20160722Demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "## Python Basic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "125000.0"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2500000 * 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "tax = 2500000 * 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "125000.0\n"
     ]
    }
   ],
   "source": [
    "print(tax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Markdown Example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# h1\n",
    "## h2\n",
    "### h3\n",
    "\n",
    "### ordered item list\n",
    "\n",
    "1. item1\n",
    "2. item2\n",
    "3. item3\n",
    "\n",
    "### unordered item list\n",
    "\n",
    "- item\n",
    "- item\n",
    "- item\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "## TW2330 Sample Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-07-21</td>\n",
       "      <td>171.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>33130000</td>\n",
       "      <td>172.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-07-20</td>\n",
       "      <td>170.0</td>\n",
       "      <td>170.5</td>\n",
       "      <td>169.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>38053000</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-07-19</td>\n",
       "      <td>170.5</td>\n",
       "      <td>170.5</td>\n",
       "      <td>169.0</td>\n",
       "      <td>170.5</td>\n",
       "      <td>42456000</td>\n",
       "      <td>170.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>168.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>169.5</td>\n",
       "      <td>24749000</td>\n",
       "      <td>169.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-07-15</td>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>41000</td>\n",
       "      <td>169.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date   Open   High    Low  Close    Volume  Adj Close\n",
       "0  2016-07-21  171.0  172.0  170.0  172.0  33130000      172.0\n",
       "1  2016-07-20  170.0  170.5  169.0  170.0  38053000      170.0\n",
       "2  2016-07-19  170.5  170.5  169.0  170.5  42456000      170.5\n",
       "3  2016-07-18  168.0  170.0  168.0  169.5  24749000      169.5\n",
       "4  2016-07-15  169.5  169.5  169.5  169.5     41000      169.5"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# C:\\Users\\Student\\tw2330.csv\n",
    "import pandas\n",
    "tw2330 = pandas.read_csv('C:\\\\Users\\\\Student\\\\tw2330.csv')\n",
    "tw2330.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32.754\n",
      "count    3904.000000\n",
      "mean       75.939250\n",
      "std        31.686305\n",
      "min        32.754000\n",
      "25%        54.860425\n",
      "50%        63.023600\n",
      "75%        88.475000\n",
      "max       172.000000\n",
      "Name: Close, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(min(tw2330['Close']))\n",
    "print(tw2330['Close'].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x98095c0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aYZVnklzSNF0NfA+4F7i5absJ+PJCP0OSNHeDznK5gslpi68E/hvw94GzgHuAi4AjTE5b\nfL7Pa+2ha0Ha0rNty/fQ8lqSWS6DMtC1UG0JwrZ8Dy2vpZrlIklaQQx0SWqJgZb+S8OSFiz9X7du\n2BWobQx0jZzlGHd2fFujyCEXSWoJA12SWsJAl6SWMNAlqSUMdKmPsbFhVyDNnytFJWmEuFJUklYB\nA12SWsJAl6SWMNAlqSUMdKmPnrsjSiPDWS5SH+7lopXKWS6StAoY6JLUEgMHepJXJPl2knubx+uS\nPJDkyST3J1k7eJmSpNksRg99O7C/5/EOYE9VvQl4ENi5CJ8hSZrFQIGeZCPwi8Cne5qvA3Y3x7uB\n6wf5DGkY3MtFo2igWS5JvgD8c2At8BtVdW2S56pqXc85P6iq1/R5rbNcJGmelmSWS5K/BUxU1V5g\npjs8mtqStAwGuafozwPXJvlF4FXAuUn+DXAsyfqqmkiyAfifZ3qD8Z7VG51Oh06nM0A5ktQ+3W6X\nbrc7p3MXZWFRkrfzoyGXjwPfr6rbk/wWsK6qdvR5jUMukjRPy72w6DbgnUmeBK5uHkuSlphL/6U+\nxsfdz0Ur00w9dANd6sO9XLRSuZeLJK0CBroktYSBLkktYaBLUksY6FIf7uWiUeQsF7VeMtPOFIvH\n37OWw0yzXAZZ+i+NBINWq4VDLpLUEga6JLWEgS5JLWGgS1JLGOiS1BIGuiS1hIEuSS1hoEtSSxjo\nktQSBroktYSBLkktseBAT7IxyYNJvpdkX5J/3LSvS/JAkieT3J9k7eKVK0k6k0F66CeBf1JVPw38\ndeDDSX4K2AHsqao3AQ8COwcvU1pe3W532CVI87bgQK+qY1W1tzl+ATgAbASuA3Y3p+0Grh+0SGm5\nGegaRYsyhp5kM/BXgW8A66tqAiZDH7hgMT5DkjSzgQM9yauBPwW2Nz310zefdjNqSVoGA92xKMka\n4D7gz6vqXzZtB4BOVU0k2QA8VFVb+rzWoJekBViqOxZ9Btg/FeaNe4GbgduBm4Avz6cgSdLCLLiH\nnuTngf8I7GNyWKWAjwKPAfcAFwFHgBur6vlFqVaSdEZDu0m0JGlxuVJUq0KS9Uk+n+Rgkm8muS/J\nG5PsG3Zt0mIZdAxdGhVfBHZV1S8BJLkMWI+zsNQi9tDVekneAfy/qvrXU21VtQ94puecc5J8Jsnj\nSb6VpNO0X5rk0STfTrI3yeub9vf3tP+rJF7k19AZ6FoN3gx8a5ZzPgy8WFWXA78M7E5yNvAPgX9R\nVVcCbwH+e7PFxd8Bfq5pfxF4/5JVL82RQy7SpKuAPwCoqieTHAYuAR4BPpbkIuDPqupQkquBK4Fv\nNj3zHwMmhlO29CMGulaD7wE3zPM1Aaiqzyf5BvAe4N8l+QfNc7ur6mOLW6Y0GIdc1HpV9SBwdpJf\nmWprLope1HPaf6IZNklySfPck0kurqqnquoPmVw0dznwH4Abkvzl5vx1SV63PN9GOjMDXavFe4F3\nJjnUTFX8HeBYz/OfAs5K8jjweeCmqjoB3JjkiSTfAX4a+FxVHQD+GfBAku8CDwAblvPLSP24sEiS\nWsIeuiS1hIEuSS1hoEtSSxjoktQSBroktYSBLkktYaBLUksY6JLUEv8fhlDcmjV88ccAAAAASUVO\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8171b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%pylab inline\n",
