This is an edited verison of Dr. Wang's "myfirst_jupyternotebook" blog post (https://yongmeiwang.github.io/2021/12/21/myfirst_jupyternotebook.html) to demonstrate Jupyter Notebook datafile import and editing.

The following changes were made:

1. Saved original datafile (.dat) as (.csv)
2. Renamed and added "Difference" column ("20nm Near-field" minus "15nm Near-field") to .csv file
3. Added legend and plot labels
4. Changed plot resolution from default (100) to 500 dpi

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from cycler import cycler

data = pd.read_csv("./datafile/Au_15nm_20nm_MieNF_JC.csv")
print(data)

     Wavelength (nm)  15nm Near-field  20nm Near-field  Difference
0                300         2.279255         2.333296    0.054041
1                301         2.278743         2.332563    0.053820
2                302         2.278083         2.331566    0.053483
3                303         2.277580         2.330844    0.053263
4                304         2.277081         2.330126    0.053045
..               ...              ...              ...         ...
596              896         2.824623         2.845540    0.020917
597              897         2.821784         2.842624    0.020840
598              898         2.818994         2.839757    0.020763
599              899         2.816524         2.837214    0.020690
600              900         2.813762         2.834376    0.020614

[601 rows x 4 columns]

fig, ax = plt.subplots()
ax.set_facecolor("black")

line1 = ax.plot(data["Wavelength (nm)"], data["15nm Near-field"], label="15nm AuNP", color="#00ff41")
line2 = ax.plot(data["Wavelength (nm)"], data["20nm Near-field"], label="20nm AuNP", color="#FE53BB")
line3 = ax.plot(data["Wavelength (nm)"], data["Difference"], label="Difference", color="#F5D300")

ax.legend(loc='upper right')
plt.title("Gold Nanoparticle Mei Scatter")
plt.xlabel("Wavelength (nm)")
plt.ylabel("Electromagnetic Nearfield Absorption")


mpl.rcParams["figure.dpi"] = 500