# pip install pandas matplotlib
# python analyze_air_quality.py
# The script will create a directory named with today’s date (e.g., 2024-10-11) and save the graphs as PNG images inside that directory.

import os
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime

def load_data(file_path):
    """Load the air quality CSV data."""
    return pd.read_csv(file_path)

def preprocess_data(data):
    """Preprocess the data by converting the 'Time' column to datetime."""
    data['Time'] = pd.to_datetime(data['Time'], format='%d/%m/%Y %I:%M:%S %p')
    return data

def create_output_directory():
    """Create a directory with today's date to store the plots."""
    today = datetime.today().strftime('%Y-%m-%d')
    if not os.path.exists(today):
        os.makedirs(today)
    return today

def plot_data(data, output_dir):
    """Generate and save the time series plots to the output directory."""
    
    # Plot CO2 levels over time
    plt.figure(figsize=(10, 6))
    plt.plot(data['Time'], data['CO2_ppm'], label='CO2 (ppm)', color='green')
    plt.xlabel('Time')
    plt.ylabel('CO2 (ppm)')
    plt.title('CO2 Levels Over Time')
    plt.grid(True)
    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.savefig(f"{output_dir}/CO2_levels_over_time.png")
    plt.close()

    # Plot Temperature over time
    plt.figure(figsize=(10, 6))
    plt.plot(data['Time'], data['Temperature_F'], label='Temperature (°F)', color='red')
    plt.xlabel('Time')
    plt.ylabel('Temperature (°F)')
    plt.title('Temperature Over Time')
    plt.grid(True)
    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.savefig(f"{output_dir}/Temperature_over_time.png")
    plt.close()

    # Plot Relative Humidity over time
    plt.figure(figsize=(10, 6))
    plt.plot(data['Time'], data['Humidity_percent'], label='Relative Humidity (%)', color='blue')
    plt.xlabel('Time')
    plt.ylabel('Relative Humidity (%)')
    plt.title('Relative Humidity Over Time')
    plt.grid(True)
    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.savefig(f"{output_dir}/Relative_humidity_over_time.png")
    plt.close()

    # Plot Atmospheric Pressure over time
    plt.figure(figsize=(10, 6))
    plt.plot(data['Time'], data['Pressure_hPa'], label='Pressure (hPa)', color='purple')
    plt.xlabel('Time')
    plt.ylabel('Pressure (hPa)')
    plt.title('Atmospheric Pressure Over Time')
    plt.grid(True)
    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.savefig(f"{output_dir}/Pressure_over_time.png")
    plt.close()

def main():
    """Main function to load, process, and plot the air quality data."""
    file_path = "export.csv"
    
    # Load and preprocess the data
    data = load_data(file_path)
    data = preprocess_data(data)

    output_dir = create_output_directory()

    plot_data(data, output_dir)

    print(f"Graphs have been saved in the directory: {output_dir}")

if __name__ == "__main__":
    main()