    "tw2330['Close'].plot(kind='box')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xafe2438>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x9c2e908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%pylab inline\n",
    "tw2330['Close'].plot(kind='hist')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python and File Process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# w => write data to a file, r => read data from a file\n",
    "fid = open('test.txt', 'w')\n",
    "\n",
    "# write hello world into 'test.txt'\n",
    "fid.write('Hello World')\n",
    "\n",
    "# close the file\n",
    "fid.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['__class__', '__delattr__', '__doc__', '__enter__', '__exit__', '__format__', '__getattribute__', '__hash__', '__init__', '__iter__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', 'close', 'closed', 'encoding', 'errors', 'fileno', 'flush', 'isatty', 'mode', 'name', 'newlines', 'next', 'read', 'readinto', 'readline', 'readlines', 'seek', 'softspace', 'tell', 'truncate', 'write', 'writelines', 'xreadlines']\n",
      "Help on built-in function read:\n",
      "\n",
      "read(...)\n",
      "    read([size]) -> read at most size bytes, returned as a string.\n",
      "    \n",
      "    If the size argument is negative or omitted, read until EOF is reached.\n",
      "    Notice that when in non-blocking mode, less data than what was requested\n",
      "    may be returned, even if no size parameter was given.\n",
      "\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "fid = open('test.txt', 'w')\n",
    "print(dir(fid)) # look up the funciton of an object\n",
    "print(help(fid.read)) # look up the help page of the read function\n",
    "fid.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# # stands for comment\n",
    "with open('test.txt', 'w') as f: # as => alias, with: automatically close the file\n",
    "    f.write('Hello, how are you') # indent: attribute action to certain block"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('test.txt', 'w') as f: \n",
    "    f.write('Hello \\n how are you') # \\n: new line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello \n",
      " how are you\n"
     ]
    }
   ],
   "source": [
    "# r, read data from the file\n",
    "with open('test.txt', 'r') as f:\n",
    "    print f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello \n",
      "\n",
      " how are you\n"
     ]
    }
   ],
   "source": [
    "# r, read data from the file\n",
    "with open('test.txt', 'r') as f:\n",
    "    for line in f.readlines(): # for loop belones to with...open\n",
    "        print line # print belongs to for loop"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 讀取半結構化資料與結構化資料"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>2001-01-08</td>\n",
       "      <td>53.4707</td>\n",
       "      <td>55.8604</td>\n",
       "      <td>52.5744</td>\n",
       "      <td>53.4707</td>\n",
       "      <td>143667300</td>\n",
       "      <td>24.3994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>2001-01-05</td>\n",
       "      <td>50.7822</td>\n",
       "      <td>54.0681</td>\n",
       "      <td>50.7822</td>\n",
       "      <td>54.0681</td>\n",
       "      <td>149055800</td>\n",
       "      <td>24.6720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>2001-01-04</td>\n",
       "      <td>51.0809</td>\n",
       "      <td>51.3796</td>\n",
       "      <td>49.8861</td>\n",
       "      <td>50.7822</td>\n",
       "      <td>173936400</td>\n",
       "      <td>23.1726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>2001-01-03</td>\n",
       "      <td>48.0937</td>\n",
       "      <td>49.2885</td>\n",
       "      <td>47.4963</td>\n",
       "      <td>48.0937</td>\n",
       "      <td>82200300</td>\n",
       "      <td>21.9458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>2001-01-02</td>\n",
       "      <td>46.6002</td>\n",
       "      <td>49.8861</td>\n",
       "      <td>46.3015</td>\n",
       "      <td>49.8861</td>\n",
       "      <td>81548300</td>\n",
       "      <td>22.7637</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date     Open     High      Low    Close     Volume  Adj Close\n",
       "3899  2001-01-08  53.4707  55.8604  52.5744  53.4707  143667300    24.3994\n",
       "3900  2001-01-05  50.7822  54.0681  50.7822  54.0681  149055800    24.6720\n",
