Indexer finished with the last index, on monday we will discuss the implementation of the main dashboard with these indexes
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1 changed files with 15 additions and 8 deletions
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@ -1,7 +1,6 @@
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import pandas as pd
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def get_peg(ticker: str):
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# Read current ratios .csv
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current_ratios = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}_current_ratios.csv', index_col=[0])
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@ -20,7 +19,6 @@ def get_peg(ticker: str):
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return peg_ratio.values[0]
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def get_financial_health(ticker: str):
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# Read balance sheet .csv
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balance_sheet = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}_balance_sheet_4Y+4Q.csv', index_col=[0])
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@ -42,14 +40,23 @@ def get_financial_health(ticker: str):
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return financial_health.values[0]
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def estimated_growth(ticker: str):
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# Read 5 years growth estimates
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# Read 5 years growth estimates
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growth_estimated = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}5YGrowthEstimates.csv', index_col=[0])['5Y Growth estimate'].values[0]
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return growth_estimated
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if __name__ == '__main__':
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print(get_peg('MCD')) # < 1 (GREEN); > 1 (RED); = 1 (ORANGE)
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print(get_financial_health('MCD')) # < 1 (GREEN); > 1 (RED); = 1 (ORANGE)
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print(estimated_growth('MCD')) # < 0 (RED); 0 < x < 8% (ORANGE); < 8 % (GREEN)
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def past_performance_earnings(ticker: str):
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# Read earnings csv
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earnings = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}earnings.csv', index_col=[0])
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# Performance
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performance_index = round((earnings['epsActual'].sum() - earnings['epsEstimate'].sum()) / earnings['epsEstimate'].sum() * 100, 2)
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return performance_index
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if __name__ == '__main__':
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print(get_peg('GOOGL')) # < 1 (GREEN); > 1 (RED); = 1 (ORANGE)
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print(get_financial_health('GOOGL')) # < 1 (GREEN); > 1 (RED); = 1 (ORANGE)
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print(estimated_growth('GOOGL')) # < 0 (RED); 0 < x < 8% (ORANGE); < 8 % (GREEN)
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print(past_performance_earnings('GOOGL'), "%") # -100 < x < 0 (RED); = 0 (ORANGE); 0 < x < 100 (GREEN)
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