Untitled35.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib import rcParams\n",
    "rcParams[\"savefig.dpi\"] = 100\n",
    "rcParams[\"figure.dpi\"] = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "token = \"ENTER A USER TOKEN HERE\"\n",
    "url = \"https://api.github.com/search/code\"\n",
    "search = \"filename:\\\"Untitled{0}.ipynb\\\"\".format\n",
    "\n",
    "r = requests.get(url, auth=(\"dfm\", token), params={\"q\": search(\"\")})\n",
    "results = [r.json().get(\"total_count\", 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 11795\n",
      "2 4410\n",
      "3 2101\n",
      "4 1263\n",
      "5 799\n",
      "6 547\n",
      "7 394\n",
      "8 307\n",
      "9 217\n",
      "10 194\n",
      "11 153\n",
      "12 117\n",
      "13 97\n",
      "14 77\n",
      "15 69\n",
      "16 54\n",
      "17 46\n",
      "18 53\n",
      "19 38\n",
      "20 31\n",
      "21 0\n",
      "22 0\n",
      "23 0\n",
      "24 0\n",
      "25 0\n",
      "26 0\n",
      "27 0\n",
      "28 0\n",
      "29 0\n",
      "30 0\n",
      "31 0\n",
      "32 0\n",
      "33 0\n",
      "34 0\n",
      "35 0\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 36):\n",
    "    r = requests.get(url, auth=(\"dfm\", token), params={\"q\": search(i)})\n",
    "    results.append(r.json().get(\"total_count\", 0))\n",
    "    print(i, results[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qpaju/qUkmZnc/UrIItz9gcVNlBLGJc1neK0fJf3YeNzidQEAQBdl2bgsc7Aws1Nmdk1R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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1127456d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.semilogy(results[:21], \".\")\n",
    "plt.locator_params(axis=\"x\", integer=True)\n",
    "plt.xlabel(\"Untitled*.ipynb\")\n",
    "plt.ylabel(\"number of files on GitHub\")\n",
    "plt.savefig(\"meme.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "!open ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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