| title | teaching | exercises | questions | objectives | keypoints | ||||||||||||||
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Counting and mining with the shell |
60 |
30 |
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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.
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
{: .bash}
Remember, if at any time you are not sure where you are in your directory structure,
use the pwd command to find out:
$ pwd
{: .bash}
/Users/riley/Desktop/shell-lesson
{: .output}
And let's just check what files are in the directory and how large they
are with ls -lh:
$ ls -lh
{: .bash}
total 139M
-rw-r--r-- 1 riley staff 3.6M Jan 31 18:47 2014-01-31_JA-africa.tsv
-rw-r--r-- 1 riley staff 7.4M Jan 31 18:47 2014-01-31_JA-america.tsv
-rw-rw-r-- 1 riley staff 126M Jun 10 2015 2014-01_JA.tsv
-rw-r--r-- 1 riley staff 1.4M Jan 31 18:47 2014-02-02_JA-britain.tsv
-rw-r--r-- 1 riley staff 583K Feb 1 22:53 33504-0.txt
drwxr-xr-x 2 riley staff 68 Feb 2 00:58 backup
-rw-r--r-- 1 riley staff 598K Jan 31 18:47 gulliver.txt
{: .output}
In this episode we'll focus on the dataset 2014-01_JA.tsv, that contains
journal article metadata, and the three .tsv files derived from the original
dataset. Each of these three .tsv files includes all data where a keyword such
as africa or america appears in the 'Title' field of 2014-01_JA.tsv.
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
CSVprogram, 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. {: .callout}
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
{: .bash}
13712 511261 3773660 2014-01-31_JA-africa.tsv
27392 1049601 7731914 2014-01-31_JA-america.tsv
507732 17606310 131122144 2014-01_JA.tsv
5375 196999 1453418 2014-02-02_JA-britain.tsv
554211 19364171 144081136 total
{: .output}
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
{: .bash}
13712 2014-01-31_JA-africa.tsv
27392 2014-01-31_JA-america.tsv
507732 2014-01_JA.tsv
5375 2014-02-02_JA-britain.tsv
554211 total
{: .output}
The wc command itself doesn't have a flag to sort the output, but as we'll
see, we can combine three different 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
{: .bash}
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
{: .bash}
13712 2014-01-31_JA-africa.tsv
27392 2014-01-31_JA-america.tsv
507732 2014-01_JA.tsv
5375 2014-02-02_JA-britain.tsv
554211 total
{: .bash}
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
{: .bash}
5375 2014-02-02_JA-britain.tsv
13712 2014-01-31_JA-africa.tsv
27392 2014-01-31_JA-america.tsv
507732 2014-01_JA.tsv
554211 total
{: .output}
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
{: .bash}
5375 2014-02-02_JA-britain.tsv
{: .output}
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
{: .bash}
5375 2014-02-02_JA-britain.tsv
13712 2014-01-31_JA-africa.tsv
27392 2014-01-31_JA-america.tsv
507732 2014-01_JA.tsv
554211 total
{: .output}
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
{: .bash}
5375 2014-02-02_JA-britain.tsv
{: .output}
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.
