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from sklearn import datasets, linear_model

import matplotlib.pyplot as plt

import numpy as np

import os

import pandas as pd

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn import datasets, linear_model
from sklearn.metrics import mean_squared_error
import os
bmi = pd.read_csv('../input/bmidataset/bmi.csv')

bmi_x = bmi.Weight[:, np.newaxis]

bmi_x_train = bmi_x[:-30]

bmi_x_test = bmi_x[-30:]

bmi_y_train = bmi.Index[:-30]
bmi_y_test = bmi.Index[-30:]

model = linear_model.LinearRegression()

model.fit(bmi_x_train, bmi_y_train)

bmi_y_predicted = model.predict(bmi_x_test)

plt.scatter(bmi_x_test, bmi_y_test)
plt.plot(bmi_x_test, bmi_y_predicted)
plt.show()