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'))

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', 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)     #removing NaN rows
    df.columns = ['OPEN', 'HIGH','LOW','CLOSE','VOLUME']    #Renaming columns in pandas
    
    return df

data = get_quote_data('KPIT.NS', '1d', '1m')
print(data)

Does anyone know why yahoo does not provide 30 minute data? I know that 1, 15, 60 work fine but not 30m.

how do you get 1, 15, 60 minute data from yahoo?

using the script posted just before my question.

The code above by kongaraman is wonderful. thanks for posting.

Thanks ynagendra

I noticed that yahoo data is not constant. For 1 minute, i observed that data gives differently for the same time period.

When i run the above python code, it should be the same for data, as long as i run any number of times.

Can someone have idea on this? Also this data is not exactly matching to actual exchange data.

I am not sure, why there is a difference. If anybody have idea then please post your comments.

Observed that there are many empty values while extracting data.

So i used df.dropna(inplace=True) #removing NaN rows

Infact the above line is not needed. We need to get good quality data, which is missing from above link.

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', 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)     #removing NaN rows
    df.columns = ['OPEN', 'HIGH','LOW','CLOSE','VOLUME']    #Renaming columns in pandas
    
    return df

data = get_quote_data('KPIT.NS', '1d', '1m')
print(data)

Hi,
I am getting error ModuleNotFoundError: No module named 'arrow'. I have installed arrow module, still it throws this error

Thanks for great ideas.
I tried to apply kongaraman function on a list of stock tickers. when i pplied a for loop, i got the follwing error:

TypeError: 'NoneType' object has no attribute 'getitem'

HI All,
The yahoo finance API seems to be stuck at March 28th 2019 and not returning any data post that. I am trying to import data for the NIFTYBANK NSE Index and also tried for other stocks as well. Are others also facing the same problem and can anyone suggest some alternatives for 1minute Data Provider for NSE Stocks.
Thanks,
Rajesh

Hi.
Was anyone able to get hourly information on stock prices, either individual or by S&P?

seems to have stopped working, now isnt returning anything - could be me of course

URL is http://www.google.com/finance/getprices?i=60&p=1d&f=d,o,h,l,c,v&df=cpct&q=VOD&x=LON
Empty DataFrame
Columns: []
Index: []
done

when I run that URL in the browser, it thinks I'm a bot and shuts me down, any way around that please ?

ta

that url failed for me as well.

We're sorry...
... but your computer or network may be sending automated queries. To protect our users, we can't process your request right now.

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', 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)     #removing NaN rows
    df.columns = ['OPEN', 'HIGH','LOW','CLOSE','VOLUME']    #Renaming columns in pandas
    
    return df

data = get_quote_data('KPIT.NS', '1d', '1m')
print(data)

Works great, but is there a way to save this data to a CSV file?

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', 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)     #removing NaN rows
    df.columns = ['OPEN', 'HIGH','LOW','CLOSE','VOLUME']    #Renaming columns in pandas
    
    return df

data = get_quote_data('KPIT.NS', '1d', '1m')
print(data)

Works great, but is there a way to save this data to a CSV file?

data.to_csv('output.csv')

To sum up this string..
Step 1: Install python: https://www.python.org/downloads/
Step 2: Install panda: pip install panda
Step 3: Save this code:
'
import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', 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'])

return df.loc[:, ('open', 'high', 'low', 'close', 'volume')]

data = get_quote_data('SBIN.NS', '5d', '1m')
data.dropna(inplace=True) #removing NaN rows
print(data)
data.to_csv('output.csv')
'
Step 4: Drag the saved python file to CMD and an output CSV will be saved.

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