import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
 
 
df = pd.read_excel('/content/data (1).xlsx')
device_id_to_plot = 'HCV-000-5003'  # Replace with the desired device ID
df_filtered = df[df['DEVICE_ID'] == device_id_to_plot]
grouped = df_filtered.groupby('USER_ID')
 
if not df_filtered.empty:
   
    led_types = ['Sample', 'Buffer']
    num_leds = 4  
    user_ids = list(grouped.groups.keys())
 
    num_groups = len(user_ids) // 5 + (1 if len(user_ids) % 5 != 0 else 0)
    user_id_groups = [user_ids[i*5:(i+1)*5] for i in range(num_groups)]
 
    # Create subplots for Sample and Buffer
    fig, axs = plt.subplots(num_groups, 2, figsize=(12, 5*num_groups), sharex=True, gridspec_kw={'hspace': 0.5})
    colormap = plt.cm.get_cmap('tab10')
 
    for i, group_ids in enumerate(user_id_groups):
        group_data = [grouped.get_group(user_id) for user_id in group_ids]
 
        for j, led_type in enumerate(led_types):
            led_values = [[] for _ in range(num_leds)]
 
            for user_group in group_data:
                led_vals_per_user = [[] for _ in range(num_leds)]
 
                for k in range(1, num_leds + 1):
                    led_values_per_user = user_group[f'LED{k}_{led_type}']
                    led_vals_per_user[k - 1].extend(led_values_per_user)
               
                for led_num in range(num_leds):
                    led_values[led_num].extend(led_vals_per_user[led_num])
 
            # Plot Sample and Buffer values for each LED
            x = np.arange(len(group_ids))  
            bar_width = 0.15  # Adjust bar width
            for led_num in range(num_leds):
                axs[i, j].bar(x + led_num * bar_width, led_values[led_num][:len(group_ids)], width=bar_width, color=colormap(led_num), label=f'LED {led_num + 1}')
 
           
            axs[i, j].set_ylabel('Value')
            axs[i, j].legend()
 
           
            axs[i, j].set_xticks(x + (num_leds - 1) * bar_width / 2)
            axs[i, j].set_xticklabels(group_ids, rotation=45, ha='right')
 
           
            axs[-1, j].set_xlabel('USER_ID')
 
    #Assigning user id
    for i, group_ids in enumerate(user_id_groups[:-1]):  # Exclude the last group
        for idx, user_id in enumerate(group_ids):
            axs[i, 0].text(idx, -0.2, user_id, ha='center', va='center', rotation=-45, fontsize=8)
            axs[i, 1].text(idx, -0.2, user_id, ha='center', va='center', rotation=-45, fontsize=8)
 
    last_group_ids = user_id_groups[-1][:-3]
    for idx, user_id in enumerate(last_group_ids):
        axs[-1, 0].text(idx, -0.2, user_id, ha='center', va='center', rotation=-45, fontsize=8)
        axs[-1, 1].text(idx, -0.2, user_id, ha='center', va='center', rotation=-45, fontsize=8)
 
   
    plt.tight_layout()
    plt.show()
else:
    print(f"No data points found for Device ID: {device_id_to_plot}")