--- a
+++ b/MOA/AgeHypo.py
@@ -0,0 +1,76 @@
+import numpy as np
+import pandas as panda
+import matplotlib.pyplot as plt
+from scipy.stats import norm
+import statistics
+
+
+
+db = panda.read_csv('cardio_train.csv')
+
+Age = db.loc[db.cardio == 1].age
+Age /= 356
+Age = np.floor(Age)
+
+
+
+ageMean = Age.mean()
+ageMedian = Age.median()
+ageMode = Age.mode()
+ageSD = Age.std()
+
+ageQ25,ageQ75 = np.percentile(Age,[25,75])
+
+
+plt.boxplot(Age)
+plt.title("BoxPlot Of The Age")
+plt.ylabel("Age")
+plt.show()
+
+# Data Is Clean Already
+
+unique,count = np.unique(Age, return_counts=True)
+
+r = statistics.correlation(unique,count)
+print("Correlation Between Age And Heart Disease = " +  str(r))
+
+x,y = np.polyfit(unique,count,1)
+plt.scatter(unique,count)
+plt.plot(unique,x*unique + y)
+
+plt.title("Best Linear Fit Of The Data")
+plt.ylabel("Frequency")
+plt.xlabel("Age")
+plt.show()
+
+
+plt.hist(Age,10)
+plt.title("Histogram Of The Age Column Of Patient")
+plt.ylabel("Frequency")
+plt.xlabel("Age")
+plt.show()
+
+
+AgeRightSide = Age.loc[Age >= ageMean]
+AgeLeftSide = Age.loc[Age <= ageMean]
+
+
+rightSideMean = AgeRightSide.mean()
+leftSideMean = AgeLeftSide.mean()
+
+print("Data Mean = " + str(ageMean))
+print("Right Side Mean = " + str(rightSideMean))
+print("Left Side Mean = " + str(leftSideMean))
+
+
+rightSideCount = AgeRightSide.count()
+leftSideCount = AgeLeftSide.count()
+
+PhighAge = (rightSideCount) * 100 / (Age.count())
+PLowAge = (leftSideCount) * 100 / (Age.count())
+
+print("Propability Of High Age And Heart Disease = " + str(PhighAge))
+print("Propability Of Low Age And Heart Disease = " + str(PLowAge))
+
+
+