{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "3b48fe04",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#data = floor(1000*randn(100000)**1)\n",
    "#data = floor(1000*randn(100000)**2)\n",
    "#data = floor(1000*exp(-10*rand(100000)))\n",
    "data = floor(1000*rand(1000000)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "020e4a39",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "224ef313",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "counts = Counter(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "06d11092",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "scounts = -sort(-array(counts.values()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "a68bb5a3",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x75d9850>]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uBMKXzm7YsIG+vj7WrFkTuQy3v7+f4uJimpqaSExMpLa2ltTU1IuLtCzeeMNwLpNERCQK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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(scounts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "3f767d40",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x6d1a310>]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RR8yZsXY7XH89/O53Zp6+NlGBFxGf1aQJPPEEHDwIJ05Ay5bm53//2+pkNUMF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\nEREf9X+Mja/vHHwBIwAAAABJRU5ErkJggg==\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(log(1+arange(len(scounts))),log(scounts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1435344c",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}