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from bs4 import BeautifulSoup
import requests
import pandas as pd
def get_fund_prices():
#Getting list of funds:
fundList = requests.get('')
soup = BeautifulSoup(fundList.text, 'html.parser')
isins = []
#Listing all fund names and ISIN codes
for tr in soup.find_all('tr'):
if len(tr)>10 :
fundName = tr.find_all('td')[1].text
sep = str(tr.a).find('isin=') + 5
isins.append([fundName, str(tr.a)[sep:sep+12]])
funds = pd.DataFrame(isins, columns=list(['Fund Name','ISIN']))
print('List of ISINs and fund names gathered!\n')
#Getting the prices for each ISIN
prices = []
for isin in isins:
temp = []
pricePage = requests.get('' + isin[1])
soup = BeautifulSoup(pricePage.text, 'html.parser')
txt = str(soup.find_all('script'))[str(soup.find_all('script')).find('function convertDate(date) {')+159:str(soup.find_all('script')).find('initChart(min,seriesdata,isin,valuuta')-1]
txt = txt.replace('\n','')
txt = txt.replace('convertDate(','')
txt = txt.replace(')','')
txt = txt.replace('removeNegatives(','')
txt = txt[1:txt.find(',isin')]
temp = txt.split('],[')
if len(temp)>1000:
for p in temp:
if len(p)>0:
prices.append([isin[0], isin[1], str(p[1:5]) + '-' + str(p[5:7]) + '-' + str(p[7:9]), str(p[11:])])
print('Prices for {} have been gathered!'.format(isin[0]))
#Some basic data cleaning:
print('\nCleaning prices...')
for p in prices:
p[3] = p[3].replace(']','')
data = pd.DataFrame(prices, columns=list(['Fund Name','ISIN','DATE','PRICE']))
result = data.pivot(index = 'DATE', columns = 'ISIN', values = 'PRICE')
result = result.apply(pd.to_numeric, errors='ignore')
result = result.dropna(how = 'any')
gains = result.pct_change()
riskSTD = gains.std()
#Saving everything to one MS Excel file
print('Saving data to CSV files')
funds.to_csv('FUND LIST.csv')
print('\nImport process completed!')
return result
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