Exploring.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploration of Capstone\n",
    "## Requirements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets checkout AAPL for 2017-01-01 to 2016-12-31 now okay...\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "stock_symbol = 'aapl'\n",
    "start_date = datetime.strptime('2017-01-01', '%Y-%m-%d')\n",
    "end_date = datetime.strptime('2016-12-31', '%Y-%m-%d')\n",
    "\n",
    "print('Lets checkout {} for {} to {} now okay...'.format(stock_symbol.upper(), start_date.date(), end_date.date()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python for Finance by Yves Hilpisch\n",
    "## Chapter 1 - Why Python for Finance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas/io/data.py:35: FutureWarning: \n",
      "The pandas.io.data module is moved to a separate package (pandas-datareader) and will be removed from pandas in a future version.\n",
      "After installing the pandas-datareader package (https://github.com/pydata/pandas-datareader), you can change the import ``from pandas.io import data, wb`` to ``from pandas_datareader import data, wb``.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-04-08</th>\n",
       "      <td>542.60</td>\n",
       "      <td>555.00</td>\n",
       "      <td>541.61</td>\n",
       "      <td>554.90</td>\n",
       "      <td>3152406.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-09</th>\n",
       "      <td>559.62</td>\n",
       "      <td>565.37</td>\n",
       "      <td>552.95</td>\n",
       "      <td>564.14</td>\n",
       "      <td>3324742.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-10</th>\n",
       "      <td>565.00</td>\n",
       "      <td>565.00</td>\n",
       "      <td>539.90</td>\n",
       "      <td>540.95</td>\n",
       "      <td>4027743.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-11</th>\n",
       "      <td>532.55</td>\n",
       "      <td>540.00</td>\n",
       "      <td>526.53</td>\n",
       "      <td>530.60</td>\n",
       "      <td>3916171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-14</th>\n",
       "      <td>538.25</td>\n",
       "      <td>544.10</td>\n",
       "      <td>529.56</td>\n",
       "      <td>532.52</td>\n",
       "      <td>2568020.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open    High     Low   Close     Volume\n",
       "Date                                                 \n",
       "2014-04-08  542.60  555.00  541.61  554.90  3152406.0\n",
       "2014-04-09  559.62  565.37  552.95  564.14  3324742.0\n",
       "2014-04-10  565.00  565.00  539.90  540.95  4027743.0\n",
       "2014-04-11  532.55  540.00  526.53  530.60  3916171.0\n",
       "2014-04-14  538.25  544.10  529.56  532.52  2568020.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# from Python for Finance by Yves Hilpisch - chapter 1\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas.io.data as web\n",
    "# deprecated now pandas-datareader from https://github.com//pydata/pandas-datareader\n",
    "\n",
    "goog = web.DataReader('GOOG', data_source='google',\n",
    "                      start='3/14/2009', end='4/14/2014')\n",
    "goog.tail()\n",
    "# Features: Open, High, Low, Close, Volume -- missing Adjusted Close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/honeydew/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:3: FutureWarning: pd.rolling_std is deprecated for Series and will be removed in a future version, replace with \n",
      "\tSeries.rolling(window=252,center=False).std()\n",
      "  app.launch_new_instance()\n"
     ]
    }
   ],
   "source": [
    "goog['Log_Ret'] = np.log(goog['Close'] / goog['Close'].shift(1))\n",
    "goog['Volatility'] = pd.rolling_std(goog['Log_Ret'],\n",
    "                                    window=252) * np.sqrt(252)\n",
    "# pd.rolling_std deprecated for Series use \n",
    "# Series.rolling(window=252,center=False().std()\n",
    "# app.launch_new_instance()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f7adc534fd0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f7adc468d10>], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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yv+HYCqdbm0AwPXyvsldCHg8EBmZz3GSgdH4q5j/44s1/vsWfB+fi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\nIiIZo+QsIiKSMX8FoAAe6ebAtKIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7adc4fa290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "goog[['Close', 'Volatility']].plot(subplots=True, color='blue',\n",
    "                                   figsize=(8, 6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chapter 2 - Infrastructure and Tools\n",
    "Python Quant Platform @ https://analytics.quant-platform.com (or http://pqp.io/ ?)\n",
    "\n",
    "### Jupyter Notebook Documentation\n",
    "http://ipython.org/documentation.html\n",
    "\n",
    "Equation in Latex - S_T = S_0 \\exp((r - 0.5\\sigma^2) T + \\sigma \\sqrt{T} z)\n",
    "\n",
    "#### Listing of magic commands\n",
    "%lsmagic\n",
    "\n",
    "#### Quick Reference\n",
    "%quickref\n",
    "\n",
    "#### Help\n",
    "help"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chapter 3 - Introductory Examples\n",
    "\n",
    "Example 3.1 shows code for Black-Scholes-Merton option pricing formula\n",
    "\n",
    "### Monte Carlo simulation\n",
    "* applications\n",
    "* efficiency of algorithm implementation (implications for memory use)\n",
    "* implementation examples\n",
    "\n",
    "### Technical Analysis\n",
    "\"In finance, technical analysis is a security analysis methodology for forecasting the direction of prices through the study of past market data, primarily price and volume.\" http://en.wikipedia.org/wiki/Technical_analysis\n",
    "\n",
    "The benchmark index of Standard & Poor's 500 (S&P 500) used for analysis examples to study the entire market."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "IOError",
