From 83b9f8fefdf9b585b34f3e0c2b846b5c16d40a3b Mon Sep 17 00:00:00 2001
From: Boyuan Ning <73546421+ningboyuan@users.noreply.github.com>
Date: Sun, 13 Mar 2022 03:29:31 +0100
Subject: [PATCH] Update NormalDistributions_CDF.py

---
 .../NormalDistributions_CDF.py                           | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/DEDA_Class_2017_Statistics&Finance/NormalDistributions_CDF.py b/DEDA_Class_2017_Statistics&Finance/NormalDistributions_CDF.py
index 6bcdcc3..94399cd 100644
--- a/DEDA_Class_2017_Statistics&Finance/NormalDistributions_CDF.py
+++ b/DEDA_Class_2017_Statistics&Finance/NormalDistributions_CDF.py
@@ -1,17 +1,18 @@
 import scipy as sc
 import matplotlib.pyplot as plt
 import matplotlib.mlab as mlab
-
+from scipy.stats import norm
+\
 
 def plot_normal(mu, sigma, size):
     # Create a function to receive normal distribution parameters
     normal_data = sc.random.normal(loc=mu, scale=sigma, size=size)
-    plt.axes()
+    
     # The hist() method not only draw the histogram
     # but also return the info of the drawing
-    n, bins, patchs = plt.hist(normal_data, bins=100, normed=1)
+    n, bins, patchs = plt.hist(normal_data, bins=100, density=True)
     # Use bins returned from hist() to draw a wrap line
-    y = mlab.normpdf(bins, mu, sigma)
+    y = norm.pdf(bins, mu, sigma)
     plt.plot(bins, y, '-')
     plt.draw()
     return plt