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Retrieve intraday stock data from Google Finance.
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#!/usr/bin/env python | |
""" | |
Retrieve intraday stock data from Google Finance. | |
""" | |
import csv | |
import datetime | |
import re | |
import pandas as pd | |
import requests | |
def get_intraday(ticker, period=60, days=1): | |
""" | |
Retrieve intraday stock data from Google Finance. | |
Parameters | |
---------- | |
ticker : str | |
Company ticker symbol. | |
period : int | |
Interval between stock values in seconds. | |
days : int | |
Number of days of data to retrieve. | |
Returns | |
------- | |
df : pandas.DataFrame | |
DataFrame containing the opening price, high price, low price, | |
closing price, and volume. The index contains the times associated with | |
the retrieved price values. | |
""" | |
uri = 'http://www.google.com/finance/getprices' \ | |
'?i={period}&p={days}d&f=d,o,h,l,c,v&df=cpct&q={ticker}'.format(ticker=ticker, | |
period=period, | |
days=days) | |
page = requests.get(uri) | |
reader = csv.reader(page.content.splitlines()) | |
columns = ['Close', 'High', 'Low', 'Open', 'Volume'] | |
rows = [] | |
times = [] | |
for row in reader: | |
if re.match('^[a\d]', row[0]): | |
if row[0].startswith('a'): | |
start = datetime.datetime.fromtimestamp(int(row[0][1:])) | |
times.append(start) | |
else: | |
times.append(start+datetime.timedelta(seconds=period*int(row[0]))) | |
rows.append(map(float, row[1:])) | |
if len(rows): | |
return pd.DataFrame(rows, index=pd.DatetimeIndex(times, name='Date'), | |
columns=columns) | |
else: | |
return pd.DataFrame(rows, index=pd.DatetimeIndex(times, name='Date')) |
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Example of usage:
>>> get_google_finance_intraday('TATASTEEL')
Returns 1min intraday day for TATASTEEL