Counting and mining with the shell

Overview

Teaching: 60 min
Exercises: 30 min

Questions

• How can I count data?

• How can I find data within files?

• How can I combine existing commands to do new things?

Objectives

• Demonstrate counting lines, words, and characters with the shell command wc and appropriate flags

• Use strings to mine files and extract matched lines with the shell

• Create complex single line commands by combining shell commands and regular expressions to mine files

• Redirect a command’s output to a file.

• Process a file instead of keyboard input using redirection.

• Construct command pipelines with two or more stages.

• Explain Unix’s ‘small pieces, loosely joined’ philosophy.

Counting and mining data

Now that you know how to navigate the shell, we will move onto learning how to count and mine data using a few of the standard shell commands. While these commands are unlikely to revolutionise your work by themselves, they’re very versatile and will add to your foundation for working in the shell and for learning to code. The commands also replicate the sorts of uses library users might make of library data.

Counting and sorting

We will begin by counting the contents of files using the Unix shell. We can use the Unix shell to quickly generate counts from across files, something that is tricky to achieve using the graphical user interfaces of standard office suites.

Let’s start by navigating to the directory that contains our data using the cd command:

$ cd shell-lesson

Remember, if at any time you are not sure where you are in your directory structure, use the pwd command to find out:

$ pwd

/Users/riley/Desktop/shell-lesson

And let’s just check what files are in the directory and how large they are with ls -lh:

$ ls -lh

total 9672
-rw-rw-r--  1 jb677  1322   582K 17 Oct 15:45 33504-0.txt
-rw-rw-r--  1 jb677  1322   598K 17 Oct 15:45 829-0.txt
-rw-r--r--@ 1 jb677  1322   920K 20 Oct 16:55 TNA-download-FO-881-file-level-only-csv.tsv
-rw-r--r--@ 1 jb677  1322   1.2M 20 Oct 16:56 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
-rw-r--r--@ 1 jb677  1322   1.0M 20 Oct 16:57 TNA-download-WO-97-multilevel-xlsx.tsv
-rw-rw-r--  1 jb677  1322    16K 17 Oct 15:45 callnumbers.txt
-rw-rw-r--  1 jb677  1322    18K 17 Oct 15:45 diary.html
-rw-rw-r--  1 jb677  1322    16K 17 Oct 15:45 pdflist.txt
drwxr-xr-x  2 jb677  1322    68K Feb  2 00:58 backup
-rw-r--r--  1 jb677  1322   598K Jan 31 18:47 gulliver.txt

In this episode we’ll focus on the three tsv files. These contain data from the UK National Archives ‘Discovery’ catalogue:

• TNA-download-FO-881-file-level-only-csv.tsv contains metadata for records in the Foreign Office: Confidential Print (Numerical Series)
• TNA-download-HO-396-tagged-in-Excel-xlsx.tsv contains metadata for records in the Home Office: Aliens Department: Internees Index
• TNA-download-WO-97-multilevel-xlsx.tsv contains metadata for records in the Royal Hospital Chelsea: Soldier Service Documents.

All content is available under the Open Government Licence v3.0.

CSV and TSV Files

CSV (Comma-separated values) is a common plain text format for storing tabular data, where each record occupies one line and the values are separated by commas. TSV (Tab-separated values) is just the same except that values are separated by tabs rather than commas. Confusingly, CSV is sometimes used to refer to both CSV, TSV and variations of them. The simplicity of the formats make them great for exchange and archival. They are not bound to a specific program (unlike Excel files, say, there is no CSV program, just lots and lots of programs that support the format, including Excel by the way.), and you wouldn’t have any problems opening a 40 year old file today if you came across one.

wc is the “word count” command: it counts the number of lines, words, bytes and characters in files. Since we love the wildcard operator, let’s run the command wc *.tsv to get counts for all the .tsv files in the current directory (it takes a little time to complete):

$ wc *.tsv

    6000  151981  942164 TNA-download-FO-881-file-level-only-csv.tsv
   15025  128415 1249673 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
    4000  150915 1086654 TNA-download-WO-97-multilevel-xlsx.tsv
   25025  431311 3278491 total

The first three columns contains the number of lines, words and bytes (to show number characters you have to use a flag).

If we only have a handful of files to compare, it might be faster or more convenient to just check with Microsoft Excel, OpenRefine or your favourite text editor, but when we have tens, hundreds or thousands of documents, the Unix shell has a clear speed advantage. The real power of the shell comes from being able to combine commands and automate tasks, though. We will touch upon this slightly.

For now, we’ll see how we can build a simple pipeline to find the shortest file in terms of number of lines. We start by adding the -l flag to get only the number of lines, not the number of words and bytes:

$ wc -l *.tsv

    6000 TNA-download-FO-881-file-level-only-csv.tsv
   15025 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
    4000 TNA-download-WO-97-multilevel-xlsx.tsv
   25025 total

The wc command itself doesn’t have a flag to sort the output, but as we’ll see, we can combine three differen shell commands to get what we want.

