Grabbing per minute stock data from a large time range Python

Question

So I'm trying to grab per minute stock data over a one year time gap and I know the Google Finance API doesn't work anymore so I did some digging around I found some code from a old github thread that could find the range within 5 days from yahoo finance data; however, it does not do anymore than that even when I put a keyword like '1Y' which defaults to 1 day. Here is the code below:

import requests
import pandas as pd
import arrow
import datetime
import os

def get_quote_data(symbol='AAPL', data_range='5d', 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).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

Answer 1

body['meta']['validRanges'] tells you:

['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']

You are requesting 1Y instead of 1y. This difference is important.

By the way you can load the timestamps much more easily like this:

pd.to_datetime(body['timestamp'], unit='s')