Skip to content

Instantly share code, notes, and snippets.

@liyi-1989

liyi-1989/GetGoogleFinance.ipynb

Forked from jgoad/GetGoogleFinance.ipynb
Created July 19, 2016 14:31
Show Gist options
  • Save liyi-1989/bd768634cc8cd63f1fbd2f54ef4f1d1a to your computer and use it in GitHub Desktop.
Save liyi-1989/bd768634cc8cd63f1fbd2f54ef4f1d1a to your computer and use it in GitHub Desktop.
Download ZIP
Display the source blob
Display the rendered blob
Raw
GetGoogleFinance.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:d618eb449ee1ee930e52b892279ec4cd0713b4be190aa8f8b317369d8d629d4f"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"import requests\n",
"import json\n",
"import pandas as pd\n",
"import numpy as np\n",
"from pandas import DataFrame, Series, MultiIndex\n",
"import datetime as datetime\n",
"from ggplot import *\n",
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def round_time(dt=None, roundTo=60):\n",
" \n",
" seconds = (dt - dt.min).seconds\n",
" \n",
" rounding = (seconds+roundTo/2) // roundTo * roundTo\n",
" return dt + datetime.timedelta(0,rounding-seconds,-dt.microsecond)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def get_google_finance(ticker,period = '2M'):\n",
" \n",
" '''Returns a data frame containing minute data for the given ticker over the given interval'''\n",
" \n",
" r = requests.get('http://www.google.com/finance/getprices?q='+ticker+'&i=119&p='+period+'&f=d,o,h,l,c,v')\n",
" split = r.text.split('\\n')\n",
" df = []\n",
" \n",
" for word in split[7:]:\n",
" df.append(word.split(','))\n",
" data = DataFrame(df, columns = ['DATE','CLOSE','HIGH','LOW','OPEN','VOLUME'], dtype = 'float').dropna()\n",
" for i in range(len(data.DATE)):\n",
" data.DATE.ix[i] = data.DATE.ix[i].replace('a','')\n",
" for i in range(len(data.DATE)):\n",
" data.DATE.ix[i] = datetime.datetime.fromtimestamp(int(data.DATE.ix[i])).strftime('%Y-%m-%d %H:%M:%S')\n",
" \n",
" timedelta = round_time(datetime.datetime.utcnow(),60) - round_time(datetime.datetime.now(),60)\n",
" data.DATE = pd.to_datetime(data.DATE) + timedelta\n",
" \n",
" \n",
" data.index = pd.DatetimeIndex(data.DATE)\n",
" data = data.drop('DATE', axis = 1)\n",
" data = data[['OPEN','HIGH','LOW','CLOSE','VOLUME']]\n",
" return data"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 18
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"get_google_finance('AAPL')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\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",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2014-06-25 13:30:00</th>\n",
" <td> 90.2100</td>\n",
" <td> 90.2800</td>\n",
" <td> 90.2100</td>\n",
" <td> 90.2300</td>\n",
" <td> 362910</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:31:00</th>\n",
" <td> 90.2200</td>\n",
" <td> 90.3200</td>\n",
" <td> 90.1800</td>\n",
" <td> 90.2900</td>\n",
" <td> 315522</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:32:00</th>\n",
" <td> 90.3000</td>\n",
" <td> 90.3500</td>\n",
" <td> 90.2100</td>\n",
" <td> 90.2100</td>\n",
" <td> 201281</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:33:00</th>\n",
" <td> 90.2000</td>\n",
" <td> 90.2200</td>\n",
" <td> 89.6500</td>\n",
" <td> 89.8300</td>\n",
" <td> 1720753</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:34:00</th>\n",
" <td> 89.8295</td>\n",
" <td> 89.8900</td>\n",
" <td> 89.7800</td>\n",
" <td> 89.8351</td>\n",