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
wcorsortthat 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. {: .callout}
We have our
wc -l *.tsv | sort -n | head -n 1pipeline. What would happen if you piped this intocat? Try it!The
catcommand just outputs whatever it gets as input, so you get exactly the same output from$ wc -l *.tsv | sort -n | head -n 1{: .bash}
and
$ wc -l *.tsv | sort -n | head -n 1 | cat{: .bash} {: .solution} {: .challenge}
To count the total lines in every
tsvfile, sorting the results and then print the first line of the file we use the following:wc -l *.tsv | sort | head -n 1{: .bash}
Now let's change the scenario. Imagine that we have a directory containing 100
csvfiles. 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 | ____{: .bash}
Here we use the
wccommand with the-w(word) flag on allcsvfiles,sortthem and then output the last 10 lines using thetailcommand.wc -w *.csv | sort | tail -n 10{: .solution} {: .bash} {: .challenge}
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
lsintowcto find the answer, or something close to the answer.You get close with
$ ls -l | wc -l{: .bash}
but the count will be one too high, since the "total" line from
lsis included in the count. We'll get back to a way to fix that later when we've learned about thegrepcommand. {: .solution} {: .challenge}
The
datecommand outputs the current date and time. Can you write the current date and time to a new file calledlogfile.txt? Then check the contents of the file.$ date > logfile.txt $ cat logfile.txt{: .bash} To check the contents, you could also use
lessor many other commands.Beware that
>will happily overwrite an existing file without warning you, so please be careful. {: .solution} {: .challenge}
While
>writes to a file,>>appends something to a file. Try to append the current date and time to the filelogfile.txt?$ date >> logfile.txt $ cat logfile.txt{: .bash} {: .solution} {: .challenge}
Check the manual for the
wccommand (either usingman wcorwc --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.tsvfiles.If you have time, you can also try to sort the results by piping it to
sort. And/or explore the other flags ofwc.From
man wc, you will see that there is a-wflag to print the number of words:-w The number of words in each input file is written to the standard output.{: .output}
So to print the word counts of the
.tsvfiles:$ wc -w *.tsv{: .bash}
511261 2014-01-31_JA-africa.tsv 1049601 2014-01-31_JA-america.tsv 17606310 2014-01_JA.tsv 196999 2014-02-02_JA-britain.tsv 19364171 total{: .output}
And to sort the lines numerically:
$ wc -w *.tsv | sort -n{: .bash}
196999 2014-02-02_JA-britain.tsv 511261 2014-01-31_JA-africa.tsv 1049601 2014-01-31_JA-america.tsv 17606310 2014-01_JA.tsv 19364171 total{: .output} {: .solution} {: .challenge}
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
{: .bash}
Now let's try our first search:
$ grep 1999 *.tsv
{: .bash}
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 "1999" and
print the matching lines.
A string is a sequence of characters, or "a piece of text". {: .callout}
Press the up arrow once in order to cycle back to your most recent action.
Amend grep 1999 *.tsv to grep -c 1999 *.tsv and hit enter.
$ grep -c 1999 *.tsv
{: .bash}
2014-01-31_JA-africa.tsv:804
2014-01-31_JA-america.tsv:1478
2014-01_JA.tsv:28767
2014-02-02_JA-britain.tsv:284
{: .output}
The shell now prints the number of times the string 1999 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 revolution *.tsv
{: .bash}
2014-01-31_JA-africa.tsv:20
2014-01-31_JA-america.tsv:34
2014-01_JA.tsv:867
2014-02-02_JA-britain.tsv:9
{: .output}
We got back the counts of the instances of the string revolution within the files.
Now, amend the above command to the below and observe how the output of each is different:
$ grep -ci revolution *.tsv
{: .bash}
2014-01-31_JA-africa.tsv:118
2014-01-31_JA-america.tsv:1018
2014-01_JA.tsv:9327
2014-02-02_JA-britain.tsv:122
{: .output}
This repeats the query, but prints a case
insensitive count (including instances of both revolution and Revolution and other variants).
Note how the count has increased nearly 30 fold for those journal article
titles that contain the keyword 'america'. As before, 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 revolution *.tsv
{: .bash}
This script looks in the defined files and prints any lines containing revolution
(without regard to case) to the shell.
$ grep -i revolution *.tsv > results/2016-07-19_JAi-revolution.tsv
{: .bash}
This saves the subsetted data to file.
However, if we look at this file, it contains every instance of the
string 'revolution' including as a single word and as part of other words
such as 'revolutionary'. 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 revolution *.tsv > results/DATE_JAiw-revolution.tsv
{: .bash}
This script looks in both of the defined files and
exports any lines containing the whole word revolution (without regard to case)
to the specified .tsv file.
We can show the difference between the files we created.
$ wc -l results/*.tsv
{: .bash}
10695 2016-07-19_JAi-revolution.tsv
7859 2016-07-19_JAiw-revolution.tsv
18554 total
{: .output}
Finally, we'll use the regular expression syntax covered earlier to search for similar words.
