def getdataForMultipleTickers(tickerlist,start_date,end_date,dataset,company_name, company):
combineddataset= web.DataReader(tickerlist,'yahoo',start_date,end_date)
print("\n"+"*" *100)
option = input("Choose\n1. For Basic Statistics View\n2. For Graphical View\n3. Previous Menu\n")
print("\n"+"*" *100)
try:
if option == "1":
closeDataCombined = combineddataset['Close']
print("Descriptive Analytics done on Close Price for Combined dataset:\n ",closeDataCombined.describe())
getdataForMultipleTickers(tickerlist,start_date,end_date,dataset,company_name, company)
elif option == "2":
companyValues = "Multiple Companies"
simple_moving_avg(combineddataset,start_date,end_date,companyValues)
close = combineddataset['Close']
close = close.fillna(method='ffill')
ct.drawplot(close,title =f"Raw Time Series for closing price of {company}")
getdataForMultipleTickers(tickerlist,start_date,end_date,dataset,company_name, company)
elif option == "3":
descriptive_mode(dataset,start_date,end_date,company_name,company)
else:
print("Please select correct option")
getdataForMultipleTickers(tickerlist,start_date,end_date,dataset,company_name, company)
except ValueError:
print("Select from below the options")
getdataForMultipleTickers(tickerlist,start_date,end_date,dataset,company_name, company)
def exponential_Weighted_MA(dataset, start_date, end_date, company_name):
try:
window_size = int(
input(
"Enter the n value for Weighted Moving Average, i.e Window size \n"
))
if window_size > 250:
window_size = 100
dataset['wm_avg'] = dataset['Adj Close'].ewm(span=window_size,
min_periods=0,
adjust=True,
ignore_na=True).mean()
ct.drawplot(
dataset['wm_avg'],
title=
f"Exponential Weighted Moving Average of {company_name} for window size {window_size}"
)
except ValueError:
print("The window size should be a number ")
exponential_Weighted_MA(dataset, start_date, end_date, company_name)
except:
print(
"Window size is to small test expect result for greater range values"
)
exponential_Weighted_MA(dataset, start_date, end_date, company_name)
def MACD(dataset,start_date,end_date,company_name):
close_26_ewma = dataset['Adj Close'].ewm(span=26, min_periods=0, adjust=True, ignore_na=True).mean()
close_12_ewma = dataset['Adj Close'].ewm(span=12, min_periods=0, adjust=True, ignore_na=True).mean()
dataset['26ema'] = close_26_ewma
dataset['12ema'] = close_12_ewma
dataset['MACD'] = (dataset['12ema'] - dataset['26ema'])
ct.drawplot(dataset['MACD'],title =f"Moving Average Convergence Divergence (MACD) of {company_name}")
def simple_moving_avg(dataset, start_date, end_date, company_name):
try:
window_size = int(
input("Enter the n value for Moving Average i.e Window size\n"))
if window_size > 250:
window_size = 100
#print(rolling.head(20))
rolling = dataset['Adj Close'].rolling(window=int(window_size)).mean()
ct.drawplot(
rolling,
title=
f"Simple Moving Average of {company_name} for rolling window size {window_size}"
)
print("Window size is not able to fit the graph")
except ValueError:
print("The window size should be a number ")
simple_moving_avg(dataset, start_date, end_date, company_name)
except:
print(
"Window size is to small test expect result for greater range values"
)
simple_moving_avg(dataset, start_date, end_date, company_name)