I am trying to learn about the normal distribution and using python and a udemy course to help. I have two tiny codes I's like help distinguishing the difference between the two. Could you explain both graphs and what is going on? the second one is confusing. what is pdf doing. i thought you couldn't find the probabiliy of a single number (should be 0?)Please explain what is going on in code and be prepared for follow up question just in case

In [23]: #sns.set_theme(style="whitegrid") import seaborn as sns import numpy as np import matplotlib.pyplot as plt cf_1=np.random.normal(100,2,1000) sns.kdeplot(cf_1) plt.show() 0.175 0.150 0.125 0.100 0.075 0.050 0.025 0.000 90.0 92.5 95.0 97.5 100.0 102.5 105.0 107.5 In [33]: Nx_ax=np.linspace(144,156,13) X_ax . Out[33]: array([144., 145., 146., 147., 148., 149., 150., 151., 152., 153., 154., 155., 156.]) In [34]: y_ax=norm.pdf(x_ax, 150,2) y_ax Out[34]: array([0.00221592, 0.00876415, 0.02699548, 0.0647588 0.12098536, 0.17603266, 0.19947114, 0.17603266, 0.12098536, 0.0647588 0.02699548, 0.00876415, 0.00221592]) In [35]: sns.lineplot(x_ax,y_ax) Out[35]: 0.200 0.175 0.150 0.125 0.100 0.075 0.050 0.025 0.000 144 146 148 150 152 154 156 In 1: N