From 26b1b94e3be90500aa1bb22ab1f11cf34694565c Mon Sep 17 00:00:00 2001
From: Pietro Rodolfo Masera <pietrorodolfomasera@Pietros-MacBook-Pro-3.local>
Date: Wed, 10 May 2023 13:55:07 +0200
Subject: [PATCH] Indexer con peg ratio, financial health, estimated_growth,
 manca past_performance

---
 indexer/indexer.py | 55 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 55 insertions(+)
 create mode 100644 indexer/indexer.py

diff --git a/indexer/indexer.py b/indexer/indexer.py
new file mode 100644
index 0000000..059042a
--- /dev/null
+++ b/indexer/indexer.py
@@ -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)
+