Clojure Data Analysis Cookbook by Eric Rochester

By Eric Rochester

As information invades increasingly more of existence and company, the necessity to examine it successfully hasn't ever been larger. With Clojure and this publication, youll quickly be attending to grips with each element of information research. Youll commence with sensible recipes that enable you load and fresh your information, then get concise directions to accomplish all of the crucial research initiatives from uncomplicated facts to stylish desktop studying and information clustering algorithms. Get a extra intuitive deal with in your info via hands-on visualization concepts that let you supply attention-grabbing, informative, and compelling reviews, and use Clojure to post your findings to the internet.

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Extra resources for Clojure Data Analysis Cookbook

Sample text

In that case, we can just pull out the information we're interested in and flatten the nested maps before we pass it to Incanter. In this recipe, however, we'll just work with fairly simple data structures. io EOFException]) Moreover, you need some data. json and placed it in the folder named data. It contains a number of top-level JSON objects. xz. You'll need to decompress it into the data directory. Reader. json")] (read-all-json r)))) This binds d to a new dataset that contains the information read in from the JSON documents.

The first parameter of the macro is inserted into the next expression as the last parameter. This structure is inserted into the third expression as the last parameter, and so on, until the end of the form. Let's trace this through a few steps. Say, we start off with the expression (->> x first (map length) (apply +)). As Clojure builds the final expression, here's each intermediate step (the elements to be combined are highlighted at each stage): (->> x first (map length) (apply +))(->>(first x) (map length) (apply +))(->>(map length (first x)) (apply +))(apply + (map length (first x))) Comparing XML and JSON XML and JSON (from the Reading JSON data into Incanter datasets recipe) are very similar.

Getting ready First, we'll use the same dependencies and the require statements as we did in the last recipe, Scraping data from tables in web pages. Next, we'll identify the file to scrape the data from. html. This is a much more modern example of a web page. Instead of using tables, it marks up the text with the section and article tags and other features from HTML5, which help convey what the text means, not just how it should look. " [html-url] (let [html (html/html-resource (URL. html")) | :family | :name | :relationship | |----------------+-----------------+---------------| | Addam's Family | Gomez Addams | — father | | Addam's Family | Morticia Addams | — mother | | Addam's Family | Pugsley Addams | — brother | … How it works… After examining the web page, each family is wrapped in an article tag that contains a header with an h2 tag.

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