<jupyter_start><jupyter_text>We have computed the Euclidean Distance between employee A and all other persons. From the results, we can see that employee E is the most similar person to A. Does this make sensence? Let us try to use do the standardisation on both 'Age' and 'Salary' and calculate the distance again.<jupyter_code>df['Age_scale']=0
df['Salary_scale']=0
from sklearn.preprocessing import MinMaxScaler
minScaler = MinMaxScaler()

df[['Age_scale','Salary_scale']] = minScaler.fit_transform(df[['Age','Salary']])#pd.Da#aFrame(minScaler.fit_transform(df[['Age','Salary']].values), columns=['Age','Salary'])
df['new_distance'] = df[['Age_scale', 'Salary_scale']].sub(df.iloc[0]).pow(2).sum(1).pow(0.5)
df<jupyter_output><empty_output>
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