Untitled

# import psycopg2
# import matplotlib.pyplot as plt

# # Connect to the PostgreSQL database
# conn = psycopg2.connect(
#     dbname="country_economics",
#     user="postgres",
#     password="3204965",
#     host="localhost",
#     port="5432"
# )

# # Create a cursor
# cur = conn.cursor()

# # Construct the list of year columns dynamically
# year_columns = ",\n".join([f"year_{year}" for year in range(1960, 2023)])

# # SQL query
# sql_query = f"""
#     SELECT
#         gdp.country_name,
#         {year_columns}
#     FROM inflation_consumer AS gdp
#     WHERE country_name IN ('Turkiye', 'Germany');
# """

# # Fetch data from the gdp_countries table
# cur.execute(sql_query)
# gdp_data_all = cur.fetchall()

# # Fetch data from the inflation table
# inf_query = f"""
#     SELECT
#         inf.country_name,
#         {year_columns}
#     FROM gdp_per_capita_growth AS inf
#     WHERE country_name IN ('Turkiye', 'Germany');
# """
# #, 'European Union',
#     #  'Middle East & North Africa'

# cur.execute(inf_query)
# inf_data_all = cur.fetchall()

# # Close the cursor and connection
# cur.close()
# conn.close()

# years = list(range(1960, 2023))
# gdp_values = []
# gdp_countries = []
# inf_values = []
# inf_countries = []

# for row in gdp_data_all:
#     country_name = row[0]
#     gdp_values.append(row[1:])
#     gdp_countries.append(country_name)

# for row in inf_data_all:
#     country_name = row[0]
#     inf_values.append(row[1:])
#     inf_countries.append(country_name)

# # Calculate the difference between GDP and inflation
# diff_values = []

# for gdp_row, inf_row in zip(gdp_values, inf_values):
#     diff_row = []
#     for gdp, inf in zip(gdp_row, inf_row):
#         if gdp is not None and inf is not None:
#             diff_row.append(inf - gdp)
#         else:
#             diff_row.append(None)
#     diff_values.append(diff_row)


# # Create a line plot
# fig, axes = plt.subplots(3, 1, figsize=(10, 18))

# # Plot GDP data in the first subplot
# for country, gdp in zip(gdp_countries, gdp_values):
#     axes[0].plot(years, gdp, marker='o', label=f"{country} GDP Per Capita")

# axes[0].set_title("Yearly Consumer Prices Inflation Graph")
# axes[0].set_xlabel("Year")
# axes[0].set_ylabel("GDP Consumer Prices Inflation Ratio")
# # axes[0].set_yscale("log")
# axes[0].grid(True)
# axes[0].legend()

# # Plot inflation data in the second subplot
# for country, inf in zip(inf_countries, inf_values):
#     axes[1].plot(years, inf, marker='o', label=f"{country} GDP PC Growth")

# axes[1].set_title("Annual GDP PC Growth Graph")
# axes[1].set_xlabel("Year")
# axes[1].set_ylabel("GDP PC Growth Ratio")
# # axes[1].set_yscale("log")
# axes[1].grid(True)
# axes[1].legend()

# for country, diff in zip(gdp_countries, diff_values):
#     axes[2].plot(years, diff, marker='o', label=f"{country} GDP - Inflation")

# axes[2].set_title("Annual (GDP Per Capita - Inflation Graph)")
# axes[2].set_xlabel("Year")
# axes[2].set_ylabel("(GDP Per Capita - Inflation) Ratio")
# axes[2].grid(True)
# axes[2].legend()

# # Adjust layout
# plt.tight_layout()
# plt.show()