -w1 < dracula.txt | \
      tr '[:lower:]' '[:upper:]' | sort | \
      tr -d '[:punct:]' | uniq -c | \
      sort -rn | head
157559
79011 E
58618 T
53146 A
51122 O
43975 N
43501 H
43423 I
39296 S
35607 R

Will this ordering change if we use all three of our books rather than just Dracula? Let's try it:

$ cat *.txt | fold -w1 | \
     tr '[:lower:]' '[:upper:]' | sort | \
     tr -d '[:punct:]' | uniq -c | \
     sort -rn | head
468727
273409 E
201726 T
175637 A
169836 O
158561 N
155910 I
135513 S
133927 R
127716 H

Same result! In order of frequency, the letters appear in text in the following sequence: E T A O N I S R H D L C U M F W G P Y B V K X J Q Z. (I'm a bit surprised that J shows up so infrequently.)

You now know what order to guess letters in Hangman, if nothing else.

Before we wrap this up, let's go back through the words in our corpus and find just those that are at least ten letters long and occur infrequently. Here's how I'll do that:

$ cat *.txt | tr ' ' '\012' | \
     tr '[:upper:]' '[:lower:]' | \
     tr -d '[:punct:]' | tr -d '[0-9]' | \
     sort | uniq -c | sort -n | \
     grep -E '..................' | head
   1 abolitionists
   1 accommodation
   1 accommodations
   1 accomplishing
   1 accomplishments
   1 accountability
   1 achievements
   1 acknowledging
   1 acknowledgments
   1 acquaintanceship
   1 administrative
   1 advertisement

That gives us long words that occur infrequently in the English language—or, at least only once in the 500,000 word corpus we've been analyzing.

(True confession: I simply added more and more dots to the grep regular expression until I weeded out almost all of the results. I could also have used .{10,} to get ten-character or longer matches.)

Some of these words obviously are more common in everyday parlance than in these particular books, however, such as advertisement, which I'm sure occurs more than once every 500,000 words in normal conversation, or at least in the circles I frequent!

What would really be great for Hangman would be to apply the letter-frequency rule further, so that you extract the infrequently occurring words, then come up with a sum value for the frequency of each letter in the word (I'd assign E = 1, T = 2, A = 3, O = 4, for example) and identify the longest words with the highest scores. Those will be your very best Hangman words.

But, I'm out of space and last I checked, I was supposed to be writing about different variable reference formats in shell scripts anyway. I swear, next column, I'll get back to that. Unless you (hint, hint) write me a note with a puzzle or scripting challenge to solve.