Pharmaceutical, Machine Learning, Graph Theory, Linear Programming.
npi_info['Sales'].iloc[i]=np.random.randint(100,10000) npi_info.head() from sklearn.cluster import KMeans import numpy as np from sklearn.preprocessing import MinMaxScaler scaler=MinMaxScaler() X=scaler.fit_transform(npi_info[['Avg Patients / day','Total Rx','Product1_Rx','Product2_Rx', "KOL",