" <td> 326972</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:35:00</th>\n",
" <td> 89.8300</td>\n",
" <td> 89.9000</td>\n",
" <td> 89.8000</td>\n",
" <td> 89.8400</td>\n",
" <td> 262885</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:36:00</th>\n",
" <td> 89.8400</td>\n",
" <td> 90.1900</td>\n",
" <td> 89.8100</td>\n",
" <td> 90.0900</td>\n",
" <td> 518114</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:37:00</th>\n",
" <td> 90.0850</td>\n",
" <td> 90.2900</td>\n",
" <td> 90.0010</td>\n",
" <td> 90.2500</td>\n",
" <td> 432227</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:38:00</th>\n",
" <td> 90.2600</td>\n",
" <td> 90.2900</td>\n",
" <td> 90.0400</td>\n",
" <td> 90.1001</td>\n",
" <td> 254484</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:39:00</th>\n",
" <td> 90.1100</td>\n",
" <td> 90.1800</td>\n",
" <td> 90.0500</td>\n",
" <td> 90.1600</td>\n",
" <td> 234494</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:40:00</th>\n",
" <td> 90.1300</td>\n",
" <td> 90.1740</td>\n",
" <td> 90.0600</td>\n",
" <td> 90.1600</td>\n",
" <td> 220604</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:41:00</th>\n",
" <td> 90.1600</td>\n",
" <td> 90.1799</td>\n",
" <td> 90.1080</td>\n",
" <td> 90.1500</td>\n",
" <td> 120848</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:42:00</th>\n",
" <td> 90.1500</td>\n",
" <td> 90.1800</td>\n",
" <td> 90.0900</td>\n",
" <td> 90.1448</td>\n",
" <td> 105612</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:43:00</th>\n",
" <td> 90.1400</td>\n",
" <td> 90.1700</td>\n",
" <td> 90.1100</td>\n",
" <td> 90.1400</td>\n",
" <td> 73700</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:44:00</th>\n",
" <td> 90.1400</td>\n",
" <td> 90.2400</td>\n",
" <td> 90.1200</td>\n",
" <td> 90.1700</td>\n",
" <td> 129717</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:45:00</th>\n",
" <td> 90.1800</td>\n",
" <td> 90.3300</td>\n",
" <td> 90.1700</td>\n",
" <td> 90.3200</td>\n",
" <td> 153911</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:46:00</th>\n",
" <td> 90.3201</td>\n",
" <td> 90.3300</td>\n",
" <td> 90.2200</td>\n",
" <td> 90.2600</td>\n",
" <td> 208784</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:47:00</th>\n",
" <td> 90.2600</td>\n",
" <td> 90.3000</td>\n",
" <td> 90.2500</td>\n",
" <td> 90.2500</td>\n",
" <td> 99326</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:48:00</th>\n",
" <td> 90.2500</td>\n",
" <td> 90.2600</td>\n",
" <td> 90.2000</td>\n",
" <td> 90.2100</td>\n",
" <td> 95772</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:49:00</th>\n",
" <td> 90.2000</td>\n",
" <td> 90.2100</td>\n",
" <td> 90.1200</td>\n",
" <td> 90.1395</td>\n",
" <td> 97774</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:50:00</th>\n",
" <td> 90.1300</td>\n",
" <td> 90.1900</td>\n",
" <td> 90.1200</td>\n",
" <td> 90.1700</td>\n",
" <td> 100114</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:51:00</th>\n",
" <td> 90.1801</td>\n",
" <td> 90.2000</td>\n",
" <td> 90.1500</td>\n",
" <td> 90.1539</td>\n",
" <td> 66920</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:52:00</th>\n",
" <td> 90.1500</td>\n",
" <td> 90.2100</td>\n",
" <td> 90.1400</td>\n",
" <td> 90.2000</td>\n",
" <td> 113604</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:53:00</th>\n",
" <td> 90.2020</td>\n",
" <td> 90.3000</td>\n",
" <td> 90.2000</td>\n",
" <td> 90.2899</td>\n",
