data1.clj

;; gorilla-repl.fileformat = 1

;; @@
(ns economy-health
  (:require [gorilla-plot.core :as plot]
            [clojure.string :as string]))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-nil'>nil</span>","value":"nil"}
;; <=

;; @@
(def player-file (slurp "/home/nmccarty/players.csv"))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;economy-health/player-file</span>","value":"#'economy-health/player-file"}
;; <=

;; **
;;; This piece of code intreprets and filters the data given to it.
;; **

;; @@
(def monies (->> player-file
                 (string/split-lines)
                 (map #(string/split % #";"))
                 (drop 26)
                 (map last)
                 (map #(Long/parseLong %))
                 (filter #(every? true?
                                  (map (fn [x] (not= x %1))
                                       [500 530 545 560 590 620 635 650 630])))
                 (filter #(> % 1))))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;economy-health/monies</span>","value":"#'economy-health/monies"}
;; <=

;; **
;;; The number of data points left after filtering.
;; **

;; @@
(count monies)
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-unkown'>274</span>","value":"274"}
;; <=

;; **
;;; The first 10 elements of the list of data. I did this just to make sure it looked sane.
;; **

;; @@
(take 10 monies)
;; @@
;; =>
;;; {"type":"list-like","open":"<span class='clj-lazy-seq'>(</span>","close":"<span class='clj-lazy-seq'>)</span>","separator":" ","items":[{"type":"html","content":"<span class='clj-long'>152065</span>","value":"152065"},{"type":"html","content":"<span class='clj-long'>815</span>","value":"815"},{"type":"html","content":"<span class='clj-long'>1707</span>","value":"1707"},{"type":"html","content":"<span class='clj-long'>790</span>","value":"790"},{"type":"html","content":"<span class='clj-long'>9954364</span>","value":"9954364"},{"type":"html","content":"<span class='clj-long'>3275</span>","value":"3275"},{"type":"html","content":"<span class='clj-long'>7890</span>","value":"7890"},{"type":"html","content":"<span class='clj-long'>175613</span>","value":"175613"},{"type":"html","content":"<span class='clj-long'>223465</span>","value":"223465"},{"type":"html","content":"<span class='clj-long'>540817</span>","value":"540817"}],"value":"(152065 815 1707 790 9954364 3275 7890 175613 223465 540817)"}
;; <=

;; **
;;; The most common ammount of money in the data set and how many times it appears.
;; **

;; @@
(reduce (fn [[x1 x2] [y1 y2]]
          (if (> x2 y2)
            [x1 x2]
            [y1 y2]))
        (frequencies monies))
;; @@
;; =>
;;; {"type":"list-like","open":"<span class='clj-vector'>[</span>","close":"<span class='clj-vector'>]</span>","separator":" ","items":[{"type":"html","content":"<span class='clj-long'>680</span>","value":"680"},{"type":"html","content":"<span class='clj-long'>9</span>","value":"9"}],"value":"[680 9]"}
;; <=

;; **
;;; The highest data in the set.
;; **

;; @@
(reduce max monies)
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-long'>9954364</span>","value":"9954364"}
;; <=

;; **
;;; The lowest data in the set.
;; **

;; @@
(reduce min monies)
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-long'>2</span>","value":"2"}
;; <=

;; **
;;; The following is the distribution of wealth overlayed with a translated graph of 1/x.
;;; The x axis is money, and the y axis is the number of players with that ammount of money.
;; **

;; @@
(plot/compose
 (plot/histogram monies 
                :bins 57
                :plot-range [[0 6700] :all])
 (plot/plot #(/ (/ (- % 549) 3300)) [550 6700]))
;; @@
;; =>
;;; 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;; <=

;; @@
;; Output dat file for irkalla
#_(->> monies
     (interpose \newline)
     (reduce str)
     (spit "/home/nmccarty/monies.txt"))
;; @@

