def get_options_dict(ticker_list,warm_dict=None):
if not warm_dict:
tdict={}
else:
tdict=warm_dict
for ticker in ticker_list:
if not tdict.has_key(ticker):
print '****\n****\n**** getting for %s\n****\n****' % ticker
op = Options(ticker, 'yahoo')
try:
data = op.get_all_data()
up = op.underlying_price
time.sleep(1200)
tdict[ticker]={'data':data,'up':up}
except pd.io.data.RemoteDataError:
print'Request Refused, Dumping and Exiting...'
cPickle.dump(tdict,open('warm_dict.pkl','wb'))
sys.exit(0)
return tdict
def __validate_source_connection__(self):
""" Check internet connection """
test_stock = 'AAPL'
try:
aapl = Options(test_stock, self.source)
data = aapl.get_all_data()
return True
except Exception:
return False
def __validate_source_connection__(self):
""" Check internet connection """
test_stock='AAPL'
try:
aapl = Options(test_stock, self.source)
data = aapl.get_all_data()
return True
except Exception:
return False
def retrieve_option_chain(ticker="SPY"):
spy_data = pandas.DataFrame()
print(" --> Today's option chain not on system: downloading it now... ")
try:
spy_options = Options(ticker, "yahoo")
spy_data = spy_options.get_all_data()
spy_data = spy_data.reset_index()
if "Symbol" in spy_data.keys():
spy_data = spy_data.set_index("Symbol")
spy_data.to_csv(filename, date_format="%Y-%m-%d")
# Load the data from the CSV you just wrote
# (this ensures that re-shaping is always done
# by retrieve_option_chain_from_file() )
spy_data = retrieve_option_chain_from_file(filename)
except:
print("Error with retrieving data. Please double-check the ticker symbol")
return spy_data
return spy_data
def pull_data(self, ticket_list):
"""
Pull online option data
:param ticket_list: list contains tickets you want to download
:return: option data dict, in the form of [ ticket : DataFrame, ... ]
"""
if isinstance(ticket_list, str):
ticket_list = (ticket_list, )
option_dict = {}
for ticket in ticket_list:
print "Pull Option Data : %s ..." % ticket
try:
option_method = Options(ticket, self.source)
option_dict[ticket] = option_method.get_all_data()
if len(option_dict[ticket]) == 0:
print "Length of data is Zero during the time asked"
except Exception as err_message:
option_dict[ticket] = None
print "Exception: %s" % err_message
# raise RuntimeError("Can't not download Stock: %s" % stock)
return option_dict
def pull_data(self, ticket_list):
"""
Pull online option data
:param ticket_list: list contains tickets you want to download
:return: option data dict, in the form of [ ticket : DataFrame, ... ]
"""
if isinstance(ticket_list, str):
ticket_list = (ticket_list, )
option_dict = {}
for ticket in ticket_list:
print "Pull Option Data : %s ..." % ticket
try:
option_method = Options(ticket, self.source)
option_dict[ticket] = option_method.get_all_data()
if len(option_dict[ticket]) == 0:
print "Length of data is Zero during the time asked"
except Exception as err_message:
option_dict[ticket] = None
print "Exception: %s" % err_message
# raise RuntimeError("Can't not download Stock: %s" % stock)
return option_dict
start = dt.datetime(2015, 1, 1)
msi = web.DataReader('msi', 'yahoo', start)
msi['Close'].plot()
#%%
"""
Options data -- doesn't work
http://pandas.pydata.org/pandas-docs/stable/remote_data.html#yahoo-finance-options
"""
import pandas as pd
print('Pandas version:', pd.__version__)
from pandas.io.data import Options
aapl = Options('aapl', 'yahoo')
data = aapl.get_all_data()
#%%
"""
convert do file to pandas format and variable labels
CPS
http://www.nber.org/data/cps_progs.html
MEPS
http://meps.ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-155
"""
import pandas as pd
url = 'http://www.nber.org/data/progs/cps/cpsmar2014.dct'
pd.read_csv(url, sep='\s+')
#open(url).read()
def get_option_data(self, symbol):
aapl = Options(symbol, 'google')
data = aapl.get_all_data()
return data
"""
the usual checks
"""
import sys
import pandas as pd
print('\nPython version: ', sys.version)
print('\nPandas version: ', pd.__version__, '\n')
#%%
"""
Remote data access
"""
from pandas.io.data import Options
aapl = Options('aapl', 'yahoo')
data = aapl.get_all_data()
#%%
"""
Set up simple dataframes to play with
"""
# create arbitrary dataframe
gdp = [2, 5, 7, 9]
pop = [9, 6, 3, 10]
cty = ['USA', 'USA', 'FRA', 'FRA']
year = ['2010', '2011', '2012', '2013']
data = {'gdp': gdp, 'pop': pop, 'cty': cty}
df = pd.DataFrame(data=data, index=year)
from pandas.io.data import Options
spy = Options('spy', 'yahoo')
chain = spy.get_all_data()
