input: Write a python function to train a linear regression model using given data and make predictions.
  assert train_and_predict(pd.DataFrame({'feature1': [1, 2, 3], 'feature2': [4, 5, 6], 'price': [10, 20, 30]})).tolist() == [10.0, 20.0, 30.0]
  assert train_and_predict(pd.DataFrame({'feature1': [2, 4, 6], 'feature2': [3, 6, 9], 'price': [14, 28, 42]})).tolist() == [14.0, 28.0, 42.0]
  assert train_and_predict(pd.DataFrame({'feature1': [1, 3, 5], 'feature2': [2, 6, 10], 'price': [12, 36, 60]})).tolist() == [12.0, 36.0, 60.0]
output: def train_and_predict(data):
      from sklearn.linear_model import LinearRegression
      X = data[['feature1', 'feature2']]
      y = data['price']
      model = LinearRegression()
      model.fit(X, y)
      predictions = model.predict(X)
      return predictions