       "3901  2001-01-04  51.0809  51.3796  49.8861  50.7822  173936400    23.1726\n",
       "3902  2001-01-03  48.0937  49.2885  47.4963  48.0937   82200300    21.9458\n",
       "3903  2001-01-02  46.6002  49.8861  46.3015  49.8861   81548300    22.7637"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas # import, include package into python \n",
    "# press tab to find function\n",
    "tw2330 = pandas.read_csv('C:\\\\Users\\\\Student\\\\tw2330.csv') # read csv into a data frame\n",
    "tw2330.head() # lookup the first 5 ines\n",
    "tw2330.tail() # lookup the last  5 lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rate = pandas.read_excel('C:\\\\Users\\\\Student\\\\rate.xlsx') # read excel into a data frame\n",
    "rate.head()\n",
    "rate.head().to_excel('new.xlsx') # to_excel, write data into excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tw2330.head().to_json('2330.json') # write data to json file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>Adj Close</th>\n",
       "      <th>Close</th>\n",
       "      <th>Date</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>172.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>2016-07-21</td>\n",
       "      <td>172.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>33130000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>170.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>2016-07-20</td>\n",
       "      <td>170.5</td>\n",
       "      <td>169.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>38053000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>170.5</td>\n",
       "      <td>170.5</td>\n",
       "      <td>2016-07-19</td>\n",
       "      <td>170.5</td>\n",
       "      <td>169.0</td>\n",
       "      <td>170.5</td>\n",
       "      <td>42456000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>170.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>24749000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>2016-07-15</td>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>169.5</td>\n",
       "      <td>41000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Adj Close  Close       Date   High    Low   Open    Volume\n",
       "0      172.0  172.0 2016-07-21  172.0  170.0  171.0  33130000\n",
       "1      170.0  170.0 2016-07-20  170.5  169.0  170.0  38053000\n",
       "2      170.5  170.5 2016-07-19  170.5  169.0  170.5  42456000\n",
       "3      169.5  169.5 2016-07-18  170.0  168.0  168.0  24749000\n",
       "4      169.5  169.5 2016-07-15  169.5  169.5  169.5     41000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_tw2330 = pandas.read_json('2330.json') # read data from json file\n",
    "json_tw2330.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>https://www.ptt.cc/bbs/creditcard/index.html</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [https://www.ptt.cc/bbs/creditcard/index.html]\n",
       "Index: []"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clipboard = pandas.read_clipboard() #read data from copied region\n",
    "clipboard.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PTT 爬蟲"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Response [200]>\n",
      "<class 'requests.models.Response'>\n"
     ]
    }
   ],
   "source": [
    "import requests # import package\n",
    "res = requests.get('https://www.ptt.cc/bbs/creditcard/index.html') # use GET to retrieve page\n",
    "print(res)\n",
    "print(type(res))\n",
    "#print(res.text) # print out crawled result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HTTP 狀態碼\n",
    "- https://zh.wikipedia.org/wiki/HTTP%E7%8A%B6%E6%80%81%E7%A0%81"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 高鐵爬蟲"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Response [200]>\n"
     ]
    }
   ],
   "source": [
    "import requests # import package\n",
    "#信紙\n",
    "payload = { \n",
    "'StartStation':'977abb69-413a-4ccf-a109-0272c24fd490',\n",
    "'EndStation':'3301e395-46b8-47aa-aa37-139e15708779',\n",
    "'SearchDate':'2016/07/22',\n",
    "'SearchTime':'15:30',\n",
    "'SearchWay':'DepartureInMandarin'\n",
    "}\n",
    "res = requests.post('https://www.thsrc.com.tw/tw/TimeTable/SearchResult', data = payload) # use post to retrieve page\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BeautifulSoup4 範例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " <html> <body> <h1 id=\"title\">Hello World</h1> <a class=\"link\" href=\"#\">This is link1</a> <a class=\"link\" href=\"# link2\">This is link2</a> </body> </html>\n",
      "<class 'bs4.BeautifulSoup'>\n",
      "   Hello World This is link1 This is link2  \n"
