<jupyter_start><jupyter_text>Correlation<jupyter_code>from scipy.stats import norm
correlation=df1.corr()
print(correlation)
sns.heatmap(correlation,cmap='BrBG')
plt.show()
covar=df1.cov()
print(covar)
sns.heatmap(covar)
plt.show()<jupyter_output><empty_output><jupyter_text>Normalization<jupyter_code>df
df.shape
age=np.array(df['age'])
age
age=np.array(df['age'])
print("max age",max(age))
age=age.reshape(395,1)
age=np.array(df['age'])
print("MIn age",min(age))
age=age.reshape(395,1)
from scipy import stats
zscore=np.array(stats.zscore(age))
zscore=zscore[0:394]
zscore=zscore.reshape(2,197)
zscore<jupyter_output><empty_output><jupyter_text>Decimal NOrmalization<jupyter_code>dn=[]
dn.append(age/pow(10,2) )
dn=np.array(dn)
dn<jupyter_output><empty_output><jupyter_text>Min-Max Normalization<jupyter_code>age=np.array(df['age'])
print("max age",max(age))
age=age.reshape(395,1)
age=np.array(df['age'])
print("min age",min(age))
age=age.reshape(395,1)<jupyter_output>min age 15
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