Generate Chart of Median House Prices With Mortgage Rates And Recessions in Python

import pandas as pd
import matplotlib.pyplot as plt
from pandas_datareader.data import DataReader
from datetime import datetime

save_path = "./results/median-house-price-with-mortgage-rates.png"

# Fetch median sales price data from FRED
def fetch_median_sales_price():
    """
    Fetches Median Sales Price of Houses in the US from FRED.
    Returns:
        DataFrame with date index and median sales price.
    """
    start_date = "1988-01-01"
    end_date = datetime.now()
    median_sales_price = DataReader("MSPNHSUS", "fred", start_date, end_date)
    median_sales_price.rename(columns={"MSPNHSUS": "Median Sales Price"}, inplace=True)
    return median_sales_price

# Fetch mortgage rates from FRED
def fetch_mortgage_rates():
    """
    Fetches 30-Year Fixed Mortgage Rates in the US from FRED.
    Returns:
        DataFrame with date index and mortgage rates.
    """
    start_date = "1988-01-01"
    end_date = datetime.now()
    mortgage_rates = DataReader("MORTGAGE30US", "fred", start_date, end_date)
    mortgage_rates.rename(columns={"MORTGAGE30US": "Mortgage Rates"}, inplace=True)
    return mortgage_rates

# Fetch recession data from FRED
def fetch_recession_data():
    """
    Fetches US recession data from FRED.
    Returns:
        DataFrame with date index and recession indicators.
    """
    start_date = "1988-01-01"
    end_date = datetime.now()
    recession_data = DataReader("USREC", "fred", start_date, end_date)
    return recession_data

def get_recession_periods(recessions):
    """
    Extracts periods of recessions.
    Args:
        recessions: DataFrame containing recession indicators (1 for recession, 0 otherwise).
    Returns:
        List of tuples representing start and end dates of recessions.
    """
    recession_periods = []
    in_recession = False
    start_date = None
    for date, value in recessions["USREC"].items():
        if value == 1 and not in_recession:
            in_recession = True
            start_date = date
        elif value == 0 and in_recession:
            in_recession = False
            end_date = date
            recession_periods.append((start_date, end_date))
    return recession_periods

def plot_median_sales_price_and_mortgage_rates(median_sales_price, mortgage_rates, recession_periods):
    """
    Plots the Median Sales Price of Houses and Mortgage Rates with recession periods.
    Args:
        median_sales_price: DataFrame with median sales price data.
        mortgage_rates: DataFrame with mortgage rate data.
        recession_periods: List of recession periods (start and end dates).
    """
    fig, ax1 = plt.subplots(figsize=(14, 8))
    
    # Plot median sales price
    ax1.plot(median_sales_price.index, median_sales_price["Median Sales Price"], color="blue", linewidth=1.5, label="Median Sales Price")
    ax1.set_xlabel("Year", fontsize=14, labelpad=10)
    ax1.set_ylabel("Median Sales Price (USD)", fontsize=14, labelpad=10, color="blue")
    ax1.tick_params(axis="y", labelcolor="blue")
    ax1.grid(visible=True, which="major", linestyle="--", linewidth=0.5, alpha=0.7)
    
    # Add recession periods
    for start_date, end_date in recession_periods:
        ax1.axvspan(start_date, end_date, color="gray", alpha=0.3, label="Recession" if start_date == recession_periods[0][0] else "")
    
    # Plot mortgage rates
    ax2 = ax1.twinx()
    ax2.plot(mortgage_rates.index, mortgage_rates["Mortgage Rates"], color="green", linewidth=1.5, linestyle="--", label="Mortgage Rates")
    ax2.set_ylabel("Mortgage Rates (%)", fontsize=14, labelpad=10, color="green")
    ax2.tick_params(axis="y", labelcolor="green")
    
    # Combine legends
    lines, labels = ax1.get_legend_handles_labels()
    lines2, labels2 = ax2.get_legend_handles_labels()
    ax1.legend(lines + lines2, labels + labels2, fontsize=12, loc="upper left")
    
    # Title and layout
    plt.title("Median Sales Price of Houses and Mortgage Rates with Recession Periods", fontsize=18, fontweight="bold", pad=20)
    plt.tight_layout()
    plt.savefig(save_path, dpi=300, bbox_inches="tight")
    plt.show()

if __name__ == "__main__":
    try:
        median_sales_price = fetch_median_sales_price()
        mortgage_rates = fetch_mortgage_rates()
        recession_data = fetch_recession_data()
        recession_periods = get_recession_periods(recession_data)
        plot_median_sales_price_and_mortgage_rates(median_sales_price, mortgage_rates, recession_periods)
    except Exception as e:
        print(f"An error occurred: {e}")