Jupyter_1st.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 解読「Python & Jupyterでデータ解析入門」\n",
    "\n",
    "<div style=\"text-align: right;\">\n",
    "2016.9.18:\n",
    "</div>\n",
    "\n",
    "日経Linuxで、2016.9から表記の連載が始まった。記事の通り触ってみると、Jupyterいいなぁ、と思い始めた。\n",
    "\n",
    "これまでCloud9で環境を構築していたが、コードをファイルで管理しなくてはいけない。特に大変なのは、matplotlibで描画したら、ファイルとして出力しなくてはいけないことだ。\n",
    "\n",
    "これはこれで役に立つことがあるかもしれないが、より便利で簡単な方法を探るのが、コーダーとしては基本的な心がけ。という訳で、しばらくJupyterを触ってみよう。\n",
    "\n",
    "ファンも多い。[現代のエンジニアのための強力なメモ帳 Jupyter notebookのすゝめ \\- クックパッド開発者ブログ](http://techlife.cookpad.com/entry/write-once-share-anywhare)のように、楽しい解説もある。\n",
    "\n",
    "取りあえず、連載が紹介している、cloud上でJupyterが使えるサイト「[Project Jupyter](http://jupyter.org/)」を使い倒してみよう。\n",
    "\n",
    "以下に関連リンク。\n",
    "\n",
    "1. [Jupyter Notebookを利用してお手軽分析環境構築 \\| DATUM STUDIO 株式会社](https://datumstudio.jp/backstage/795)\n",
    "2. [Jupyter nbconvert（ファイル変換）メモ \\- はしくれエンジニアもどきのメモ](http://cartman0.hatenablog.com/entry/2016/03/29/131903)\n",
    "3. [Jupyter Notebook を使ってみよう – Python でデータサイエンス](http://pythondatascience.plavox.info/python%E3%81%AE%E9%96%8B%E7%99%BA%E7%92%B0%E5%A2%83/jupyter-notebook%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%81%BF%E3%82%88%E3%81%86/)\n",
    "\n",
    "## 課題もある\n",
    "\n",
    "コーディングの環境設定ではつきものだが、例によって、独自の設定が必要になる。上記の連載２回目のコードも、そのままでは動かない。盛大にエラーが吐き出される。（**Localにインストールした場合は違うかもしれない。別ウィンドウでシンプルに描画される可能性もあるが、試していない。**）\n",
    "\n",
    "以下のコード。（オリジナルはデータが多すぎるので、簡易化したもの）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n",
      "/opt/conda/lib/python3.5/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "Invalid DISPLAY variable",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m\u001b[0m",
      "\u001b[1;31mRuntimeError\u001b[0mTraceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-cb6ff15229f2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m6\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m8\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m   3145\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0m_autogen_docstring\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mAxes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3146\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3147\u001b[1;33m     \u001b[0max\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgca\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3148\u001b[0m     \u001b[1;31m# allow callers to override the hold state by passing hold=True|False\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3149\u001b[0m     \u001b[0mwashold\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mishold\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mgca\u001b[1;34m(**kwargs)\u001b[0m\n\u001b[0;32m    926\u001b[0m     \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mFigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgca\u001b[0m \u001b[1;33m:\u001b[0m \u001b[0mThe\u001b[0m \u001b[0mfigure\u001b[0m\u001b[0;31m'\u001b[0m\u001b[0ms\u001b[0m \u001b[0mgca\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    927\u001b[0m     \"\"\"\n\u001b[1;32m--> 928\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mgcf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgca\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    929\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    930\u001b[0m \u001b[1;31m# More ways of creating axes:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mgcf\u001b[1;34m()\u001b[0m\n\u001b[0;32m    576\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mfigManager\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    577\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 578\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    579\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    580\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mfigure\u001b[1;34m(num, figsize, dpi, facecolor, edgecolor, frameon, FigureClass, **kwargs)\u001b[0m\n\u001b[0;32m    525\u001b[0m                                         \u001b[0mframeon\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mframeon\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    526\u001b[0m                                         \u001b[0mFigureClass\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mFigureClass\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 527\u001b[1;33m                                         **kwargs)\n\u001b[0m\u001b[0;32m    528\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    529\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mfigLabel\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/backends/backend_qt4agg.py\u001b[0m in \u001b[0;36mnew_figure_manager\u001b[1;34m(num, *args, **kwargs)\u001b[0m\n\u001b[0;32m     44\u001b[0m     \u001b[0mFigureClass\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'FigureClass'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mFigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     45\u001b[0m     \u001b[0mthisFig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mFigureClass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 46\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mnew_figure_manager_given_figure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnum\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mthisFig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     47\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     48\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/backends/backend_qt4agg.py\u001b[0m in \u001b[0;36mnew_figure_manager_given_figure\u001b[1;34m(num, figure)\u001b[0m\n\u001b[0;32m     51\u001b[0m     \u001b[0mCreate\u001b[0m \u001b[0ma\u001b[0m \u001b[0mnew\u001b[0m \u001b[0mfigure\u001b[0m \u001b[0mmanager\u001b[0m \u001b[0minstance\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mgiven\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     52\u001b[0m     \"\"\"\n\u001b[1;32m---> 53\u001b[1;33m     \u001b[0mcanvas\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mFigureCanvasQTAgg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     54\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mFigureManagerQT\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnum\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     55\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/backends/backend_qt4agg.