First, we have the wc -l *.tsv command. We will save the output from this command in a new file. To do that, we redirect the output from the command to a file using the ‘greater than’ sign (>), like so:

$ wc -l *.tsv > lengths.txt

There’s no output now since the output went into the file lengths.txt, but we can check that the output indeed ended up in the file using cat or less (or Notepad or any text editor).

$ cat lengths.txt

    6000 TNA-download-FO-881-file-level-only-csv.tsv
   15025 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
    4000 TNA-download-WO-97-multilevel-xlsx.tsv
   25025 total

Next, there is the sort command. We’ll use the -n flag to specify that we want numerical sorting, not lexical sorting, we output the results into yet another file, and we use cat to check the results:

$ sort -n lengths.txt > sorted-lengths.txt
$ cat sorted-lengths.txt

    4000 TNA-download-WO-97-multilevel-xlsx.tsv
    6000 TNA-download-FO-881-file-level-only-csv.tsv
   15025 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
   25025 total

Finally we have our old friend head, that we can use to get the first line of the sorted-lengths.txt:

$ head -n 1 sorted-lengths.txt

    4000 TNA-download-WO-97-multilevel-xlsx.tsv

But we’re really just interested in the end result, not the intermediate results now stored in lengths.txt and sorted-lengths.txt. What if we could send the results from the first command (wc -l *.tsv) directly to the next command (sort -n) and then the output from that command to head -n 1? Luckily we can, using a concept called pipes. On the command line, you make a pipe with the vertical bar character |. Let’s try with one pipe first:

$ wc -l *.tsv | sort -n

    4000 TNA-download-WO-97-multilevel-xlsx.tsv
    6000 TNA-download-FO-881-file-level-only-csv.tsv
   15025 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
   25025 total

Notice that this is exactly the same output that ended up in our sorted-lengths.txt earlier. Let’s add another pipe:

$ wc -l *.tsv | sort -n | head -n 1

    4000 TNA-download-WO-97-multilevel-xlsx.tsv

It can take some time to fully grasp pipes and use them efficiently, but it’s a very powerful concept that you will find not only in the shell, but also in most programming languages.

Pipes and Filters

This simple idea is why Unix has been so successful. Instead of creating enormous programs that try to do many different things, Unix programmers focus on creating lots of simple tools that each do one job well, and that work well with each other. This programming model is called “pipes and filters”. We’ve already seen pipes; a filter is a program like wc or sort that transforms a stream of input into a stream of output. Almost all of the standard Unix tools can work this way: unless told to do otherwise, they read from standard input, do something with what they’ve read, and write to standard output.

The key is that any program that reads lines of text from standard input and writes lines of text to standard output can be combined with every other program that behaves this way as well. You can and should write your programs this way so that you and other people can put those programs into pipes to multiply their power.

Adding another pipe

We have our wc -l *.tsv | sort -n | head -n 1 pipeline. What would happen if you piped this into cat? Try it!

Solution

The cat command just outputs whatever it gets as input, so you get exactly the same output from

$ wc -l *.tsv | sort -n | head -n 1

and

$ wc -l *.tsv | sort -n | head -n 1 | cat

Count, sort and print (faded example)

To count the total lines in every tsv file, sorting the results and then print the first line of the file we use the following:

wc -l *.tsv | sort | head -n 1

Now let’s change the scenario. Imagine that we have a directory containing 100 csv files. We want to know the 10 files that contain the most words. Fill in the blanks below to count the words for each file, put them into order, and then make an output of the 10 files with the most words (Hint: The sort command sorts in ascending order by default).

__ -w *.csv | sort | ____

Solution

Here we use the wc command with the -w (word) flag on all csv files, sort them and then output the last 10 lines using the tail command.

wc -w *.csv | sort | tail -n 10

Counting number of files, part I

Let’s make a different pipeline. You want to find out how many files and directories there are in the current directory. Try to see if you can pipe the output from ls into wc to find the answer, or something close to the answer.

Solution

You get close with

$ ls -l | wc -l

but the count will be one too high, since the “total” line from ls is included in the count. We’ll get back to a way to fix that later when we’ve learned about the grep command.

Writing to files

The date command outputs the current date and time. Can you write the current date and time to a new file called logfile.txt? Then check the contents of the file.

Solution

$ date > logfile.txt
$ cat logfile.txt

To check the contents, you could also use less or many other commands.

Beware that > will happily overwrite an existing file without warning you, so please be careful.

Appending to a file

While > writes to a file, >> appends something to a file. Try to append the current date and time to the file logfile.txt?

