├── iphone_price.csv
└── predict_iphone_price.py


/iphone_price.csv:
--------------------------------------------------------------------------------
 1 | version,price
 2 | 1,499
 3 | 2,599
 4 | 3,599
 5 | 4,649
 6 | 5,649
 7 | 6,749
 8 | 7,769
 9 | 8,799
10 | 9,949
11 | 10,999
12 | 11,1249
13 | 12,1399


--------------------------------------------------------------------------------
/predict_iphone_price.py:
--------------------------------------------------------------------------------
1 | import pandas
2 | import matplotlib.pyplot as plt
3 | from sklearn.linear_model import LinearRegression
4 | data = pandas.read_csv('iphone_price.csv')
5 | plt.scatter(data['version'], data['price'])
6 | plt.show()
7 | model = LinearRegression()
8 | model.fit(data[['version']], data[['price']])
9 | print(model.predict([[30]]))


--------------------------------------------------------------------------------