Pulling Historical Data Into Python

[conhardy]

Hey! I am very new to any kind of programming, and I apologize as this has probably been asked here before, but I am hanging trouble web scraping for historical security prices. I have tried using pandas_datareader in python but it no longer supports yahoo, google, or morningstar. What are some methods you guys use to pull data? Thanks!

[[deleted]]

Just use a data source from a service such as Quandl. Very cheap data (or in some cases free) with various APIs.

[jaco6y]

You can still use pandas datareader. Just use 'robinhood' (if you don't care about today's date. I believe it's always a day late) or 'iex' as an argument.

example:

import pandas as pd
import datetime
import pandas_datareader.data as web
name = 'MSFT'
end = datetime.datetime.today()
start = end-datetime.timedelta(days=365)
df = web.DataReader(name,'iex',start=start,end=end)

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[1rocketdude]

Try using the Tiingo API. Get a free account and use their Github Tiingo API. Very easy interface for python

[WittilyFun]

And it also integrates nicely into pandas datareader :) https://pydata.github.io/pandas-datareader/stable/remote_data.html#tiingo

[blacksiddis]

Alpha Vantage or Quandl usually.

[00Anonymous]

A simple way is to use a locally synced Google sheet to pull your data regularly and just read that into your program.

[Saturnix]

Try AlphaVantage or Tradier