     "evalue": "after 3 tries, Yahoo! did not return a 200 for url 'http://ichart.finance.yahoo.com/table.csv?s=^GSPC&a=0&b=1&c=2000&d=3&e=14&f=2014&g=d&ignore=.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIOError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-cf3ae38baea4>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m sp500 = web.DataReader('^GSPC', data_source='yahoo',\n\u001b[1;32m----> 6\u001b[1;33m                        start='1/1/2000', end='4/14/2014')\n\u001b[0m\u001b[0;32m      7\u001b[0m \u001b[0msp500\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas/io/data.py\u001b[0m in \u001b[0;36mDataReader\u001b[1;34m(name, data_source, start, end, retry_count, pause)\u001b[0m\n\u001b[0;32m     91\u001b[0m         return get_data_yahoo(symbols=name, start=start, end=end,\n\u001b[0;32m     92\u001b[0m                               \u001b[0madjust_price\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m25\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 93\u001b[1;33m                               retry_count=retry_count, pause=pause)\n\u001b[0m\u001b[0;32m     94\u001b[0m     \u001b[1;32melif\u001b[0m \u001b[0mdata_source\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"google\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     95\u001b[0m         return get_data_google(symbols=name, start=start, end=end,\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas/io/data.py\u001b[0m in \u001b[0;36mget_data_yahoo\u001b[1;34m(symbols, start, end, retry_count, pause, adjust_price, ret_index, chunksize, interval)\u001b[0m\n\u001b[0;32m    438\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Invalid interval: valid values are 'd', 'w', 'm' and 'v'\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    439\u001b[0m     return _get_data_from(symbols, start, end, interval, retry_count, pause,\n\u001b[1;32m--> 440\u001b[1;33m                           adjust_price, ret_index, chunksize, 'yahoo')\n\u001b[0m\u001b[0;32m    441\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    442\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas/io/data.py\u001b[0m in \u001b[0;36m_get_data_from\u001b[1;34m(symbols, start, end, interval, retry_count, pause, adjust_price, ret_index, chunksize, source)\u001b[0m\n\u001b[0;32m    379\u001b[0m     \u001b[1;31m# If a single symbol, (e.g., 'GOOG')\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    380\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstring_types\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mint\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;32m--> 381\u001b[1;33m         \u001b[0mhist_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msrc_fn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstart\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mend\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minterval\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mretry_count\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpause\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    382\u001b[0m     \u001b[1;31m# Or multiple symbols, (e.g., ['GOOG', 'AAPL', 'MSFT'])\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    383\u001b[0m     \u001b[1;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas/io/data.py\u001b[0m in \u001b[0;36m_get_hist_yahoo\u001b[1;34m(sym, start, end, interval, retry_count, pause)\u001b[0m\n\u001b[0;32m    222\u001b[0m            \u001b[1;34m'&g=%s'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0minterval\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    223\u001b[0m            '&ignore=.csv')\n\u001b[1;32m--> 224\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0m_retry_read_url\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mretry_count\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpause\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Yahoo!'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    225\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    226\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas/io/data.py\u001b[0m in \u001b[0;36m_retry_read_url\u001b[1;34m(url, retry_count, pause, name)\u001b[0m\n\u001b[0;32m    199\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    200\u001b[0m     raise IOError(\"after %d tries, %s did not \"\n\u001b[1;32m--> 201\u001b[1;33m                   \"return a 200 for url %r\" % (retry_count, name, url))\n\u001b[0m\u001b[0;32m    202\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    203\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIOError\u001b[0m: after 3 tries, Yahoo! did not return a 200 for url 'http://ichart.finance.yahoo.com/table.csv?s=^GSPC&a=0&b=1&c=2000&d=3&e=14&f=2014&g=d&ignore=.csv'"
     ]
    }
   ],
   "source": [
    "# import numpy as np\n",
    "# import pandas as pd\n",
    "# import pandas.io.data as web\n",
    "\n",
    "sp500 = web.DataReader('^GSPC', data_source='yahoo',\n",
    "                       start='1/1/2000', end='4/14/2014')\n",
    "sp500.info()\n",
    "# IOError: after 3 tries, Yahoo! did not return a 200 (HTTP OK)\n",
    "# for url 'http://ichart.finance.yahoo.com/table.csv?s=^GSPC&a=0&b=1&c=2000&d=3&e=14&f=2014&g=d&ignore=.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>PE</th>\n",
       "      <th>change_pct</th>\n",
       "      <th>last</th>\n",
       "      <th>short_ratio</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>189.59</td>\n",
       "      <td>+1.08%</td>\n",
       "      <td>1006.73</td>\n",
       "      <td>2.09</td>\n",
       "      <td>4:00pm</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          PE change_pct     last  short_ratio    time\n",
       "AMZN  189.59     +1.08%  1006.73         2.09  4:00pm"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Yahoo! Finance data resolution\n",
    "import pandas_datareader.data as wb\n",
    "\n",
    "amzn = wb.get_quote_yahoo('AMZN')\n",
    "amzn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>PE</th>\n",
       "      <th>change_pct</th>\n",
       "      <th>last</th>\n",
       "      <th>short_ratio</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>^GSPC</th>\n",
       "      <td>N/A</td>\n",
       "      <td>+0.37%</td>\n",
       "      <td>2439.07</td>\n",
       "      <td>N/A</td>\n",
       "      <td>4:44pm</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        PE change_pct     last short_ratio    time\n",
