Help me edit the graphs so that the text markers inside the graphs appear slighly more on the left, like 3 centimeters

import os
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

# Specify the folder paths
input_folder = r"C:\Users\samuel.hernandez\OneDrive - FUNDECYT - PCTEX\Escritorio\Doctorado\Experimental\FTIR"
output_folder = r"C:\Users\samuel.hernandez\OneDrive - FUNDECYT - PCTEX\Escritorio\Doctorado\Experimental\FTIR\Python\Test"

# Ensure the output folder exists
os.makedirs(output_folder, exist_ok=True)

def read_data_from_file(file_path):
    try:
        # Read the file, specifying the decimal separator as comma
        data = pd.read_csv(file_path, delim_whitespace=True, header=None, decimal=',')
        wave_number = data.iloc[:, 0].astype(float)
        transmittance = data.iloc[:, 1].astype(float) * 100  # Multiply by 100 to get percentage
        return wave_number, transmittance
    except Exception as e:
        print(f"Error reading {file_path}: {str(e)}")
        return None, None

def create_tight_stacked_subplots(files, output_filename, peak_markers):
    n_files = len(files)
    fig, axs = plt.subplots(n_files, 1, figsize=(12, 2*n_files), sharex=True)
    
    if n_files == 1:
        axs = [axs]  # Make axs iterable if there's only one subplot
    
    # Colorful colors
    colors = plt.cm.tab10(np.linspace(0, 1, n_files))
    
    x_min, x_max = float('inf'), float('-inf')
    
    for ax, file, color in zip(axs, files, colors):
        file_path = os.path.join(input_folder, file)
        wave_number, transmittance = read_data_from_file(file_path)
        
        if wave_number is not None and transmittance is not None:
            ax.plot(wave_number, transmittance, color=color)
            ax.set_yticklabels([])
            
            # Add black text as title
            ax.text(0.02, 0.5, file.replace(".dpt", ""), transform=ax.transAxes, 
                    color='black', va='center', fontsize='small')
            
            # Remove x-axis labels for all but the bottom subplot
            if ax != axs[-1]:
                ax.tick_params(axis='x', which='both', bottom=False, top=False, labelbottom=False)
            
            # Update x_min and x_max
            x_min = min(x_min, wave_number.min())
            x_max = max(x_max, wave_number.max())
            
            # Highlight the specified peaks with black discontinuous vertical lines
            for label, peak in peak_markers.items():
                ax.axvline(x=peak, color='black', linestyle='--', linewidth=1.5)  # Discontinuous vertical line for the peak
                
                # Set distance based on the specific file
                if file in ["PBA-H-0.dpt", "PBA-C-1.dpt"]:
                    ax.text(peak - 0, transmittance.max() * 0.92, label, color='black', ha='right', fontsize='small')  # Smaller distance for specific files
                else:
                    ax.text(peak - 0, transmittance.max() * 0.75, label, color='black', ha='right', fontsize='small')  # Default distance
    
    # Set x-axis label only for the bottom subplot
    axs[-1].set_xlabel('Wave Number (cm⁻¹)')
    plt.xlim(x_max, x_min)  # Set x-axis limits based on data and invert axis
    
    # Add a single y-axis label for the entire figure
    fig.text(0.1, 0.5, 'Transmittance (%)', va='center', rotation='vertical')
    
    # Create a legend for the bonds with wavenumbers
    bond_labels = [f"{label} ({peak} cm⁻¹)" for label, peak in peak_markers.items()]
    
    # Create handles for the legend
    handles = [plt.Line2D([0], [0], color='black', lw=0, label=label) for label in bond_labels]
    
    # Add the legend to the plot below the x-axis
    plt.legend(handles=handles, loc='upper center', bbox_to_anchor=(0.5, -0.3), fontsize='medium', ncol=4)

    plt.tight_layout()
    plt.subplots_adjust(hspace=0, left=0.12, bottom=0.25)  # Adjust bottom margin for the legend
    
    output_path = os.path.join(output_folder, output_filename)
    plt.savefig(output_path, dpi=300, bbox_inches='tight')
    plt.close()
    print(f"Stacked subplots graph saved: {output_path}")

# Define the peak markers for H-series and C-series
h_peak_markers = {
    'ν(Fe–CN)': 590,
    'ν(C≡N)': 2060,
    'ν(O-H)': 1405,
    'δ(O-H)': 3180
}

c_peak_markers = {
    'ν(Fe–CN)': 590,
    'ν(C≡N)': 2055,
    'ν(O-H)': 1615,
    'δ(O-H)': 3650
}

# Find files containing 'C' and 'H'
c_files = [f for f in os.listdir(input_folder) if 'C' in f and f.endswith('.dpt')]
h_files = [f for f in os.listdir(input_folder) if 'H' in f and f.endswith('.dpt')]

if c_files:
    c_files.sort()  # Sort files alphabetically
    create_tight_stacked_subplots(c_files, 'C_containing_samples_FTIR.png', c_peak_markers)
    print(f"Processed C files: {c_files}")

if h_files:
    h_files.sort()  # Sort files alphabetically
    create_tight_stacked_subplots(h_files, 'H_containing_samples_FTIR.png', h_peak_markers)
    print(f"Processed H files: {h_files}")

if not c_files and not h_files:
    print("No files containing 'C' or 'H' found in the input folder.")
    print("Available .dpt files:")
    for file in os.listdir(input_folder):
        if file.endswith('.dpt'):
            print(file)

print(f"Check the output folder: {output_folder}")