In [1]:
import pandas as pd
import investpy
In [ ]:
#pip install investpy==0.9.14
In [6]:
#Get list of all stocks traded in Chile
stock_list = investpy.get_stocks_list(country='chile')
stock_list.sort()
In [7]:
#Remove stocks with unavailable data
stock_list.remove('ANDROMACO')
stock_list.remove('GNC_old')
In [8]:
#FOr each stock, get its historical prices
for i in range(len(stock_list)):
    Ticker = str(stock_list[i])
    #if Ticker == 'AGUNSA':
     #break
    df = investpy.get_stock_historical_data(stock=Ticker,
                                        country='chile',
                                        from_date='01/01/1990',
                                        to_date='01/05/2020')
    
    df.insert(6,"Ticker", Ticker)
    all_stocks = pd.concat([all_stocks, df], axis=0)
In [ ]:
all_stocks.Ticker.unique()
In [10]:
#Export data to csv
all_stocks.to_csv('Stocks_Prices.csv',  decimal='.' , sep='\t', encoding='utf-8')
In [ ]:
stocks = ["AESGENER","AGUASA","AGUNSA","ALMENDRAL","ANDINAA","ANDINAB","ANTARCHILE","AQUACHILE","AUSTRALIS","BANMEDICA","BANVIDA","BCI","BESALCO","BLUMAR",
"BSANTANDER","CAMANCHACA","CAP","CCU","CEMENTOS","CENCOSUD","CHILE",
"CINTAC","CMPC","COLBUN","COLO COLO","COLOSO","CONCHATORO","COPEC","CRISTALES","ECL","EDELPA","EISA","EMBONOR-B","ENAEX","ENELAM","ENELCHILE","ENELGXCH","ENJOY","ENTEL",
"FALABELLA","FORUS","GASCO","HABITAT","HITES","IAM","ILC","INDISA","INGEVEC","INTEROCEAN","INVERCAP","INVERMAR","ITAUCORP","LAS CONDES","UPIGAS",
"LTM","MASISA","MINERA","MOLLER","MOLYMET","MULTIFOODS","NITRATOS",
"NORTEGRAN","NUEVAPOLAR","ORO BLANCO","PACIFICO","PARAUCO","PASUR","PAZ","PEHUENCHE","PUCOBRA","QUINENCO","RIPLEY","SALFACORP",
"SECURITY","SK","SMSAAM","SMU","SOCOVESA","SONDA","SOQUICOM","SQMA","SQMB","TRICOT","VAPORES","VSPT","WATTS","ZOFRI"
]