import pandas as pd
import matplotlib.pyplot as plt

# Data
data = {
    'Year': list(range(2000, 2021)),
    'Pommes_Quantity': [100, 103, 107, 109, 112, 112, 114, 115, 119, 118, 116, 118, 117, 119, 120, 125, 128, 129, 131, 136, 143],
    'Pommes_Price': [40, 39, 39, 39, 40, 39, 40, 40, 40, 42, 43, 42, 42, 43, 44, 45, 45, 46, 47, 47, 47],
    'Bananes_Quantity': [50, 47, 47, 45, 46, 46, 47, 46, 43, 40, 41, 40, 41, 40, 40, 41, 38, 38, 37, 37, 34],
    'Bananes_Price': [30, 35, 38, 38, 41, 39, 36, 42, 44, 46, 44, 50, 50, 53, 56, 59, 66, 61, 64, 61, 61],
    'Cerises_Quantity': [200, 206, 213, 215, 224, 227, 237, 249, 255, 262, 268, 280, 289, 290, 297, 308, 320, 330, 344, 353, 361],
    'Cerises_Price': [20, 20, 19, 18, 18, 17, 16, 16, 16, 15, 15, 15, 15, 14, 13, 13, 13, 13, 13, 13, 12]
}

df = pd.DataFrame(data)

# Prices of the year 2000
base_prices = {
    'Pommes': 40,
    'Bananes': 30,
    'Cerises': 20
}

# Calculate nominal GDP
df['Nominal_GDP'] = (df['Pommes_Quantity'] * df['Pommes_Price'] +
                     df['Bananes_Quantity'] * df['Bananes_Price'] +
                     df['Cerises_Quantity'] * df['Cerises_Price'])

# Calculate real GDP using the prices of the year 2000
df['Real_GDP_2000'] = (df['Pommes_Quantity'] * base_prices['Pommes'] +
                       df['Bananes_Quantity'] * base_prices['Bananes'] +
                       df['Cerises_Quantity'] * base_prices['Cerises'])

# Calculate chained real GDP
df['Chained_Real_GDP'] = df['Real_GDP_2000'].iloc[0]
for i in range(1, len(df)):
    # Calculate growth rates
    g_t_I = (df['Pommes_Quantity'].iloc[i] * df['Pommes_Price'].iloc[i-1] +
             df['Bananes_Quantity'].iloc[i] * df['Bananes_Price'].iloc[i-1] +
             df['Cerises_Quantity'].iloc[i] * df['Cerises_Price'].iloc[i-1]) / \
            (df['Pommes_Quantity'].iloc[i-1] * df['Pommes_Price'].iloc[i-1] +
             df['Bananes_Quantity'].iloc[i-1] * df['Bananes_Price'].iloc[i-1] +
             df['Cerises_Quantity'].iloc[i-1] * df['Cerises_Price'].iloc[i-1]) - 1

    g_t_F = (df['Pommes_Quantity'].iloc[i] * df['Pommes_Price'].iloc[i] +
             df['Bananes_Quantity'].iloc[i] * df['Bananes_Price'].iloc[i] +
             df['Cerises_Quantity'].iloc[i] * df['Cerises_Price'].iloc[i]) / \
            (df['Pommes_Quantity'].iloc[i-1] * df['Pommes_Price'].iloc[i] +
             df['Bananes_Quantity'].iloc[i-1] * df['Bananes_Price'].iloc[i] +
             df['Cerises_Quantity'].iloc[i-1] * df['Cerises_Price'].iloc[i]) - 1

    # Geometric mean of growth rates
    g_t = ((1 + g_t_I) ** 0.5 * (1 + g_t_F) ** 0.5) - 1

    # Calculate chained real GDP
    df.loc[i, 'Chained_Real_GDP'] = df.loc[i-1, 'Chained_Real_GDP'] * (1 + g_t)

# Plot the series
plt.figure(figsize=(10, 6))
plt.plot(df['Year'], df['Real_GDP_2000'], label='Real GDP 2000')
plt.plot(df['Year'], df['Chained_Real_GDP'], label='Chained Real GDP')
plt.xlabel('Year')
plt.ylabel('GDP')
plt.title('Nominal GDP vs Chained Real GDP')
plt.legend()
plt.grid(True)
plt.show()

# Calculate average growth rates
real_growth_rate_2000 = (df['Real_GDP_2000'].iloc[-1] / df['Real_GDP_2000'].iloc[0]) ** (1 / (len(df) - 1)) - 1
chained_real_growth_rate = (df['Chained_Real_GDP'].iloc[-1] / df['Chained_Real_GDP'].iloc[0]) ** (1 / (len(df) - 1)) - 1

print(f"Average real 2000 growth rate: {real_growth_rate_2000:.2%}")
print(f"Average chained real growth rate: {chained_real_growth_rate:.2%}")