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, figure)\u001b[0m\n\u001b[0;32m     74\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mDEBUG\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     75\u001b[0m             \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'FigureCanvasQtAgg: '\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 76\u001b[1;33m         \u001b[0mFigureCanvasQT\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     77\u001b[0m         \u001b[0mFigureCanvasQTAggBase\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     78\u001b[0m         \u001b[0mFigureCanvasAgg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/backends/backend_qt4.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, figure)\u001b[0m\n\u001b[0;32m     66\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mDEBUG\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     67\u001b[0m             \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'FigureCanvasQt qt4: '\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfigure\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 68\u001b[1;33m         \u001b[0m_create_qApp\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     69\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     70\u001b[0m         \u001b[1;31m# Note different super-calling style to backend_qt5\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/backends/backend_qt5.py\u001b[0m in \u001b[0;36m_create_qApp\u001b[1;34m()\u001b[0m\n\u001b[0;32m    136\u001b[0m                 \u001b[0mdisplay\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0menviron\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'DISPLAY'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    137\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mdisplay\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mre\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msearch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m':\\d'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdisplay\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 138\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Invalid DISPLAY variable'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    139\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    140\u001b[0m             \u001b[0mqApp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mQtWidgets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mQApplication\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\" \"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mRuntimeError\u001b[0m: Invalid DISPLAY variable"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [1, 2, 3]\n",
    "y = [4, 6, 8]\n",
    "\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一行だけ書き加える必要がある。例えば、以下のサイトから。\n",
    "\n",
    "4. [jupyter \\(ipython\\) notebook でグラフが出ない時の対応方法 \\- Qiita](http://qiita.com/polikeiji/items/c6a11c16a0587705c887)\n",
    "5. [python \\- in Ipython notebook, Pandas is not displying the graph I try to plot\\. \\- Stack Overflow](http://stacko\n",
    "6. [%matplotlib inlineを毎回書かなくて済む方法 \\- Qiita](http://qiita.com/nogut0123/items/2c83e30e274e5a51cb41)verflow.com/questions/10511024/in-ipython-notebook-pandas-is-not-displying-the-graph-i-try-to-plot)\n",
    "7. [%matplotlib inlineを毎回書かなくて済む方法 \\- Qiita](http://qiita.com/nogut0123/items/2c83e30e274e5a51cb41)\n",
    "8. [iPython Notebookの\\-\\-pylab inlineは使うのをやめようという話 \\- Wolfeyes Bioinformatics beta](http://yagays.github.io/blog/2014/08/15/ipython-notebook-matplotlib-inline/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f1d6e420160>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nwHqXtCgs+ZZZ75IWiSXfEutd0iKy5FtgvUtaVJb8FKx3SYvOkp+Q9S5pGVjyY7LeJS0T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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1d6f2f2ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 以下の一行を追加。\n",
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [1, 2, 3]\n",
    "y = [4, 6, 8]\n",
    "\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 追記1\n",
    "\n",
    "以下のように、Jupyterをcloud9に入れておく手もある。拡張機能を使えるなど利点もありそうだ。\n",
    "\n",
    "1. [Cloud9で簡単Jupyter環境構築 \\- Qiita](http://qiita.com/y__sama/items/58419e85f39265fe6df8)\n",
    "2. [extensionを追加してもっと快適なJupyter環境を構築する \\- Qiita](http://qiita.com/sasaki77/items/30a19d2be7d94116b237)\n",
    "\n",
    "## 追記2\n",
    "\n",
    "GitHub、Gistに上げておくこともできる。以下。\n",
    "\n",
    "1. [GitHub Gistを使ってブログにJupyter\\(IPython\\) Notebookを表示する方法](http://p--q.blogspot.jp/2015/10/github-gistjupyteripython-notebook.html)\n",
    "2. [Jupyter NotebookをGitHub上で公開する \\- abcdefg\\.\\.\\.\\.\\.](http://pppurple.hatenablog.com/entry/2016/06/11/194713)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  },
  "widgets": {
   "state": {},
   "version": "1.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}