This post includes code adapted from python for finance and trading algorithms udemy course and python for finance and trading algorithms udemy course notebooks.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

import pandas_datareader.data as web
import datetime

start = datetime.datetime(2020, 1, 1)
end = pd.to_datetime('today')

AAPL_stock = web.DataReader('AAPL', 'yahoo', start, end)
AAPL_stock.head()

MSFT_stock = web.DataReader('MSFT', 'yahoo', start, end)
MSFT_stock.head()

ZOOM_stock = web.DataReader('ZM', 'yahoo', start, end)
ZOOM_stock.head()

SNOW_stock = web.DataReader('SNOW', 'yahoo', start, end)
SNOW_stock.head()
High Low Open Close Volume Adj Close
Date
2020-09-16 319.0 231.110001 245.000000 253.929993 36099700 253.929993
2020-09-17 241.5 215.240005 230.759995 227.539993 11907500 227.539993
2020-09-18 249.0 218.589996 235.000000 240.000000 7475400 240.000000
2020-09-21 241.5 218.600006 230.000000 228.850006 5524900 228.850006
2020-09-22 239.0 225.149994 238.500000 235.160004 3889100 235.160004 
fig = plt.figure(figsize=(12, 6))
plt.title('Open')

MSFT_stock['Open'].plot(label='Microsoft')
ZOOM_stock['Open'].plot(label='Zoom')
SNOW_stock['Open'].plot(label='Snowflake')
AAPL_stock['Open'].plot(label='Apple')
plt.legend()

fig = plt.figure(figsize=(12, 6))
plt.title('Volume')

MSFT_stock['Volume'].plot(label='Microsoft')
ZOOM_stock['Volume'].plot(label='Zoom')
SNOW_stock['Volume'].plot(label='Snowflake')
AAPL_stock['Volume'].plot(label='Apple')

plt.legend()

<matplotlib.legend.Legend at 0x7f3e5dc577f0>
import pandas_datareader.data as web

import datetime



gdp = web.DataReader("GDP", "fred", start, end)

gdp.head()
GDP
DATE
2020-01-01 21561.139
2020-04-01 19520.114
2020-07-01 21170.252 
import quandl

#quandl.ApiConfig.api_key = ''

mydata = quandl.get("EIA/PET_RWTC_D")

mydata.head()

---------------------------------------------------------------------------
LimitExceededError                        Traceback (most recent call last)
<ipython-input-10-68997e6ce84c> in <module>
----> 1 mydata = quandl.get("EIA/PET_RWTC_D")
      2 
      3 mydata.head()

~/anaconda3/lib/python3.8/site-packages/quandl/get.py in get(dataset, **kwargs)
     46         if dataset_args['column_index'] is not None:
     47             kwargs.update({'column_index': dataset_args['column_index']})
---> 48         data = Dataset(dataset_args['code']).data(params=kwargs, handle_column_not_found=True)
     49     # Array
     50     elif isinstance(dataset, list):

~/anaconda3/lib/python3.8/site-packages/quandl/model/dataset.py in data(self, **options)
     45         updated_options = Util.merge_options('params', params, **options)
     46         try:
---> 47             return Data.all(**updated_options)
     48         except NotFoundError:
     49             if handle_not_found_error:

~/anaconda3/lib/python3.8/site-packages/quandl/operations/list.py in all(cls, **options)
     13             options['params'] = {}
     14         path = Util.constructed_path(cls.list_path(), options['params'])
---> 15         r = Connection.request('get', path, **options)
     16         response_data = r.json()
     17         Util.convert_to_dates(response_data)

~/anaconda3/lib/python3.8/site-packages/quandl/connection.py in request(cls, http_verb, url, **options)
     36         abs_url = '%s/%s' % (ApiConfig.api_base, url)
     37 
---> 38         return cls.execute_request(http_verb, abs_url, **options)
     39 
     40     @classmethod

~/anaconda3/lib/python3.8/site-packages/quandl/connection.py in execute_request(cls, http_verb, url, **options)
     48                                        **options)
     49             if response.status_code < 200 or response.status_code >= 300:
---> 50                 cls.handle_api_error(response)
     51             else:
     52                 return response

~/anaconda3/lib/python3.8/site-packages/quandl/connection.py in handle_api_error(cls, resp)
    112         klass = d_klass.get(code_letter, QuandlError)
    113 
--> 114         raise klass(message, resp.status_code, resp.text, resp.headers, code)

LimitExceededError: (Status 429) (Quandl Error QELx01) You have exceeded the anonymous user limit of 50 calls per day. To make more calls today, please register for a free Quandl account and then include your API key with your requests.
mydata.plot(figsize=(12,6))

#mydata = quandl.get("EIA/PET_RWTC_D", returns="numpy",start_date=start,end_date=end)

mydata = quandl.get("FRED/GDP",start_date=start,end_date=end)

mydata.head()

mydata = quandl.get(["NSE/OIL.1", "WIKI/AAPL.4"],start_date=start,end_date=end)

mydata.head()
NSE/OIL - Open WIKI/AAPL - Close 
mydata = quandl.get("FRED/GDP")

mydata = quandl.get('WIKI/FB',start_date=start,end_date=end)

mydata.head()
Open High Low Close Volume Ex-Dividend Split Ratio Adj. Open Adj. High Adj. Low Adj. Close Adj. Volume
Date 
mydata = quandl.get('WIKI/FB.1',start_date=start,end_date=end)

mydata.head()
Open
Date 
mydata = quandl.get('WIKI/FB.7',start_date=start,end_date=end)
mydata.head()
Split Ratio
Date 
# Homes

houses = quandl.get('ZILLOW/M11_ZRIAH',start_date=start,end_date=end)

houses.head()
Value
Date
2020-01-31 3342.0
2020-02-29 3358.0 
houses.plot()

<matplotlib.axes._subplots.AxesSubplot at 0x7f900d58fef0>