Solution

$ date >> logfile.txt
$ cat logfile.txt

Counting the number of words

Check the manual for the wc command (either using man wc or wc --help) to see if you can find out what flag to use to print out the number of words (but not the number of lines and bytes). Try it with the .tsv files.

If you have time, you can also try to sort the results by piping it to sort. And/or explore the other flags of wc.

Solution

From man wc, you will see that there is a -w flag to print the number of words:

     -w      The number of words in each input file is written to the standard
             output.

So to print the word counts of the .tsv files:

$ wc -w *.tsv

 151981 TNA-download-FO-881-file-level-only-csv.tsv
 128415 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
 150915 TNA-download-WO-97-multilevel-xlsx.tsv
 431311 total

And to sort the lines numerically:

$ wc -w *.tsv | sort -n

 128415 TNA-download-HO-396-tagged-in-Excel-xlsx.tsv
 150915 TNA-download-WO-97-multilevel-xlsx.tsv
 151981 TNA-download-FO-881-file-level-only-csv.tsv
 431311 total

Mining or searching

Searching for something in one or more files is something we’ll often need to do, so let’s introduce a command for doing that: grep (short for global regular expression print). As the name suggests, it supports regular expressions and is therefore only limited by your imagination, the shape of your data, and - when working with thousands or millions of files - the processing power at your disposal.

To begin using grep, first navigate to the shell-lesson directory if not already there. Then create a new directory “results”:

$ mkdir results

Now let’s try our first search:

$ grep 1867 *.tsv 

Remember that the shell will expand *.tsv to a list of all the .tsv files in the directory. grep will then search these for instances of the string “1867” and print the matching lines.

Strings

A string is a sequence of characters, or “a piece of text”.

Press the up arrow once in order to cycle back to your most recent action. Amend grep 1867 *.tsv to grep -c 1867 *.tsv and hit enter.

$ grep -c 1867 *.tsv

TNA-download-FO-881-file-level-only-csv.tsv:120
TNA-download-HO-396-tagged-in-Excel-xlsx.tsv:23
TNA-download-WO-97-multilevel-xlsx.tsv:0

The shell now prints the number of times the string 1867 appeared in each file. If you look at the output from the previous command, this tends to refer to the date field for each journal article.

We will try another search:

$ grep -c German *.tsv

TNA-download-FO-881-file-level-only-csv.tsv:156
TNA-download-HO-396-tagged-in-Excel-xlsx.tsv:340
TNA-download-WO-97-multilevel-xlsx.tsv:14

We got back the counts of the instances of the string German within the files. Now, amend the above command to the below and observe how the output of each is different:

$ grep -ci German *.tsv

TNA-download-FO-881-file-level-only-csv.tsv:194
TNA-download-HO-396-tagged-in-Excel-xlsx.tsv:340
TNA-download-WO-97-multilevel-xlsx.tsv:15

**goes up. But why?. Do grep -c german *.tsv no hits. What is going on? (ALL CAPS!!)

This repeats the query, but prints a case insensitive count (including instances of both german and German and other variants). Note how the count has increased only modestly and in some cases not at all.

Let’s dig a little more into what is going on. Try:

$ grep -c german *.tsv

TNA-download-FO-881-file-level-only-csv.tsv:0
TNA-download-HO-396-tagged-in-Excel-xlsx.tsv:0
TNA-download-WO-97-multilevel-xlsx.tsv:0

We now see the string german appears nowhere in our data. What then accounts for the difference between grep -c German *.tsv and grep -ci German *.tsv? (hint: consider what other variants of german and German are found by grep -ci German *.tsv)

Note if you wanted to any of these outputs, cycling back and adding > results/, followed by a filename (ideally in .txt format), will save the results to a data file.

So far we have counted strings in file and printed to the shell or to file those counts. But the real power of grep comes in that you can also use it to create subsets of tabulated data (or indeed any data) from one or multiple files.

$ grep -i german *.tsv

This script looks in the defined files and prints any lines containing german (without regard to case) to the shell.

$ grep -i german *.tsv > results/TNAdata-german-i.tsv

This saves the subsetted data to file.

However, if we look at this file, it contains every instance of the string ‘german’ including as a single word and as part of other words such as ‘Germany’. This perhaps isn’t as useful as we thought… Thankfully, the -w flag instructs grep to look for whole words only, giving us greater precision in our search.

$ grep -iw german *.tsv > results/TNAdata-german-iw.tsv

This script looks in both of the defined files and exports any lines containing the whole word german (without regard to case) to the specified .tsv file.

We can show the difference between the files we created.

$ wc -l results/*.tsv

     549 results/TNAdata-german-i.tsv
      75 results/TNAdata-german-iw.tsv
     624 total

What can account for the difference?

