Example AI request for a Python script to do data analysis:
Write a python program that reads in data from files in a folder having file that start with the same prefix name followed by time. 
The prefix name needs to be an input to the script from the program user. Each file has 20 lines of header to be ignored, and then two columns of data containing wavelength in one column and Transmission in the other column. Calculate OpticalDepth using the equation OpticalDepth=-ln(Transmission/100). Make individual plots of the OpticalDepth data, and a plot that overlays all of the files in one plot. Label the x axis with "Wavelength (nm)" and the y axis as "Optical Depth". Save each plot as a .png file. Make an mp4 movie from the individual files and save it. For the individual OpticalDepth graphs, use the same filename as the input files though with the png output suffix. Name the overlay png graph with the prefix name followed by the suffix .png. Name the mp4 movie with the prefix name followed by the .mp4 suffix.

Example script from CoPilot in Windows11:
import os
import glob
import numpy as np
import matplotlib.pyplot as plt
import imageio
from math import log

def main():
    prefix = input("Enter the prefix name: ")
    files = sorted(glob.glob(f'{prefix}*.txt'))

    if not files:
        print("No files found with the given prefix.")
        return

    overlay_data = []

    for file in files:
        data = np.loadtxt(file, skiprows=20)
        wavelength = data[:, 0]
        transmission = data[:, 1]
        optical_depth = -np.log(transmission / 100)

        plt.figure()
        plt.plot(wavelength, optical_depth, label=file)
        plt.xlabel("Wavelength (nm)")
        plt.ylabel("Optical Depth")
        plt.title(f'Optical Depth - {file}')
        plt.legend()
        plt.savefig(f'{os.path.splitext(file)[0]}.png')
        plt.close()

        overlay_data.append((wavelength, optical_depth))

    # Plot overlay
    plt.figure()
    for wavelength, optical_depth in overlay_data:
        plt.plot(wavelength, optical_depth)
    plt.xlabel("Wavelength (nm)")
    plt.ylabel("Optical Depth")
    plt.title(f'Overlay Optical Depth - {prefix}')
    plt.savefig(f'{prefix}.png')
    plt.close()

    # Create MP4 movie
    with imageio.get_writer(f'{prefix}.mp4', fps=1) as writer:
        for file in files:
            image = imageio.imread(f'{os.path.splitext(file)[0]}.png')
            writer.append_data(image)

if __name__ == "__main__":
    main()



NOTES:

Input Prefix: The script prompts the user to enter the prefix name.

File Reading: It reads all files in the folder with the specified prefix.

Header Ignoring: It skips the first 20 lines of each file.

Data Extraction: It extracts the wavelength and transmission data, calculates the optical depth, and creates individual plots for each file.

Overlay Plot: It generates a plot that overlays the optical depth data from all files.

Saving Plots: Each plot is saved as a .png file with the appropriate filename.

MP4 Movie: It creates an mp4 movie from the individual png files and saves it.

Make sure you have the necessary libraries installed. You can install them using:

sh
pip install numpy matplotlib imageio