       "^GSPC  N/A     +0.37%  2439.07         N/A  4:44pm"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now retry earlier code\n",
    "#sp500 = web.DataReader('^GSPC', data_source='yahoo',\n",
    "#                       start='1/1/2000', end='4/14/2014')\n",
    "#sp500.info()\n",
    "sp500 = wb.get_quote_yahoo('^GSPC')\n",
    "sp500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO: identify fix for Yahoo! Finance data download issues, then review S&P500 examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "RemoteDataError",
     "evalue": "Unable to read URL: http://ichart.finance.yahoo.com/table.csv?a=0&ignore=.csv&s=AAPL&b=1&e=3&d=5&g=d&f=2017&c=2010",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mRemoteDataError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-8e912b235e8e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mpandas_datareader\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpdr\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mpdr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_data_yahoo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'AAPL'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/data.pyc\u001b[0m in \u001b[0;36mget_data_yahoo\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     38\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     39\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mget_data_yahoo\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---> 40\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mYahooDailyReader\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[0mread\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     41\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     42\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/yahoo/daily.pyc\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m     75\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     76\u001b[0m         \u001b[1;34m\"\"\" read one data from specified URL \"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 77\u001b[1;33m         \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mYahooDailyReader\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\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     78\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mret_index\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     79\u001b[0m             \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Ret_Index'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_calc_return_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Adj Close'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    155\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstring_types\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mint\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[0;32m    156\u001b[0m             df = self._read_one_data(self.url,\n\u001b[1;32m--> 157\u001b[1;33m                                      params=self._get_params(self.symbols))\n\u001b[0m\u001b[0;32m    158\u001b[0m         \u001b[1;31m# Or multiple symbols, (e.g., ['GOOG', 'AAPL', 'MSFT'])\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    159\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36m_read_one_data\u001b[1;34m(self, url, params)\u001b[0m\n\u001b[0;32m     72\u001b[0m         \u001b[1;34m\"\"\" read one data from specified URL \"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     73\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_format\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'string'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 74\u001b[1;33m             \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_url_as_StringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     75\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_format\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'json'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     76\u001b[0m             \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_response\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36m_read_url_as_StringIO\u001b[1;34m(self, url, params)\u001b[0m\n\u001b[0;32m     83\u001b[0m         \u001b[0mOpen\u001b[0m \u001b[0murl\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;32mand\u001b[0m \u001b[0mretry\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     84\u001b[0m         \"\"\"\n\u001b[1;32m---> 85\u001b[1;33m         \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_response\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     86\u001b[0m         \u001b[0mtext\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sanitize_response\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     87\u001b[0m         \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36m_get_response\u001b[1;34m(self, url, params)\u001b[0m\n\u001b[0;32m    118\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mparams\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m             \u001b[0murl\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0murl\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\"?\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0murlencode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 120\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mRemoteDataError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Unable to read URL: {0}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\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    121\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    122\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_read_lines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mRemoteDataError\u001b[0m: Unable to read URL: http://ichart.finance.yahoo.com/table.csv?a=0&ignore=.csv&s=AAPL&b=1&e=3&d=5&g=d&f=2017&c=2010"
     ]
    }
   ],
   "source": [
    "import pandas_datareader as pdr\n",
    "\n",
    "pdr.get_data_yahoo('AAPL')\n",
    "# RemoteDataError: Unable to \n",
    "# read URL: http://ichart.finance.yahoo.com/table.csv?a=0&ignore=.csv&s=AAPL&b=1&e=3&d=5&g=d&f=2017&c=2010"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "RemoteDataError",
