import numpy as np
import os # For checking if the file exists

def calculate_statistics(filename):
    """
    Reads a text file of integers using NumPy and prints basic statistics.

    Args:
        filename (str): The name of the input text file.
    """
    if not os.path.exists(filename):
        print(f"Error: The file '{filename}' was not found.")
        print(f"Please ensure '{filename} is in the same directory as this script.")
        return

    try:
        # Use np.loadtxt to read data from the file
        # This function is flexible and can handle various delimiters (space, comma, etc.)
        data = np.loadtxt(filename, dtype=int)
        
        # Flatten the array in case the data is read as a 2D array
        # This ensures all statistics are calculated on a single list of numbers. Uncomment the next two print statements to see the effect.
        #  print(data)
        flat_data = data.flatten()
        #  print(flat_data)
    
        print("-" * (len(filename) + 25))
        print(f"--- Statistics for '{filename}' ---")
        print(f"---    Data points found: {flat_data.size}")
        print(f"---    Data type: {flat_data.dtype}")
        print("-" * (len(filename) + 25))

        # Calculate and print basic statistics
        print(f"Mean (Average):   {np.mean(flat_data):.2f}")
        print(f"Median (Middle):  {np.median(flat_data):.2f}")
        print(f"Minimum Value:    {np.min(flat_data)}")
        print(f"Maximum Value:    {np.max(flat_data)}")
        print(f"Standard Deviation: {np.std(flat_data):.2f}")
        print(f"Sum of all values: {np.sum(flat_data)}")

    except ValueError as e:
        print(f"Error reading file: {e}")
        print("Ensure the file only contains integers and standard delimiters (spaces/commas).")
    except Exception as e:
        print(f"An unexpected error occurred: {e}")

if __name__ == "__main__":
    # Specify the name of your data file
    input_file = input("Please input the data file name: ")
    calculate_statistics(input_file)