import pandas as pd
import matplotlib.pyplot as plt
# Load the CSV file
file_path = r'C:\Users\a_gabald\Desktop\solar_different_efficiencies.csv'  # Replace with your file path
data = pd.read_csv(file_path)


# Assuming the CSV has a datetime column, parse it
data['datetime'] = pd.date_range(start='1/1/2023', periods=8760, freq='h')

# Set the datetime column as the index
data.set_index('datetime', inplace=True)

# Resample the data to monthly data
monthly_data = data.resample('ME').sum()

# Extract data for different efficiencies
monthly_16_horizontal = monthly_data['district MWh Horizontal_16%']
monthly_18_horizontal = monthly_data['district MWh Horizontal_18%']
monthly_14_horizontal = monthly_data['district MWh Horizontal_14%']

monthly_16_tilted = monthly_data['district MWh tilted_16%']
monthly_18_tilted = monthly_data['district MWh tilted_18%']
monthly_14_tilted = monthly_data['district MWh tilted_14%']

# Combine the data into a single DataFrame for easier plotting
combined_data_horizontal = pd.DataFrame({
    'Month': monthly_data.index.month,
    'Horizontal_16%': monthly_16_horizontal,
    'Horizontal_18%': monthly_18_horizontal,
    'Horizontal_14%': monthly_14_horizontal
})

combined_data_tilted = pd.DataFrame({
    'Month': monthly_data.index.month,
    'Tilted_16%': monthly_16_tilted,
    'Tilted_18%': monthly_18_tilted,
    'Tilted_14%': monthly_14_tilted
})
# Function to plot box and whisker plot
import numpy as np

# Function to plot box and whisker plot
import matplotlib.pyplot as plt

# Function to plot error bars
def plot_error_bars(data, title, ylabel):
    fig, ax = plt.subplots(figsize=(14, 8))

    months = range(1, 13)
    means_16 = []
    err_low = []
    err_high = []

    for month in months:
        month_data = data[data['Month'] == month]
        mean_16 = month_data.iloc[:, 1].mean()
        low_14 = month_data.iloc[:, 3].mean()
        high_18 = month_data.iloc[:, 2].mean()

        means_16.append(mean_16)
        err_low.append(mean_16 - low_14)
        err_high.append(high_18 - mean_16)

    ax.errorbar(months, means_16, yerr=[err_low, err_high], fmt='o', capsize=5, capthick=2, ecolor='gray')

    ax.set_xticks(months)
    ax.set_xticklabels(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'])
    ax.set_xlabel('Month')
    ax.set_ylabel(ylabel)
    ax.set_title(title)

    plt.show()

# Plot for Horizontal
plot_error_bars(combined_data_horizontal, 'Monthly District MWh (Horizontal)', 'MWh')

# Plot for Tilted
plot_error_bars(combined_data_tilted, 'Monthly District MWh (Tilted)', 'MWh')