" <td> 145378</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:54:00</th>\n",
" <td> 90.2850</td>\n",
" <td> 90.4900</td>\n",
" <td> 90.2800</td>\n",
" <td> 90.4600</td>\n",
" <td> 236207</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:55:00</th>\n",
" <td> 90.4500</td>\n",
" <td> 90.4900</td>\n",
" <td> 90.4200</td>\n",
" <td> 90.4500</td>\n",
" <td> 142003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:56:00</th>\n",
" <td> 90.4600</td>\n",
" <td> 90.4650</td>\n",
" <td> 90.2950</td>\n",
" <td> 90.3050</td>\n",
" <td> 137396</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:57:00</th>\n",
" <td> 90.3050</td>\n",
" <td> 90.4000</td>\n",
" <td> 90.2950</td>\n",
" <td> 90.3939</td>\n",
" <td> 67932</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:58:00</th>\n",
" <td> 90.4000</td>\n",
" <td> 90.4500</td>\n",
" <td> 90.3700</td>\n",
" <td> 90.4500</td>\n",
" <td> 135994</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-06-25 13:59:00</th>\n",
" <td> 90.4500</td>\n",
" <td> 90.7000</td>\n",
" <td> 90.4400</td>\n",
" <td> 90.5410</td>\n",
" <td> 321592</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 15:56:00</th>\n",
" <td> 94.8210</td>\n",
" <td> 94.8800</td>\n",
" <td> 94.8140</td>\n",
" <td> 94.8790</td>\n",
" <td> 38009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 15:57:00</th>\n",
" <td> 94.8710</td>\n",
" <td> 94.8800</td>\n",
" <td> 94.8100</td>\n",
" <td> 94.8350</td>\n",
" <td> 32632</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 15:58:00</th>\n",
" <td> 94.8399</td>\n",
" <td> 94.8399</td>\n",
" <td> 94.7200</td>\n",
" <td> 94.7500</td>\n",
" <td> 129498</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 15:59:00</th>\n",
" <td> 94.7500</td>\n",
" <td> 94.7510</td>\n",
" <td> 94.6800</td>\n",
" <td> 94.7253</td>\n",
" <td> 85007</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:00:00</th>\n",
" <td> 94.7200</td>\n",
" <td> 94.8300</td>\n",
" <td> 94.7200</td>\n",
" <td> 94.7900</td>\n",
" <td> 73925</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:01:00</th>\n",
" <td> 94.7900</td>\n",
" <td> 94.8000</td>\n",
" <td> 94.7500</td>\n",
" <td> 94.7699</td>\n",
" <td> 43186</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:02:00</th>\n",
" <td> 94.7641</td>\n",
" <td> 94.8500</td>\n",
" <td> 94.7600</td>\n",
" <td> 94.8100</td>\n",
" <td> 55349</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:03:00</th>\n",
" <td> 94.8070</td>\n",
" <td> 94.8400</td>\n",
" <td> 94.7900</td>\n",
" <td> 94.8050</td>\n",
" <td> 44061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:04:00</th>\n",
" <td> 94.8001</td>\n",
" <td> 94.8200</td>\n",
" <td> 94.7800</td>\n",
" <td> 94.8200</td>\n",
" <td> 25474</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:05:00</th>\n",
" <td> 94.8150</td>\n",
" <td> 94.8199</td>\n",
" <td> 94.7600</td>\n",
" <td> 94.7700</td>\n",
" <td> 43902</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:06:00</th>\n",
" <td> 94.7700</td>\n",
" <td> 94.7750</td>\n",
" <td> 94.6947</td>\n",
" <td> 94.7200</td>\n",
" <td> 84247</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:07:00</th>\n",
" <td> 94.7200</td>\n",
" <td> 94.7300</td>\n",
" <td> 94.6500</td>\n",
" <td> 94.6750</td>\n",
" <td> 73388</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:08:00</th>\n",
" <td> 94.6800</td>\n",
" <td> 94.6800</td>\n",
" <td> 94.6400</td>\n",
