import pandas as pd
import pickle
import numpy as np
from sklearn import tree
# Load the Random Forest CLassifier model
filename = 'model.pkl'
loaded_model = pickle.load(open(filename, 'rb'))
print(loaded_model)

input = [0.0,0.0,1.0,26.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,3.0,0.0,15.0,0.0,0.0,7.0,5.0,7.0]
manualInput =[
 [1.0,1.0,1.0,37.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,5.0,0.0,0.0,1.0,1.0,10.0,6.0,5.0]
 #,[1.0,1.0,1.0,28.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,4.0,0.0,0.0,0.0,1.0,12.0,2.0,4.0]
 #,[1.0,1.0,1.0,27.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,4.0,20.0,20.0,1.0,0.0,8.0,4.0,7.0]
]
print(input, manualInput)
col=["HighBP","HighChol","CholCheck","BMI","Smoker","Stroke","HeartDiseaseorAttack","PhysActivity","Fruits"
     ,"Veggies","HvyAlcoholConsump","AnyHealthcare","NoDocbcCost","GenHlth","MentHlth","PhysHlth","DiffWalk"
     ,"Sex","Age","Education","Income"]
ddf = pd.DataFrame(manualInput, columns=col)
print(ddf)

result = loaded_model.predict(ddf)
print(result)