chain.ipynb

{
 "metadata": {
  "name": "Twitter Chain"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "from datetime import datetime, timedelta\nimport matplotlib.pyplot as plt\nimport pylab",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "dates = [\n    datetime(2014, 2, 12, 14, 1, 35),\n    datetime(2014, 2, 12, 13, 58, 13),\n    datetime(2014, 2, 12, 12, 30, 53),\n    datetime(2014, 2, 12, 12, 28, 58),\n    datetime(2014, 2, 12, 12, 15, 29),\n    datetime(2014, 2, 12, 12, 11, 28),\n    datetime(2014, 2, 12, 12, 7, 12),\n    datetime(2014, 2, 12, 12, 2, 45),\n    datetime(2014, 2, 12, 11, 8, 54),\n    datetime(2014, 2, 12, 11, 5, 38),\n    datetime(2014, 2, 12, 11, 4, 19),\n    datetime(2014, 2, 12, 11, 2, 3),\n    datetime(2014, 2, 12, 10, 59, 34),\n    datetime(2014, 2, 12, 10, 59, 3),\n    datetime(2014, 2, 12, 10, 58, 36),\n    datetime(2014, 2, 12, 10, 56, 50),\n    datetime(2014, 2, 12, 10, 52, 27),\n    datetime(2014, 2, 12, 10, 46, 40),\n    datetime(2014, 2, 12, 8, 40, 36),\n    datetime(2014, 2, 12, 8, 38, 21),\n    datetime(2014, 2, 12, 8, 36, 46),\n    datetime(2014, 2, 12, 8, 25, 38),\n    datetime(2014, 2, 12, 8, 20, 31),\n    datetime(2014, 2, 12, 7, 58, 16),\n    datetime(2014, 2, 12, 7, 43, 47),\n    datetime(2014, 2, 12, 7, 36, 39),\n    datetime(2014, 2, 12, 6, 27, 16),\n    datetime(2014, 2, 12, 6, 15, 35),\n    datetime(2014, 2, 12, 6, 11, 42),\n    datetime(2014, 2, 12, 6, 8, 12),\n    datetime(2014, 2, 12, 5, 56, 51),\n    datetime(2014, 2, 12, 5, 51, 41),\n    datetime(2014, 2, 12, 5, 42, 17),\n    datetime(2014, 2, 12, 5, 38, 16),\n    datetime(2014, 2, 12, 5, 37, 9),\n    datetime(2014, 2, 12, 5, 33, 40),\n    datetime(2014, 2, 12, 3, 58, 57),\n    datetime(2014, 2, 12, 3, 44, 3),\n    datetime(2014, 2, 12, 3, 38, 27),\n    datetime(2014, 2, 12, 0, 49, 48),\n    datetime(2014, 2, 12, 0, 47, 16),\n    datetime(2014, 2, 12, 0, 30, 47),\n    datetime(2014, 2, 11, 21, 52, 29),\n    datetime(2014, 2, 11, 21, 43, 11),\n    datetime(2014, 2, 11, 21, 38, 43),\n    datetime(2014, 2, 11, 21, 38, 23),\n    datetime(2014, 2, 11, 21, 37, 44),\n    datetime(2014, 2, 11, 20, 51, 25),\n    datetime(2014, 2, 11, 20, 47, 36),\n    datetime(2014, 2, 11, 16, 23, 9),\n    datetime(2014, 2, 11, 16, 21, 49),\n    datetime(2014, 2, 11, 16, 20, 6),\n    datetime(2014, 2, 11, 15, 53, 8),\n    datetime(2014, 2, 11, 15, 50, 0),\n    datetime(2014, 2, 11, 15, 47, 39),\n    datetime(2014, 2, 11, 15, 45, 40),\n    datetime(2014, 2, 11, 15, 42, 45),\n]",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "fig = pylab.figure(figsize=(15, 2), dpi=150)\npylab.xlim([min(dates) - timedelta(0.2), max(dates) + timedelta(0.2)])\npylab.yticks([])\nplt.scatter(dates, [1]*len(dates), 50, c='r', marker='o', alpha=0.35, linewidths=0)",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 46,
       "text": "<matplotlib.collections.PathCollection at 0x7f2499a983d0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": "<matplotlib.figure.Figure at 0x7f2499b03410>"
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}