import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
from pandas_datareader import data as pdr
import yfinance as yf


set100 = ['AAV', 'ACE', 'ADVANC', 'AEONTS', 'AMATA', 'AOT', 'AP', 'BAM', 'BANPU', 'BBL', 
          'BCH', 'BCP', 'BCPG', 'BDMS', 'BEC', 'BEM', 'BGRIM', 'BH', 'BJC', 'BTS', 
          'CBG', 'CENTEL', 'CHG', 'CK', '***', 'COM7', 'CPALL', 'CPF', 'CPN', 'CRC', 
          'DELTA', 'DOHOME', 'DTAC', 'EA', 'EGCO', 'ESSO', 'GLOBAL', 'GPSC', 'GULF', 'GUNKUL', 
          'HANA', 'HMPRO', 'ICHI', 'INTUCH', 'IRPC', 'IVL', 'JAS', 'JMART', 'JMT', 'KBANK', 
          'KCE', 'KKP', 'KTB', 'KTC', 'LH', 'MAJOR', 'MEGA', 'MINT', 'MTC', 'NRF', 
          'OR', 'ORI', 'OSP', 'PLANB', 'PRM', 'PSL', 'PTG', 'PTL', 'PTT', 'PTTEP', 
          'PTTGC', 'QH', 'RATCH', 'RBF', 'RS', 'SAWAD', 'SCB', 'SCC', 'SCGP', 'SINGER', 
          'SPALI', 'SPRC', 'STA', 'STEC', 'STGT', 'SUPER', 'SYNEX', 'TASCO', 'TCAP', 'THANI', 
          'TISCO', 'TKN', 'TOP', 'TQM', 'TRUE', 'TTB', 'TU', 'TVO', 'VGI', 'WHA']

rawData = {}
removedStock = {}
reasons = ["Unable to extract ROA", 
           "Unable to extract ROE", 
           "Unable to extract both ROA and ROE"]


for i in range(len(set100)):
    
    stockROA = yf.Ticker(set100[i]+".BK").info["returnOnAssets"]
    stockROE = yf.Ticker(set100[i]+".BK").info["returnOnEquity"]
    
    if stockROA == None and stockROE == None:
        removedStock[set100[i]] = reasons[2]
        continue
    if stockROA == None:
        removedStock[set100[i]] = reasons[0]
        continue
    if stockROE == None:
        removedStock[set100[i]] = reasons[1]
        continue
        
    rawData[set100[i]] = {}
    rawData[set100[i]]["Return on Assets"] = stockROA*100
    rawData[set100[i]]["Return on Equity"] = stockROE*100

rawData = pd.DataFrame.from_dict(rawData).transpose()
rawData