def get_surf(ticker):
q = Options(ticker, 'yahoo').get_all_data()
q.reset_index(inplace=True)
q.set_index('Symbol', inplace=True)
vals = []
print(q.head())
#Iterate through the DataFrame pulled from the API
for index, row in q.iterrows():
if row['Type'] == 'put':
underlying = float(row['Underlying_Price'])
#Midpoint of bid/ask spread
price = (float(row['Ask']) + float(row['Bid'])) / 2.0
exp_d = (row['Expiry'] - datetime.now()).days
exp_s = (row['Expiry'] - datetime.now()).seconds
exp = (exp_d * 24 * 3600 + exp_s) / (365 * 24 * 3600)
try:
#Calculate the implied volatility
impl = calc_impl_vol(price, 'p', underlying,
float(row['Strike']), exp)
vals.append([exp, float(row['Strike']), impl])
except:
pass
vals = array(vals).T
combine_plots(vals[0], vals[1], vals[2])
def get_one_ticker():
ticker=company.get()
option_data = Options(ticker,data_source='yahoo').get_all_data()
option_data.reset_index(inplace=True)
option_data.drop('JSON', axis=1, inplace=True)
print option_data
def get_one_ticker(one_ticker_name):
option_data = Options(one_ticker_name,data_source='yahoo').get_all_data()
option_data.reset_index(inplace=True)
option_data.drop('JSON', axis=1, inplace=True)
r=clean(option_data)
return r
