I'm a programmer and recently I'm approaching to the world of trading. Now I'm attempting to obtain historical data of AAPL. This is code for obtaining historical data from Quandl:
import datetime
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
pd.options.display.max_rows = 99999
import quandl
quandl.ApiConfig.api_key = "PersonalCode"
dataset_quandl = quandl.get('AAPL', start_date="2018-01-01", end_date="2018-12-31")
dataset_quandl = dataset_quandl.iloc[:,:4]
dataset_quandl.columns = ["open","high","low","close"]
dataset_quandl.head(10)
And i will obtain the following DataFrame:
If i try to download the same data from Yahoo Finance, i will read totally different prices:
import ffn
dataset_ffn = ffn.get('aapl:Open,aapl:High,aapl:Low,aapl:Close', start='2018-01-01', end='2018-12-31')
dataset_ffn.columns = ["open","high","low","close"]
dataset_ffn = dataset_ffn.apply(lambda x: round(x,2))
dataset_ffn.head(10)
I would like to know what is the reason for this difference. How I should behave in these cases?
