{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# time_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "matplotlib.style.use(\"ggplot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(DatetimeIndex(['2016-03-01', '2016-03-02', '2016-03-03', '2016-03-04',\n",
       "                '2016-03-05', '2016-03-06', '2016-03-07', '2016-03-08',\n",
       "                '2016-03-09', '2016-03-10', '2016-03-11', '2016-03-12',\n",
       "                '2016-03-13', '2016-03-14', '2016-03-15', '2016-03-16',\n",
       "                '2016-03-17', '2016-03-18', '2016-03-19', '2016-03-20',\n",
       "                '2016-03-21', '2016-03-22', '2016-03-23', '2016-03-24',\n",
       "                '2016-03-25', '2016-03-26', '2016-03-27', '2016-03-28',\n",
       "                '2016-03-29', '2016-03-30', '2016-03-31'],\n",
       "               dtype='datetime64[ns]', freq='D'), 31)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = pd.date_range(start=\"2016-03-01\", end=\"2016-03-31\")\n",
    "dates, len(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(DatetimeIndex(['2016-03-01', '2016-03-02', '2016-03-03', '2016-03-04',\n",
       "                '2016-03-07', '2016-03-08', '2016-03-09', '2016-03-10',\n",
       "                '2016-03-11', '2016-03-14', '2016-03-15', '2016-03-16',\n",
       "                '2016-03-17', '2016-03-18', '2016-03-21', '2016-03-22',\n",
       "                '2016-03-23', '2016-03-24', '2016-03-25', '2016-03-28',\n",
       "                '2016-03-29', '2016-03-30', '2016-03-31'],\n",
       "               dtype='datetime64[ns]', freq='B'), 23)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# b is business\n",
    "bdates = pd.bdate_range(start=\"2016-03-01\", end=\"2016-03-31\")\n",
    "bdates, len(bdates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex([ '1 days',  '2 days',  '3 days',  '4 days',  '5 days',\n",
       "                 '6 days',  '7 days',  '8 days',  '9 days', '10 days',\n",
       "                '11 days', '12 days', '13 days', '14 days', '15 days',\n",
       "                '16 days', '17 days', '18 days', '19 days', '20 days',\n",
       "                '21 days', '22 days', '23 days', '24 days', '25 days',\n",
       "                '26 days', '27 days', '28 days', '29 days', '30 days',\n",
       "                '31 days'],\n",
       "               dtype='timedelta64[ns]', freq='D')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.timedelta_range(start=\"1 days\", end=\"31 days\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function pandas.tseries.period.period_range>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.period_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PeriodIndex(['2016-03-01', '2016-03-02', '2016-03-03', '2016-03-04',\n",
       "             '2016-03-05', '2016-03-06', '2016-03-07', '2016-03-08',\n",
       "             '2016-03-09', '2016-03-10', '2016-03-11', '2016-03-12',\n",
       "             '2016-03-13', '2016-03-14', '2016-03-15', '2016-03-16',\n",
       "             '2016-03-17', '2016-03-18', '2016-03-19', '2016-03-20',\n",
       "             '2016-03-21', '2016-03-22', '2016-03-23', '2016-03-24',\n",
       "             '2016-03-25', '2016-03-26', '2016-03-27', '2016-03-28',\n",
       "             '2016-03-29', '2016-03-30', '2016-03-31'],\n",
       "            dtype='int64', freq='D')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pindex = pd.period_range(start=\"2016-03-01\", end=\"2016-03-31\")\n",
    "pindex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Period('2016-03-01', 'D'), pandas._period.Period)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pindex[0], type(pindex[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(pandas._period.Period, pandas.core.frame.DataFrame)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Period, pd.DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# http://docs.python.jp/3/library/io.html\n",
    "# http://stackoverflow.com/questions/4330812/how-do-i-clear-a-stringio-object\n",
    "import sys\n",
    "import io\n",
    "from contextlib import contextmanager\n",
    "\n",
    "\n",
    "@contextmanager\n",
    "def capture():\n",
    "    _stdout = sys.stdout\n",
    "    with io.StringIO() as strio:\n",
    "        try:\n",
    "            sys.stdout = strio\n",
    "            yield strio\n",
    "        finally:\n",
    "            sys.stdout = _stdout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "output\n",
