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Your data is too big for excel? Command line tools for journalists

Oh no why?

What is this terminal thing you ask? And why do we want to use it?

  • What if the CSV file we want to open is too big for your spreadsheet program?
  • Feel like having a quick look at what the data is without opening the file and needing to take a smoke break?
  • An inexplicable reason your file does not open in your chosen spreadsheet program...
  • There is power here. Grab bits of the internet, manipulate them quickly, and pop them into files or databases without needing to learn the complexities of coding.

The terminal is a text based interface that allows you to run text commands and interact with your file system.

There are alternate names for the terminal including; console, shell, command line, command prompt.

##The beginning

The following tutorial is tailored to the Mac and Linux terminals.

You will need to open up the terminal;

For those on Linux or Mac go right ahead and install csvkit for the last part of the tutorial:

$ easy_install pip
$ pip install csvkit

What are those commands? Package management

Quick note easy_install, pip, and brew are all package managers that allow you to install what we need from the command line. Rather than downloading and trying to install and configure them yourself.

  • easy_install is a package manager to install Python packages, however it isn't a fully fledged one. Pip however is, so first we install easy_install and then pip.
  • pip is another Python package manager. A lot of these packages are on the Python Package Index (PyPI)

When you have trouble installing

There could be a number of issues;

  • dependencies
  • permissions

With dependencies, you should 'oogle the specific error. Perhaps you already have somethings installed, perhaps you need to upgrade, perhaps your operating system has a specific issue. Stackoverflow is a good place to get answers.

Permissions can be a bit more confusing. All the commands we have shown so far are run with permissions that you (the default user) have. Sometimes this isn't enough and you need to run with bigger, grander permissions. Like a super hero, or in this case a super user (also known as root).

$ sudo <your command>

Be careful though, there are some ramifications to doing this.

TODO: explain this

##Getting all the data There have been a lot of tutorials on scraping, getting data out of documents and freedom of information requests.

For this exercise I grabbed all the tweets relating to the #dataharvest16 twitter handle and popped them into a CSV file using a tool called T. Which has it's own tutorial we don't have time for

$ t search all 'EIJC16' --csv -n 3200 > Dataharvest16tweets.csv

This is how I'll write commands in this tutorial. These are the commands we will pop into the terminal in order to do stuff, like processing our data.

Don't worry if you don't have a CSV, you can convert to one

in2csv input_file.xls output_file.csv

Moving around

When you open your terminal you'll be somewhere - but where is that?

$ pwd

Will show you the path that you are in right now.

TODO: mkdir, cd, navigation

List the shizzle in your directory. Command first and options after. List. All. With readable file sizes.

$ ls -alk

Notice that there is your username or perhaps other usernames (like root) listed. These are the owners of the files, and the letters on the very left are permissions (i.e -rw-r--r--).

Don't know what a command does?

$ man ls

How will you get the data?

You will use wget to the file with out data (or whole sites)

$ wget https://github.com/arc64/dataharvest-2016-commandline/blob/master/dataharvest16tweets.csv

You may find you don't have wget installed. To install it, the easiest way is with another package manager called Homebrew. And then run $ brew install wget

If you don't feel like installing the fabulous tool wget, just grab the file (click raw in github), and put it into the directory where you want to use it.

So what does the file look like?

Count the words

wc -w dataharvest16tweets.csv
    3739 dataharvest16tweets.csv

Or lines

wc -l README.md

In a CSV though we want to count the number of rows

csvstat --count dataharvest16tweets.csv
    Row count: 197

Looking at the beginning and end of the file

head dataharvest16tweets.csv
tail dataharvest16tweets.csv

And searching for specific text

grep "@nrecherch" dataharvest16tweets.csv

Return only the top 10

grep "@nrecherch" dataharvest16tweets.csv | head

Get all the headers for the file

$ csvcut -n dataharvest16tweets.csv
  1: ID
  2: Posted at
  3: Screen name
  4: Text

Grab some columns

$ csvcut -c 3, 4 dataharvest16tweets.csv

Print it pretty

head dataharvest16tweets.csv | csvcut -c 3,4 dataharvest16tweets.csv | csvlook

Get some stats about your tweeters

csvcut -c 3 dataharvest16tweets.csv | csvstat

csvgrep -c 3 -m "Hackette7" | csvlook

$ csvcut -c 3 dataharvest16tweets.csv

Getting all the unique handles

$ csvcut -c 'Screen name' dataharvest16tweets.csv | sort | uniq -c | sort -rn

Getting just tweets by Hackette7

csvgrep -c 3 -m "Hackette7" dataharvest16tweets.csv | csvlook

What about just getting the RT

csvgrep -c 4 -r "^RT" dataharvest16tweets.csv

You can run sql queries on it, which if your file is very big will run slow (it is in memory!)

csvsql --query "SELECT * FROM dataharvest16tweets" dataharvest16tweets.csv > dataharvest16tweets_nrecherch.csv

If you really want to you can push this all to a sqllite database

$ cat dataharvest16tweets.csv | csvsql --table tweets --db sqlite:///tweets.sqlite --insert

$ sqlite3 tweets.sqlite

    sqlite> SELECT * FROM tweets;

    sqlite> .exit

What can CSVkit do?

  • clean
  • do sql
  • fuzzy matching
  • pop into a database

CHEATSHEET

Keyboard shortcuts

  • tab completion: use to finish command, directory or file names, or to see directories or files that match
  • ctrl + a: move to the beginning of a line
  • ctrl + e: move to the end of a line
  • ctrl + c: terminate a command that is running
  • up arrow: cycle back through previous commands

UNIX features you should know

  • redirection - >
  • append - >>
  • piping - |

Commands you have have heard in this tutorial

Additional resources

in the beginning was the command line

wget http://www.cryptonomicon.com/command.zip ; unzip command.zip ; nano command.txt

For a workshop that Annabel Church and Sandhya Kambhampati did at Dataharvest in 2016.

With specific thanks to these tutorials and authors for their inspiraton