Tommaso Verzegnassi 2023-05-13 16:39:03 +02:00
commit 87c225170b

55
indexer/indexer.py Normal file
View file

@ -0,0 +1,55 @@
import pandas as pd
def get_peg(ticker: str):
# Read current ratios .csv
current_ratios = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}_current_ratios.csv', index_col=[0])
# Convert Object to DateTime
current_ratios['asOfDate'] = pd.to_datetime(current_ratios['asOfDate'])
# Sorting per Date
current_ratios = current_ratios.sort_values('asOfDate', ascending=False)
# Drop NaN pandas values
current_ratios = current_ratios.dropna()
# Take first value (the last peg ratio)
peg_ratio = current_ratios['PegRatio'][:1]
return peg_ratio.values[0]
def get_financial_health(ticker: str):
# Read balance sheet .csv
balance_sheet = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}_balance_sheet_4Y+4Q.csv', index_col=[0])
# Convert Object to DateTime
balance_sheet['asOfDate'] = pd.to_datetime(balance_sheet['asOfDate'])
# Sorting per Date
balance_sheet = balance_sheet.sort_values('asOfDate', ascending=False)
# Drop NaN pandas values
balance_sheet = balance_sheet.dropna()
# Create financial health column
balance_sheet['financial_health'] = balance_sheet['TotalDebt'] / balance_sheet['TotalAssets']
# Get financial health
financial_health = balance_sheet['financial_health'][:1]
return financial_health.values[0]
def estimated_growth(ticker: str):
# Read 5 years growth estimates
growth_estimated = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}5YGrowthEstimates.csv', index_col=[0])['5Y Growth estimate'].values[0]
return growth_estimated
if __name__ == '__main__':
print(get_peg('MCD')) # < 1 (GREEN); > 1 (RED); = 1 (ORANGE)
print(get_financial_health('MCD')) # < 1 (GREEN); > 1 (RED); = 1 (ORANGE)
print(estimated_growth('MCD')) # < 0 (RED); 0 < x < 8% (ORANGE); < 8 % (GREEN)