     "evalue": "Unable to read URL: http://ichart.finance.yahoo.com/table.csv?a=0&ignore=.csv&s=GS&b=1&e=1&d=0&g=d&f=2010&c=2006",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mRemoteDataError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-11-f943f74df450>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m gs = wb.DataReader(\"GS\", data_source='yahoo', start='2006-01-01',\n\u001b[1;32m----> 2\u001b[1;33m                     end='2010-01-01')\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mgs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/data.pyc\u001b[0m in \u001b[0;36mDataReader\u001b[1;34m(name, data_source, start, end, retry_count, pause, session, access_key)\u001b[0m\n\u001b[0;32m    115\u001b[0m                                 \u001b[0madjust_price\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m25\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    116\u001b[0m                                 \u001b[0mretry_count\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mretry_count\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpause\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpause\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 117\u001b[1;33m                                 session=session).read()\n\u001b[0m\u001b[0;32m    118\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m     \u001b[1;32melif\u001b[0m \u001b[0mdata_source\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"yahoo-actions\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/yahoo/daily.pyc\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m     75\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     76\u001b[0m         \u001b[1;34m\"\"\" read one data from specified URL \"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 77\u001b[1;33m         \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mYahooDailyReader\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\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     78\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mret_index\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     79\u001b[0m             \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Ret_Index'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_calc_return_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Adj Close'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    155\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstring_types\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mint\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[0;32m    156\u001b[0m             df = self._read_one_data(self.url,\n\u001b[1;32m--> 157\u001b[1;33m                                      params=self._get_params(self.symbols))\n\u001b[0m\u001b[0;32m    158\u001b[0m         \u001b[1;31m# Or multiple symbols, (e.g., ['GOOG', 'AAPL', 'MSFT'])\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    159\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msymbols\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36m_read_one_data\u001b[1;34m(self, url, params)\u001b[0m\n\u001b[0;32m     72\u001b[0m         \u001b[1;34m\"\"\" read one data from specified URL \"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     73\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_format\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'string'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 74\u001b[1;33m             \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_url_as_StringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     75\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_format\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'json'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     76\u001b[0m             \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_response\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36m_read_url_as_StringIO\u001b[1;34m(self, url, params)\u001b[0m\n\u001b[0;32m     83\u001b[0m         \u001b[0mOpen\u001b[0m \u001b[0murl\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;32mand\u001b[0m \u001b[0mretry\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     84\u001b[0m         \"\"\"\n\u001b[1;32m---> 85\u001b[1;33m         \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_response\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     86\u001b[0m         \u001b[0mtext\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sanitize_response\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     87\u001b[0m         \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/honeydew/anaconda2/lib/python2.7/site-packages/pandas_datareader/base.pyc\u001b[0m in \u001b[0;36m_get_response\u001b[1;34m(self, url, params)\u001b[0m\n\u001b[0;32m    118\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mparams\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m             \u001b[0murl\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0murl\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\"?\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0murlencode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 120\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mRemoteDataError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Unable to read URL: {0}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\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    121\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    122\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_read_lines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mRemoteDataError\u001b[0m: Unable to read URL: http://ichart.finance.yahoo.com/table.csv?a=0&ignore=.csv&s=GS&b=1&e=1&d=0&g=d&f=2010&c=2006"
     ]
    }
   ],
   "source": [
    "gs = wb.DataReader(\"GS\", data_source='yahoo', start='2006-01-01',\n",
    "                    end='2010-01-01')\n",
    "gs.head()\n",
    "# RemoteDataError: Unable to \n",
    "# read URL: http://ichart.finance.yahoo.com/table.csv?a=0&ignore=.csv&s=GS&b=1&e=1&d=0&g=d&f=2010&c=2006"
   ]
  }
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