;; @@
;; Takes the average of the set
(defn average [coll]
  (double (/ (reduce + coll)
             (count coll))))

;; Takes the mode of the set
(defn mode [coll]
  (->> coll
       (frequencies)
       (reduce (fn [[x1 x2] [y1 y2]]
                 (if (> x2 y2)
                   [x1 x2]
                   [y1 y2])))
       (first)))

;; Takes weighted average in a stupid way
(defn stupid-weighted-average [coll]
  (->> coll
       (sort >)
       (reduce #(/ (+ %1 %2) 2))
       (double)))

;; Helper function to normalize a list
(defn normalize [coll]
  (let [coll-sum (reduce + coll)
        scale       (/ coll-sum)]
    (map #(* % scale)
         coll)))

;; Another helper function
(defn element-wise-combine [operator coll1 coll2]
  (if (or (empty? coll1)
          (empty? coll2))
    '()
    (lazy-seq
     (cons (operator (first coll1)
                     (first coll2))
           (element-wise-combine operator
                                 (rest coll1)
                                 (rest coll2))))))

;; Takes the actual weighted average
(defn weighted-average [coll]
  (let [freq-map      (frequencies coll)
        mode                 (mode coll)
        freq-mode        (freq-map mode)
        count-coll          (count coll)
        weights    (map #(/ (freq-map %)
                            freq-mode)
                        coll)
        weights      (normalize weights)]
    (->> coll
         (element-wise-combine * weights)
         (reduce +)
         (double))))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;economy-health/weighted-average</span>","value":"#'economy-health/weighted-average"}
;; <=

;; @@
(defn rounding-fun [x]
  (long
   (* 1000
      (Math/round
       (double (/ x 1000))))))

(def rounded-monies 
  (map rounding-fun monies))

(println "Average:")
(println (format "%.2f" 
                 (average rounded-monies)))
(println)
(println "Weighed Average:")
(println (format "%.2f" 
                 (weighted-average rounded-monies)))
(println)
(println "Mode:")
(println (format "%.2f" 
                 (double (mode rounded-monies))))
(println)
(println "Average/Weighted Average:")
(println (format "%.2f"
                 (/ (average rounded-monies)
                    (weighted-average rounded-monies))))
(println)
(println "Average/Mode:")
(println (format "%.2f" 
                 (/ (average rounded-monies)
                    (mode rounded-monies))))
(println)
(println "Wighted Average/Mode:")
(println (format "%.2f" 
                 (/ (weighted-average rounded-monies)
                    (mode rounded-monies))))
;; @@
;; ->
;;; Average:
;;; 83708.03
;;; 
;;; Weighed Average:
;;; 2286.89
;;; 
;;; Mode:
;;; 1000.00
;;; 
;;; Average/Weighted Average:
;;; 36.60
;;; 
;;; Average/Mode:
;;; 83.71
;;; 
;;; Wighted Average/Mode:
;;; 2.29
;;; 
;; <-
;; =>
;;; {"type":"html","content":"<span class='clj-nil'>nil</span>","value":"nil"}
;; <=

;; **
;;; The percentage of data points below 49132, for irkalla.
;; **

;; @@
(println
 (format "%.3f%%"
         (* 100
            (double (/ (count (filter #(< % 49132)
                                      monies))
                       (count monies))))))
;; @@
;; ->
;;; 87.956%
;;; 
;; <-
;; =>
;;; {"type":"html","content":"<span class='clj-nil'>nil</span>","value":"nil"}
;; <=

;; **
;;; The percentage of money accounted for by people having less than 49132 dollars.
;; **

;; @@
(println 
 (format "%.3f%%"
         (* 100
            (double (/ (reduce +
                               (filter #(< % 49132) monies))
                       (reduce + monies))))))
;; @@
;; ->
;;; 3.919%
;;; 
;; <-
;; =>
;;; {"type":"html","content":"<span class='clj-nil'>nil</span>","value":"nil"}
;; <=