     ]
    }
   ],
   "source": [
    "from bs4 import BeautifulSoup # read BeautifulSoup function from package bs4\n",
    "html_sample = ' \\\n",
    "<html> \\\n",
    " <body> \\\n",
    " <h1 id=\"title\">Hello World</h1> \\\n",
    " <a href=\"#\" class=\"link\">This is link1</a> \\\n",
    " <a href=\"# link2\" class=\"link\">This is link2</a> \\\n",
    " </body> \\\n",
    " </html>'\n",
    "\n",
    "#print(html_sample)\n",
    "soup = BeautifulSoup(html_sample, 'html.parser') #  read html into BeautifulSoup object\n",
    "print(soup)\n",
    "print(type(soup))\n",
    "print(soup.text) # extract text from html page, and remove tag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<h1 id=\"title\">Hello World</h1>]\n",
      "<h1 id=\"title\">Hello World</h1>\n",
      "Hello World\n"
     ]
    }
   ],
   "source": [
    "print(soup.select('h1'))\n",
    "print(soup.select('h1')[0]) # get first element from the list\n",
    "print(soup.select('h1')[0].text) # get the text of first element from the list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<a class=\"link\" href=\"#\">This is link1</a>, <a class=\"link\" href=\"# link2\">This is link2</a>]\n",
      "This is link1\n",
      "This is link2\n"
     ]
    }
   ],
   "source": [
    "print(soup.select('a'))\n",
    "for a in soup.select('a'): # if you found multiple links, use for loop to extract them all\n",
    "    #print(a)\n",
    "    print(a.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 根據 id 及class 取得資料"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<h1 id=\"title\">Hello World</h1>]\n"
     ]
    }
   ],
   "source": [
    "print(soup.select('#title')) # retrieve data wihtin id = title, id => #"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<a class=\"link\" href=\"#\">This is link1</a>, <a class=\"link\" href=\"# link2\">This is link2</a>]\n"
     ]
    }
   ],
   "source": [
    "print(soup.select('.link')) # retrieve data wihtin class = link, class => ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<a class=\"link\" href=\"#\">This is link1</a>\n",
      "#\n",
      "<a class=\"link\" href=\"# link2\">This is link2</a>\n",
      "# link2\n"
     ]
    }
   ],
   "source": [
    "for link in soup.select('.link'):\n",
    "    print(link)\n",
    "    print(link['href'])\n",
    "    #print(link.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<a bank=\"123\" href=\"#\" qoo=\"abc\">a link </a>\n",
      "#\n",
      "abc\n",
      "123\n"
     ]
    }
   ],
   "source": [
    "soup = BeautifulSoup('<a href=\"#\" qoo=abc bank=123>a link </a>')\n",
    "alink =  soup.select('a')[0]\n",
    "print(alink)\n",
    "print(alink['href'])\n",
    "print(alink['qoo'])\n",
    "print(alink['bank'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PTT crawler to retieve title, author, time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "[問題] 網購玉山信用卡複數活動可合計嗎？\n",
      "GP01Fb  7/22\n",
      "\n",
      "[心得] 元大鑽金J&V&M/愛金V&M/台新@gogo/中信調額 成功\n",
      "mltw  7/22\n",
      "\n",
      "=== 卡板板規 V5.0 === (修訂日期：2012/10/02)\n",
      "Heumay 10/02\n",
      "\n",
      "[公告] 置底檢舉專區\n",
      "bboy0720  3/05\n",
      "\n",
      "[情報] 各家銀行0800免付費電話\n",
      "MoonAthenaX  3/09\n",
      "\n",
      "Fw: [申請] creditcard調整發文權限\n",
      "MoonAthenaX  7/08\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "res  = requests.get('https://www.ptt.cc/bbs/creditcard/index.html')\n",
    "#print res.text\n",
    "soup = BeautifulSoup(res.text)\n",
    "for ent in soup.select('.r-ent'):\n",
    "    print ent.select('.title')[0].text, ent.select('.author')[0].text, ent.select('.date')[0].text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HTML Tutorial\n",
    "- http://www.w3school.com.cn/html/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## List"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "John\n",
      "180\n"
     ]
    }
   ],
   "source": [
    "# represent one person\n",
    "name   = 'John'\n",
    "height = 180\n",
    "weight = 70\n",
    "\n",
    "# represent three persons using list []\n",
    "names = ['John', 'Mary', 'QOO']\n",
    "heights = [180,172,165]\n",
    "\n",
    "\n",
    "# extract john\n",
    "print(names[0])\n",
    "\n",
    "# extract john's height\n",
    "print(heights[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "180\n",
      "172\n",
      "165\n"
     ]
    }
   ],
   "source": [
    "# repeat the same action on different object\n",
    "heights = [180,172,165]\n",
    "for h in heights:\n",
    "    print(h)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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