from django.db import models
# import matplotlib.pyplot as plt
# from scipy import stats
# # Create your models here.
# x_data = []
# y_data = []
# plt.plot(x_data,y_data)
# plt.show()
# x1, x2, x3, x4, x5, x6 = stats.linregress(x_data,y_data)

# models = {
#     'x1':x1,
#     'x2':x2,
#     'x3':x3,
#     'x4':x4,
#     'x5':x5,
#     'x6':x6,
# }
# pickle.dum(models,open('model.p','wb'))

# def predict(x):
#     import pickle
#     predict = pickle.load(open('Real estate valuation data set.xlsx'))
#     x1 = predict['x1']
#     x2 = predict['x2']
#     x3 = predict['x3']
#     x4 = predict['x4']
#     x5 = predict['x5']
#     x6 = predict['x6']
#     return y_data