      "<_io.StringIO object at 0x11721fdc8> False\n",
      "<_io.StringIO object at 0x11721fdc8> False\n",
      "\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000Help on class Period in module pandas._period:\n",
      "\n",
      "class Period(builtins.object)\n",
      " |  Represents an period of time\n",
      " |  \n",
      " |  Parameters\n",
      " |  ----------\n",
      " |  value : Period or compat.string_types, default None\n",
      " |      The time period represented (e.g., '4Q2005')\n",
      " |  freq : str, default None\n",
      " |      One of pandas period strings or corresponding objects\n",
      " |  year : int, default None\n",
      " |  month : int, default 1\n",
      " |  quarter : int, default None\n",
      " |  day : int, default 1\n",
      " |  hour : int, default 0\n",
      " |  minute : int, default 0\n",
      " |  second : int, default 0\n",
      " |  \n",
      " |  Methods defined here:\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "with capture() as c:\n",
    "    print(c, c.closed)\n",
    "    c.flush()\n",
    "    c_log1 = c.getvalue()\n",
    "    c.truncate()\n",
    "    c_log2 = c.getvalue()\n",
    "    c.truncate(0)\n",
    "    help(pd.Period)\n",
    "    help_doc = c.getvalue()\n",
    "    \n",
    "print(\"output\")\n",
    "print(c_log1.strip())\n",
    "print(c_log2.strip())\n",
    "print(\"\\n\".join(help_doc.splitlines()[:20]))\n",
    "print(c.closed)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pd.Period?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period('2016-03-06', 'D')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "period = pd.Period(year=2016, month=3, day=6, freq=\"D\")\n",
    "period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period('2016-03-06', 'D')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Period(\"2016-03-06\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('2016-03-06 00:00:00'), Timestamp('2016-03-06 23:59:59.999999999'))"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "period.start_time, period.end_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[False, True, True, True]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "dt_start = datetime.datetime(2016, 3, 6)\n",
    "dt_end = datetime.datetime(2016, 3, 6, 23, 59, 59)\n",
    "[\n",
    "    period.start_time <  dt_start <= period.end_time,\n",
    "    period.start_time <= dt_start <= period.end_time,\n",
    "    period.start_time <= dt_end <= period.end_time,\n",
    "    period.start_time <= dt_end < period.end_time,\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2016-03-02', '2016-03-03', '2016-03-04', '2016-03-05',\n",
       "               '2016-03-06', '2016-03-07', '2016-03-08', '2016-03-09',\n",
       "               '2016-03-10', '2016-03-11', '2016-03-12', '2016-03-13',\n",
       "               '2016-03-14', '2016-03-15', '2016-03-16', '2016-03-17',\n",
       "               '2016-03-18', '2016-03-19', '2016-03-20', '2016-03-21',\n",
       "               '2016-03-22', '2016-03-23', '2016-03-24', '2016-03-25',\n",
       "               '2016-03-26', '2016-03-27', '2016-03-28', '2016-03-29',\n",
       "               '2016-03-30', '2016-03-31', '2016-04-01'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_range = pd.date_range(\"2016-03-01\", periods=31)\n",
    "end_exclude = date_range.shift(1)\n",
    "end_exclude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>end_exclude</th>\n",
       "      <th>start_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2016-03-28</td>\n",
       "      <td>2016-03-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016-03-29</td>\n",
       "      <td>2016-03-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2016-03-30</td>\n",
       "      <td>2016-03-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2016-03-31</td>\n",
       "      <td>2016-03-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2016-04-01</td>\n",
       "      <td>2016-03-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   end_exclude start_date\n",
       "26  2016-03-28 2016-03-27\n",
       "27  2016-03-29 2016-03-28\n",
       "28  2016-03-30 2016-03-29\n",
       "29  2016-03-31 2016-03-30\n",
       "30  2016-04-01 2016-03-31"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_df = pd.DataFrame({\n",
    "    \"start_date\": date_range,\n",
    "     \"end_exclude\": end_exclude\n",
    "})\n",
    "date_df.tail()"
   ]
  }
 ],
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