revenues slider functionality

app.py

@@ -24,8 +24,8 @@ data = data[[
     "Debt Balance",
     "Revenues ex SS OASDI",
     "Average Rate on Federal Debt", 
-    "Net Interest / Revenues (Baseline)", 
-    "Net Interest / Revenues ex SS OASDI (Baseline)"
+    "GDP", 
+    "Net Interest"
     ]]
 
 print(data)
@@ -37,30 +37,46 @@ baseline_revenues = 15928.73
 
 def plot_interest_coverage(interest_rate, revenues):
 
-    print(revenues)
-
     # calculate the yearly increase in the interest rate based on the projected interest rate in 2054
     interest_rate_yearly_increase = (interest_rate - baseline_interest_rate) / (2054 - 2025) / 100
     # calculate the yearly increase in revenues based on the projected interest rate in 2054
     revenues_yearly_increase = (revenues - baseline_revenues) / (2054 - 2025)
 
+    # add a baseline net interest / revenues column
+    data["Net Interest / Revenues (Baseline)"] = data["Net Interest"] / data["Total Revenues"]
+
+    # add a baseline net interest / revenues ex SS OASDI column
+    data["Net Interest / Revenues ex SS OASDI (Baseline)"] = data["Net Interest"] / data["Revenues ex SS OASDI"]
+
     # add a projected average rate on federal debt column
     data["Average Rate on Federal Debt (Projected)"] = np.where(
         data["Year"].astype(int) < 2026, 
         data["Average Rate on Federal Debt"], 
         data["Average Rate on Federal Debt"] + (interest_rate_yearly_increase * (data["Year"].astype(int) - 2025)))
     
+    # add a projected revenues column
+    data["Total Revenues (Projected)"] = np.where(
+        data["Year"].astype(int) < 2026, 
+        data["Revenues"], 
+        data["Revenues"] + (revenues_yearly_increase * (data["Year"].astype(int) - 2025)))
+    
+    # add a projected revenues ex SS OASDI column
+    data["Revenues ex SS OASDI (Projected)"] = np.where(
+        data["Year"].astype(int) < 2026, 
+        data["Revenues ex SS OASDI"], 
+        data["Revenues ex SS OASDI"] + (revenues_yearly_increase * (data["Year"].astype(int) - 2025)))
+      
     # add a projected interest / revenues column
     data["Net Interest / Revenues (Projected)"] = np.where(
         data["Year"].astype(int) < 2026, 
         data["Net Interest / Revenues (Baseline)"], 
-        data["Average Rate on Federal Debt (Projected)"] * data["Debt Balance"] / data["Total Revenues"])
+        data["Average Rate on Federal Debt (Projected)"] * data["Debt Balance"] / data["Total Revenues (Projected)"])
     
     # add a projected interest / revenues ex SS OASDI column
     data["Net Interest / Revenues ex SS OASDI (Projected)"] = np.where(
         data["Year"].astype(int) < 2026, 
         data["Net Interest / Revenues ex SS OASDI (Baseline)"], 
-        data["Average Rate on Federal Debt (Projected)"] * data["Debt Balance"] / data["Revenues ex SS OASDI"])
+        data["Average Rate on Federal Debt (Projected)"] * data["Debt Balance"] / data["Revenues ex SS OASDI (Projected)"])
 
     # Create the plot
     plt.figure(figsize = (10, 4.8))