Finally, we’ll use the regular expression syntax covered earlier to search for similar words.

Basic and extended regular expressions

There is unfortunately both “basic” and “extended” regular expressions. This is a common cause of confusion, since most tutorials, including ours, teach extended regular expression, but grep uses basic by default. Unles you want to remember the details, make your life easy by always using extended regular expressions (-E flag) when doing something more complex than searching for a plain string.

The regular expression ‘fr[ae]nc[eh]’ will match “france”, “french”, but also “frence” and “franch”. It’s generally a good idea to enclose the expression in single quotation marks, since that ensures the shell sends it directly to grep without any processing (such as trying to expand the wildcard operator *).

$ grep -iwE 'fr[ae]nc[eh]' *.tsv

The shell will print out each matching line.

We include the -o flag to print only the matching part of the lines e.g. (handy for isolating/checking results):

$ grep -iwEo 'fr[ae]nc[eh]' *.tsv

Invalid option – o?

If you get an error message “invalid option – o” when running the above command, it means you use a version of grep that doesn’t support the -o flag. This is for instance the case with the version of grep that comes with Git Bash on Windows. Since the flag is not crucial to this lesson, please just relax and ignore the problem. If you really needed the flag, however, you could have installed another version of grep. The situation for Windows users also improves on Windows 10 with the new Bash on Windows.

Pair up with your neighbor and work on these exercies:

Case sensitive search

Search for all case sensitive instances of a word you choose in all three tsv files in this directory. Print your results to the shell.

Solution

$ grep hero *.tsv

Case sensitive search in select files

Search for all case sensitive instances of a word you choose in the ‘FO 881’ and ‘HO 396’ tsv files in this directory. Print your results to the shell.

Solution

$ grep hero TNA-download-FO-881-file-level-only-csv.tsv TNA-download-HO-396-tagged-in-Excel-xlsx.tsv

Count words (case sensitive)

Count all case sensitive instances of a word you choose in the ‘FO 881’ and ‘HO 396’ tsv files in this directory. Print your results to the shell.

Solution

$ grep -c hero TNA-download-FO-881-file-level-only-csv.tsv TNA-download-HO-396-tagged-in-Excel-xlsx.tsv

Count words (case insensitive)

Count all case insensitive instances of that word in the ‘FO 881’ and ‘HO 396’ tsv files in this directory. Print your results to the shell.

Solution

$ grep -ci hero TNA-download-FO-881-file-level-only-csv.tsv TNA-download-HO-396-tagged-in-Excel-xlsx.tsv

Case insensitive search in select files

Search for all case insensitive instances of that word in the ‘FO 881’ and ‘HO 396’ tsv files in this directory. Print your results to a file results/new.tsv.

Solution

$ grep -i hero TNA-download-FO-881-file-level-only-csv.tsv TNA-download-HO-396-tagged-in-Excel-xlsx.tsv > results/new.tsv

Case insensitive search in select files (whole word)

Search for all case insensitive instances of that whole word in the ‘FO 881’ and ‘HO 396’ tsv files in this directory. Print your results to a file results/new2.tsv.

Solution

$ grep -iw hero TNA-download-FO-881-file-level-only-csv.tsv TNA-download-HO-396-tagged-in-Excel-xlsx.tsv > results/new2.tsv

Finding unique values

If you pipe something to the uniq command, it will filter out duplicate lines and only return unique ones. The Royal Hospital Chelsea: Soldier Service Documents contains a number of date ranges (eg ‘1760-1854’ or ‘1815-1833’). Open the solution tab to the problem of working out how many uniq date ranges the data contains. Can you pull this code apart and figure out what each step is doing? Note: This exercise requires the -o flag. See the callout box “Invalid option – o?” above.

Solution

$ grep -Eo '\d{4}-\d{4}' TNA-download-WO-97-multilevel-xlsx.tsv | sort | uniq | wc -l

Counting number of files, part II

In the earlier counting exercise in this episode, you tried counting the number of files and directories in the current directory.

• Recall that the command ls -l | wc -l took us quite far, but the result was one too high because it included the “total” line in the line count.
• With the knowledge of grep, can you figure out how to exclude the “total” line from the ls -l output?
• Hint: You want to exclude any line starting with the text “total”. The hat character (^) is used in regular expressions to indicate the start of a line.

Solution

To find any lines starting with “total”, we would use:

$ ls -l | grep -E '^total'

To *exclude those lines, we add the -v flag:

$ ls -l | grep -v -E '^total'

The grand finale is to pipe this into wc -l:

$ ls -l | grep -v -E '^total' | wc -l

Key Points

• The shell can be used to count elements of documents

• The shell can be used to search for patterns within files

• Command can be used to count and mine any number of files

• Commands and flags can be combined to build complex queries specific to your work