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
grepuses basic by default. Unles you want to remember the details, make your life easy by always using extended regular expressions (-Eflag) when doing something more complex than searching for a plain string. {: .callout}
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
{: .bash}
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
{: .bash}
If you get an error message "invalid option -- o" when running the above command, it means you use a version of
grepthat doesn't support the-oflag. This is for instance the case with the version ofgrepthat 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 ofgrep. The situation for Windows users also improves on Windows 10 with the new Bash on Windows. {: .callout}
Pair up with your neighbor and work on these exercies:
Search for all case sensitive instances of a word you choose in all four derived tsv files in this directory. Print your results to the shell.
$ grep hero *.tsv{: .bash} {: .solution} {: .challenge}
Search for all case sensitive instances of a word you choose in the 'America' and 'Africa' tsv files in this directory. Print your results to the shell.
$ grep hero *a.tsv{: .bash} {: .solution} {: .challenge}
Count all case sensitive instances of a word you choose in the 'America' and 'Africa' tsv files in this directory. Print your results to the shell.
$ grep -c hero *a.tsv{: .bash} {: .solution} {: .challenge}
Count all case insensitive instances of that word in the 'America' and 'Africa' tsv files in this directory. Print your results to the shell.
$ grep -ci hero *a.tsv{: .bash} {: .solution} {: .challenge}
Search for all case insensitive instances of that word in the 'America' and 'Africa' tsv files in this directory. Print your results to a file
results/new.tsv.$ grep -i hero *a.tsv > results/new.tsv{: .bash} {: .solution} {: .challenge}
Search for all case insensitive instances of that whole word in the 'America' and 'Africa' tsv files in this directory. Print your results to a file
results/new2.tsv.$ grep -iw hero *a.tsv > results/new2.tsv{: .bash} {: .solution} {: .challenge}
Use regular expressions to find all ISSN numbers (four digits followed by hyphen followed by four digits) in
2014-01_JA.tsvand print the results to a fileresults/issns.tsv. Note that you might have to use the-Eflag (or-Pwith some versions ofgrep, e.g. with Git Bash on Windows.).$ grep -E '\d{4}-\d{4}' 2014-01_JA.tsv > issns.tsv{: .bash}
or
$ grep -P '\d{4}-\d{4}' 2014-01_JA.tsv > issns.tsv{: .bash}
If you came up with something more advanced, perhaps including word boundaries, please share your result on the Etherpad and give yourself a pat on the shoulder.
{: .bash} {: .solution} {: .challenge}
If you pipe something to the
uniqcommand, it will filter out duplicate lines and only return unique ones. Try piping the output from the command in the last exercise touniqand then towc -lto count the number of unique ISSN values. Note: This exercise requires the-oflag. See the callout box "Invalid option -- o?" above.$ grep -Eo '\d{4}-\d{4}' 2014-01_JA.tsv | uniq | wc -l{: .bash} {: .solution} {: .challenge}
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 -ltook 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 thels -loutput?- 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.
To find any lines starting with "total", we would use:
$ ls -l | grep -E '^total'{: .bash}
To *exclude those lines, we add the
-vflag:$ ls -l | grep -v -E '^total'{: .bash}
The grand finale is to pipe this into
wc -l:$ ls -l | grep -v -E '^total' | wc -l{: .bash} {: .solution} {: .challenge}
We will now use a loop to automate the counting of certain words within a document.
Go to http://www.gutenberg.org/cache/epub/514/pg514.txt and save the file to your Desktop.
We will now rename the file.
$ mv pg514.txt littlewomen.txt
This will rename the file to something easier to type.
Now let's create our loop. In the loop, we will ask the computer to go through the text, looking for each girl's name, and count the number of times it appears. The results will print to the screen.
$ for name in "Jo" "Meg" "Beth" "Amy"
> do
> echo $name
> grep $name littlewomen.txt | wc -w
> done
{: .bash}
Jo
18877
Meg
8314
Beth
5684
Amy
7933
{: .output}