To analyse the data points based on normal distribution and standard deviation.

std-vs-normal-distribution.py

from scipy import stats
import matplotlib.pyplot as plt
import pandas as pd

df = pd.read_csv('your_csv_name')
col = df['Grade']
density = stats.gaussian_kde(col)

col.plot.density()

s = col.std()
m = col.mean()

x1 = [m-s, m+s]
y1 = density(x1)
plt.plot(x1, y1, color='magenta')
plt.annotate("1 std (68.26%)",(x1[1],y1[1]))

x2 = [m-(2*s), m+(2*s)]
y2 = density(x2)
plt.plot(x2, y2, color='yellow')
plt.annotate("2 std (98.45%)",(x2[1],y2[1]))

x3 = [m-(3*s), m+(3*s)]
y3 = density(x3)
plt.plot(x3, y3, color='orange')
plt.annotate("3 std (99.73%)",(x3[1],y3[1]))

plt.axvline(col.mean(), color='cyan', linestyle='dashed', linewidth=2)
plt.axis('off')
plt.show()