" <td> 94.6550</td>\n",
" <td> 109110</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:09:00</th>\n",
" <td> 94.6500</td>\n",
" <td> 94.7200</td>\n",
" <td> 94.6301</td>\n",
" <td> 94.7153</td>\n",
" <td> 70664</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:10:00</th>\n",
" <td> 94.7100</td>\n",
" <td> 94.8100</td>\n",
" <td> 94.7000</td>\n",
" <td> 94.7600</td>\n",
" <td> 73352</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:11:00</th>\n",
" <td> 94.7700</td>\n",
" <td> 94.8000</td>\n",
" <td> 94.7700</td>\n",
" <td> 94.7901</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:12:00</th>\n",
" <td> 94.7999</td>\n",
" <td> 94.8500</td>\n",
" <td> 94.7999</td>\n",
" <td> 94.8500</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:13:00</th>\n",
" <td> 94.8499</td>\n",
" <td> 94.8700</td>\n",
" <td> 94.8410</td>\n",
" <td> 94.8601</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:14:00</th>\n",
" <td> 94.8650</td>\n",
" <td> 94.9000</td>\n",
" <td> 94.8400</td>\n",
" <td> 94.8517</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:15:00</th>\n",
" <td> 94.8550</td>\n",
" <td> 94.9199</td>\n",
" <td> 94.8449</td>\n",
" <td> 94.9199</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:16:00</th>\n",
" <td> 94.9100</td>\n",
" <td> 94.9150</td>\n",
" <td> 94.8600</td>\n",
" <td> 94.8899</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:17:00</th>\n",
" <td> 94.8900</td>\n",
" <td> 94.8950</td>\n",
" <td> 94.8200</td>\n",
" <td> 94.8834</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:18:00</th>\n",
" <td> 94.8834</td>\n",
" <td> 94.9200</td>\n",
" <td> 94.8600</td>\n",
" <td> 94.9156</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:19:00</th>\n",
" <td> 94.9199</td>\n",
" <td> 94.9500</td>\n",
" <td> 94.9100</td>\n",
" <td> 94.9400</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:20:00</th>\n",
" <td> 94.9400</td>\n",
" <td> 94.9900</td>\n",
" <td> 94.9400</td>\n",
" <td> 94.9700</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:21:00</th>\n",
" <td> 94.9650</td>\n",
" <td> 94.9650</td>\n",
" <td> 94.9100</td>\n",
" <td> 94.9499</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:22:00</th>\n",
" <td> 94.9500</td>\n",
" <td> 94.9614</td>\n",
" <td> 94.9500</td>\n",
" <td> 94.9500</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:23:00</th>\n",
" <td> 94.9550</td>\n",
" <td> 94.9550</td>\n",
" <td> 94.8750</td>\n",
" <td> 94.8884</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:24:00</th>\n",
" <td> 94.8800</td>\n",
" <td> 94.8800</td>\n",
" <td> 94.7666</td>\n",
" <td> 94.7734</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-08-05 16:25:00</th>\n",
" <td> 94.7700</td>\n",
" <td> 94.7900</td>\n",
" <td> 94.7034</td>\n",
" <td> 94.7100</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10939 rows \u00d7 5 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 19,
"text": [
" OPEN HIGH LOW CLOSE VOLUME\n",
"2014-06-25 13:30:00 90.2100 90.2800 90.2100 90.2300 362910\n",
"2014-06-25 13:31:00 90.2200 90.3200 90.1800 90.2900 315522\n",
"2014-06-25 13:32:00 90.3000 90.3500 90.2100 90.2100 201281\n",
"2014-06-25 13:33:00 90.2000 90.2200 89.6500 89.8300 1720753\n",
"2014-06-25 13:34:00 89.8295 89.8900 89.7800 89.8351 326972\n",
"2014-06-25 13:35:00 89.8300 89.9000 89.8000 89.8400 262885\n",
"2014-06-25 13:36:00 89.8400 90.1900 89.8100 90.0900 518114\n",
