pandas_yahoo.ipynb

pandas_yahoo.ipynb

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      "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",
       "      <th>Adj Close</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-01-02</th>\n",
       "      <td>111.389999</td>\n",
       "      <td>111.440002</td>\n",
       "      <td>107.349998</td>\n",
       "      <td>109.330002</td>\n",
       "      <td>53204600</td>\n",
       "      <td>107.498407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-05</th>\n",
       "      <td>108.290001</td>\n",
       "      <td>108.650002</td>\n",
       "      <td>105.410004</td>\n",
       "      <td>106.250000</td>\n",
       "      <td>64285500</td>\n",
       "      <td>104.470005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-06</th>\n",
       "      <td>106.540001</td>\n",
       "      <td>107.430000</td>\n",
       "      <td>104.629997</td>\n",
       "      <td>106.260002</td>\n",
       "      <td>65797100</td>\n",
       "      <td>104.479839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-07</th>\n",
       "      <td>107.199997</td>\n",
       "      <td>108.199997</td>\n",
       "      <td>106.699997</td>\n",
       "      <td>107.750000</td>\n",
       "      <td>40105900</td>\n",
       "      <td>105.944875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-08</th>\n",
       "      <td>109.230003</td>\n",
       "      <td>112.150002</td>\n",
       "      <td>108.699997</td>\n",
       "      <td>111.889999</td>\n",
       "      <td>59364500</td>\n",
       "      <td>110.015518</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                  Open        High         Low       Close    Volume  \\\n",
       "Date                                                                   \n",
       "2015-01-02  111.389999  111.440002  107.349998  109.330002  53204600   \n",
       "2015-01-05  108.290001  108.650002  105.410004  106.250000  64285500   \n",
       "2015-01-06  106.540001  107.430000  104.629997  106.260002  65797100   \n",
       "2015-01-07  107.199997  108.199997  106.699997  107.750000  40105900   \n",
       "2015-01-08  109.230003  112.150002  108.699997  111.889999  59364500   \n",
       "\n",
       "             Adj Close  \n",
       "Date                    \n",
       "2015-01-02  107.498407  \n",
       "2015-01-05  104.470005  \n",
       "2015-01-06  104.479839  \n",
       "2015-01-07  105.944875  \n",
       "2015-01-08  110.015518  "
      ]
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   ],
   "source": [
    "import datetime\n",
    "import pandas\n",
    "import pandas.io.data\n",
    "\n",
    "quotes = pandas.io.data.get_data_yahoo(\n",
    "    'AAPL', \n",
    "    start=datetime.datetime(2015, 1, 1), \n",
    "    end=datetime.date.today()\n",
    ")\n",
    "quotes.head()"
   ]
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