Analyzing Text in JavaScript

About This Project
Getting Started
- Files In This Repository
Why Are We Doing This?
Iterations

About This Project

We're going to write a set of simple command-line tools to display basic statistics about a text file or set of text files. Some basic statistics include...

Character count, word count, and sentence count
Letter frequency
Word frequency, e.g., most common and least common words

We'll also work towards adding the ability to...

Download data from an arbitrary URL
Extract the text from a web page for analysis
Display the results in different formats, e.g., charts, histograms, etc.
Export the results to a spreadsheet

Here's a screenshot of a program that downloads the entire text of Moby Dick from Project Gutenberg and prints out a histogram of the letter frequencies.

It turns out that the letter "t" makes up 9.25% of all the letters in Moby Dick.

Getting Started

To get started, you'll need to...

Fork this repository to your own GitHub account
Open a Terminal and clone this repository to your local computer
Navigate to the repository on your local computer
Open the repository in Sublime Text 3, Atom, VS Code, or your editor of choice.
Run npm install to install the required packages.
Read the Why Are We Doing This? section
Start working on the Iterations

Files In This Repository

textalyze.js is the source code for this project
sample_data is a directory containing sample text files to analyze, mostly from Project Gutenberg.

The textalyze.js file that comes with this repository is filled with comments designed to help you get started. You should feel free to delete them in order to make the program easier to read.

Why Are We Doing This?

This project is meant to be simple enough that anyone can start working on it and getting feedback. It's great for beginners and for getting a group of more experienced developers warmed up.

Iterations

This project is structured as a sequence of iterations, each of which builds on previous iterations. Iterations serve three important roles:

Models for good engineering and product management, i.e., what do we build, in what order, and why?
Natural checkpoints to ask for a code review or other feedback
The ability to accommodate students with different interests, skill levels, and time constraints.

Requesting Feedback

To request feedback on your code, use the standard GitHub flow process.

Fork this repository to your own account.
For each iteration, create a feature branch
When you're ready for feedback, submit a pull request from your feature branch to your master branch.
Ping the instructors in Slack to get a review.

[v0.1] Basic Count Statistics

Using hard-coded examples, write a method that takes an Array containing arbitrary and possibly duplicated items as input and returns a Map containing item/count pairs. Print out those pairs in a sensible way.

This iteration has tests written for you. Run

$ npm test

to see the failing tests. Remember to run npm install first!

If you're no familiar with the Map data type in JavaScript, read the Map documentation on MDN.

That is, if the input has 100 entries and 20 of them are the letter "a" then then resulting Map should contain

{ 'a': 20 }

"Sensible" is up to you to define, but here's a suggested format, pretending we hard-coded the input as ["a", "a", "a", "b", "b", "c"].

user@host text-analysis $ npm start
The counts for ["a", "a", "a", "b", "b", "c"] are...
a   3
b   2
c   1
user@host text-analysis $

[v0.2] String to Characters

Using hard-coded examples, write a method that takes an arbitrary String as input and returns an Array of all the characters in the string, including spaces and punctuation.

Feed this into the array-counting method from the previous iteration to get a Map containing letter/count pairs. Print out those pairs in a sensible way.

[v0.3] Basic String Sanitizing

Write a method called sanitize that takes an arbitrary String — perhaps containing spaces, punctuation, line breaks, etc. — and returns a "sanitized" string that replaces all upper-case letters with their lower-case equivalent. This will ensure that the letters 'A' and 'a' are not treated as two distinct letters when we analyze our text. We'll handle punctuation and other bits in a later iteration.

It should work like this

sanitize('This is a sentence.')        // => 'this is a sentence.'
sanitize('WHY AM I YELLING?')          // => 'why am i yelling?'
sanitize('HEY: ThIs Is hArD tO rEaD!') // => 'hey: this is hard to read!'

Lucky for us, Ruby comes with a built-in method to help us: String.prototype.toLowerCase.

Integrate this method into current program so that the Map of results contains, e.g.,

{ 'a': 25 }

instead of

{ 'a': 19, 'A': 6 }

Some Notes on String Sanitizing

Oftentimes the data we want isn't in a format that makes it easy to analyze. The process of taking poorly-formatted data and transforming it into something we can make use of is called sanitizing our data.

What counts as "sanitizing" varies depending on the underlying data and our needs. For example, if we wanted to look at all the text in an HTML document, we wouldn't want to be counting all the HTML tags. Conversely, if we wanted a report on the most commonly-used tags in an HTML document, we'd want to keep the tags but remove the text.

In our case, we've designed our program such that it treats upper-case letters and lower-case letters as distinct letters, i.e., our results Map might contain

{ 'a': 20, 'A': 5 }

but we'd probably rather it just contain

{ 'a': 25 }

Likewise, we probably don't care about punctuation (periods, commas, hyphens, colons, etc.), although this is harder to deal with than differences between upper-case and lower-case letters.

[v0.4] Reading From a Hard-Coded File

The base repository contains a directory called sample_data that contains a handful of text files. Hard-code the name of one of these files into your program and read the contents of that file into a string. Pass that string into your current program, so that it now prints out the letter-count statistics for that specific file instead of the hard-coded strings you had in the previous iteration.

To read the contents of a file into a string, use fs.readFile.

[v1.0] Reading From a User-Supplied File

We don't want to edit our JavaScript code every time we need to change the file from which we're reading data. Let's change it so that the user running the program can pass in the name of the file from which to read. We'll do this using command-line arguments.

This iteration marks v1.0 of our program. As it stands, our program — although limited — is self-contained enough that you could give it to another person and they could use it as you intended without having to know how to edit JavaScript code.

Congrats!

Command-Line Arguments

Consider the following command run from the Terminal:

$ node some-program.js first_argument second_argument banana

The command-line arguments are first_argument, second_argument, and banana, with a space denoting the separation between each argument. first_argument is the first command-line argument and banana is the third command-line argument.

[v1.1] Basic Frequency Statistics

Using hard-coded examples, write a method that takes an Array containing arbitrary and possibly duplicated entries as input and returns a Map containing item/frequency pairs. Print out those pairs in a sensible way.

That is, if the input has 100 entries and 20 of the are letter "a" then then resultant Map should have

{ 'a': 0.20 }

Stretch Approach

You've already written a method that takes an Array and returns a Map containing entry/count pairs and you'll need these counts (one way or another) in order to calculate the overall frequency. If you want to stretch yourself, try writing your "frequency statistics" method in a way that makes use of your "counting statistics" method, so that you don't have to duplicate as much code or work in your program.

This is a "stretch approach," which means it's absolutely not necessary for you to write your program this way. Like we've been saying, it's much better to write something and get feedback on it than get stuck while trying to puzzle out a "better", "faster", "more elegant", etc. approach.

[v1.2] Pretty Histograms

Print out a histogram of letter frequencies, a la the original screenshot. Hint: You can use the frequency for each item as a way to scale the length of the histogram.

GTessarini / text-analysis-js