"2014-06-25 13:37:00 90.0850 90.2900 90.0010 90.2500 432227\n",
"2014-06-25 13:38:00 90.2600 90.2900 90.0400 90.1001 254484\n",
"2014-06-25 13:39:00 90.1100 90.1800 90.0500 90.1600 234494\n",
"2014-06-25 13:40:00 90.1300 90.1740 90.0600 90.1600 220604\n",
"2014-06-25 13:41:00 90.1600 90.1799 90.1080 90.1500 120848\n",
"2014-06-25 13:42:00 90.1500 90.1800 90.0900 90.1448 105612\n",
"2014-06-25 13:43:00 90.1400 90.1700 90.1100 90.1400 73700\n",
"2014-06-25 13:44:00 90.1400 90.2400 90.1200 90.1700 129717\n",
"2014-06-25 13:45:00 90.1800 90.3300 90.1700 90.3200 153911\n",
"2014-06-25 13:46:00 90.3201 90.3300 90.2200 90.2600 208784\n",
"2014-06-25 13:47:00 90.2600 90.3000 90.2500 90.2500 99326\n",
"2014-06-25 13:48:00 90.2500 90.2600 90.2000 90.2100 95772\n",
"2014-06-25 13:49:00 90.2000 90.2100 90.1200 90.1395 97774\n",
"2014-06-25 13:50:00 90.1300 90.1900 90.1200 90.1700 100114\n",
"2014-06-25 13:51:00 90.1801 90.2000 90.1500 90.1539 66920\n",
"2014-06-25 13:52:00 90.1500 90.2100 90.1400 90.2000 113604\n",
"2014-06-25 13:53:00 90.2020 90.3000 90.2000 90.2899 145378\n",
"2014-06-25 13:54:00 90.2850 90.4900 90.2800 90.4600 236207\n",
"2014-06-25 13:55:00 90.4500 90.4900 90.4200 90.4500 142003\n",
"2014-06-25 13:56:00 90.4600 90.4650 90.2950 90.3050 137396\n",
"2014-06-25 13:57:00 90.3050 90.4000 90.2950 90.3939 67932\n",
"2014-06-25 13:58:00 90.4000 90.4500 90.3700 90.4500 135994\n",
"2014-06-25 13:59:00 90.4500 90.7000 90.4400 90.5410 321592\n",
"... ... ... ... ... ...\n",
"2014-08-05 15:56:00 94.8210 94.8800 94.8140 94.8790 38009\n",
"2014-08-05 15:57:00 94.8710 94.8800 94.8100 94.8350 32632\n",
"2014-08-05 15:58:00 94.8399 94.8399 94.7200 94.7500 129498\n",
"2014-08-05 15:59:00 94.7500 94.7510 94.6800 94.7253 85007\n",
"2014-08-05 16:00:00 94.7200 94.8300 94.7200 94.7900 73925\n",
"2014-08-05 16:01:00 94.7900 94.8000 94.7500 94.7699 43186\n",
"2014-08-05 16:02:00 94.7641 94.8500 94.7600 94.8100 55349\n",
"2014-08-05 16:03:00 94.8070 94.8400 94.7900 94.8050 44061\n",
"2014-08-05 16:04:00 94.8001 94.8200 94.7800 94.8200 25474\n",
"2014-08-05 16:05:00 94.8150 94.8199 94.7600 94.7700 43902\n",
"2014-08-05 16:06:00 94.7700 94.7750 94.6947 94.7200 84247\n",
"2014-08-05 16:07:00 94.7200 94.7300 94.6500 94.6750 73388\n",
"2014-08-05 16:08:00 94.6800 94.6800 94.6400 94.6550 109110\n",
"2014-08-05 16:09:00 94.6500 94.7200 94.6301 94.7153 70664\n",
"2014-08-05 16:10:00 94.7100 94.8100 94.7000 94.7600 73352\n",
"2014-08-05 16:11:00 94.7700 94.8000 94.7700 94.7901 0\n",
"2014-08-05 16:12:00 94.7999 94.8500 94.7999 94.8500 0\n",
"2014-08-05 16:13:00 94.8499 94.8700 94.8410 94.8601 0\n",
"2014-08-05 16:14:00 94.8650 94.9000 94.8400 94.8517 0\n",
"2014-08-05 16:15:00 94.8550 94.9199 94.8449 94.9199 0\n",
"2014-08-05 16:16:00 94.9100 94.9150 94.8600 94.8899 0\n",
"2014-08-05 16:17:00 94.8900 94.8950 94.8200 94.8834 0\n",
"2014-08-05 16:18:00 94.8834 94.9200 94.8600 94.9156 0\n",
"2014-08-05 16:19:00 94.9199 94.9500 94.9100 94.9400 0\n",
"2014-08-05 16:20:00 94.9400 94.9900 94.9400 94.9700 0\n",
"2014-08-05 16:21:00 94.9650 94.9650 94.9100 94.9499 0\n",
"2014-08-05 16:22:00 94.9500 94.9614 94.9500 94.9500 0\n",
"2014-08-05 16:23:00 94.9550 94.9550 94.8750 94.8884 0\n",
"2014-08-05 16:24:00 94.8800 94.8800 94.7666 94.7734 0\n",
"2014-08-05 16:25:00 94.7700 94.7900 94.7034 94.7100 0\n",
"\n",
"[10939 rows x 5 columns]"
]
}
],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment