add application file

interactive_interest_coverage_graph.py

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+# %%
+# imports
+import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+# %%
+# import data
+data = pd.read_excel("graph_data.xlsx",
+                     sheet_name = "Sheet1",
+                     header = 0
+)
+
+# clean data
+# rename year column
+data = data.rename(columns = {"Unnamed: 0": "Year"})
+# drop rows without data
+data = data.drop([0,1,2,3,4,5,6,7,8,9,10,11])
+# keep columns of interest
+data = data[[
+    "Year",
+    "Total Revenues",
+    "Debt Balance",
+    "Revenues ex SS OASDI",
+    "Average Rate on Federal Debt", 
+    "Net Interest / Revenues (Baseline)", 
+    "Net Interest / Revenues ex SS OASDI (Baseline)"
+    ]]
+
+
+
+# %%
+baseline_interest_rate = 3.67
+
+def plot_interest_coverage(interest_rate):
+
+    # calculate the yearly increase in the interest rate based on the projected interest rate in 2054
+    yearly_increase = (interest_rate - baseline_interest_rate) / (2054 - 2025) / 100
+
+    # 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"] + (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"])
+    
+    # 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"])
+
+    # Create the plot
+    plt.figure(figsize = (10, 4.8))
+    # plot average rate on federal debt
+    plt.plot(
+        data["Year"], 
+        data["Average Rate on Federal Debt"], 
+        color = "Green", 
+        label = "Average Rate on Federal Debt"
+    )
+    # plot average rate on federal debt projected
+    plt.plot(
+        data["Year"], 
+        data["Average Rate on Federal Debt (Projected)"], 
+        color = "Green", 
+        label = "Average Rate on Federal Debt (Projected)",
+        linestyle = "--"
+    )
+    # plot interest / revenues (baseline)
+    plt.plot(
+        data["Year"], 
+        data["Net Interest / Revenues (Baseline)"], 
+        color = "Blue", 
+        label = "Net Interest / Revenues (Baseline)"
+    )
+    # plot interest / revenues (projected)
+    plt.plot(
+        data["Year"], 
+        data["Net Interest / Revenues (Projected)"], 
+        color = "Blue", 
+        label = "Net Interest / Revenues (Projected)",
+        linestyle = "--"
+    )
+    # plot interest / revenues ex ss oasdi (baseline)
+    plt.plot(
+        data["Year"], 
+        data["Net Interest / Revenues ex SS OASDI (Baseline)"], 
+        color = "Orange", 
+        label = "Net Interest / Revenues ex SS OASDI (Baseline)"
+    )
+    # plot interest / revenues ex ss oasdi (projected)
+    plt.plot(
+        data["Year"], 
+        data["Net Interest / Revenues ex SS OASDI (Projected)"], 
+        color = "Orange", 
+        label = "Net Interest / Revenues ex SS OASDI (Projected)",
+        linestyle = "--"
+    )
+    plt.title("Interest as Share of Revenues Through 2054")
+    plt.legend(loc = "upper left")
+    plt.ylim(0, 1.05)
+    plt.yticks(np.arange(0, 1.1, 0.1))
+    plt.xticks(range(1962,2055,2), rotation = 90)
+    plt.axvline(x = 2024, color = "black")
+    plt.grid(True, axis = 'y', linestyle = '--', linewidth = 0.7)
+    
+    # Save the plot to a file
+    plt.savefig("interest_coverage.png")
+    plt.close()
+    
+    # Return the path to the image file
+    return "interest_coverage.png"
+
+# %%
+interest_rate_lowerbound = 0
+interest_rate_upperbound = 15
+
+with gr.Blocks() as interface:
+    # Create the image output
+    graph = gr.Image(type="filepath", label = "Graph", value = plot_interest_coverage(baseline_interest_rate))
+    
+    # Create the slider input below the image
+    interest_rate_slider = gr.Slider(
+        interest_rate_lowerbound, 
+        interest_rate_upperbound, 
+        step = .1,
+        value = baseline_interest_rate, 
+        label = "2054 Projected Interest Rate"
+    )
+
+    gr.Markdown('<p style="font-size:11px;">Source: CBO June 2024  An Update to the Budget and Economic Outlook: 2024 to 2034, March 2024 report The Long-Term Budget Outlook: 2024 to 2054, and author\'s calculations. Scenario of higher interest rate is author\'s calculations. Data points for 2035-2054 calculated to build on CBO\'s June 2024 10-year update and be consistent with the March 2024 long-term report. Historical Social Security OASDI payroll tax revenue from Table 4-3 of the SSA\'s Trust Fund Data, and projections from the CBO\'s August 2024 Long Term Projections for Social Security.</p>')
+
+    # Set up an action that updates the graph when the slider value changes
+    interest_rate_slider.change(
+        plot_interest_coverage, 
+        inputs = interest_rate_slider, 
+        outputs = graph
+    )
+
+# Launch the interface
+interface.launch(share = True)
+
+