Retrieve intraday stock data from Google Finance.

google_finance_intraday.py

#!/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_google_finance_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 = ['Open', 'High', 'Low', 'Close', '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'))

what is the symbol for NIFTY50 data

what is the symbol for NIFTY50 data

Yahoo finance symbol for nifty 50 = '^NSEI'

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol , data_range='1d', data_interval='1m'):
res = requests.get('https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?range={data_range}&interval={data_interval}'.format(**locals()))
data = res.json()
body = data['chart']['result'][0]
dt = datetime.datetime
dt = pd.Series(map(lambda x: arrow.get(x).to('Asia/Calcutta').datetime.replace(tzinfo=None), body['timestamp']), name='Datetime')
df = pd.DataFrame(body['indicators']['quote'][0], index=dt)
dg = pd.DataFrame(body['timestamp'])
df = df.loc[:, ('open', 'high', 'low', 'close', 'volume')]
df.dropna(inplace=True)
df.columns = ['OPEN', 'HIGH','LOW','CLOSE','VOLUME']

return df

for s in symbol:
data = get_quote_data(s,'1d','1m')
data.to_csv(s.strip(".NS")+'.csv')

this is for multiple stock symbols