Train the same model (all rows, age_years → price_lakh).
Store the intercept (the price the line gives at age 0), rounded to 2 decimals, in result.
import io
import pandas as pd
cars = pd.read_csv(io.StringIO("""car_id,age_years,km_driven_thousand,fuel,owners,price_lakh
1,5,32,Diesel,1,6.77
2,1,3,Petrol,1,8.59
3,2,11,Petrol,2,7.28
4,2,23,Petrol,1,7.17
5,4,37,Petrol,1,5.86
6,5,39,Diesel,1,6.68
7,6,74,Diesel,1,5.01
8,5,57,Diesel,1,6.00
9,7,68,Petrol,1,4.04
10,7,77,Diesel,2,4.41
11,3,37,Petrol,1,6.29
12,7,59,Petrol,3,4.12
13,1,11,Petrol,2,7.47
14,2,18,Petrol,1,7.34
15,11,113,Petrol,3,1.12
16,6,75,Diesel,1,5.24
17,7,77,Diesel,2,4.72
18,10,128,Petrol,1,2.01
19,1,3,Petrol,1,7.74
20,11,143,Diesel,2,2.17
21,8,95,Petrol,2,3.41
22,8,96,Petrol,1,3.27
23,3,46,Diesel,2,6.90
24,3,30,Petrol,1,7.01
25,1,17,Diesel,1,8.77
26,1,15,Petrol,1,8.07
27,11,101,Petrol,1,1.94
28,6,78,Petrol,1,4.17
29,11,136,Diesel,2,1.79
30,8,99,Petrol,2,3.11
31,5,56,Petrol,1,5.76
32,7,77,Petrol,1,4.60
33,5,60,Petrol,1,5.08
34,3,33,Diesel,1,7.18
35,2,29,Petrol,1,7.59
36,7,94,Diesel,1,4.62
37,6,57,Diesel,1,5.47
38,6,54,Diesel,1,5.88
39,3,38,Petrol,1,7.21
40,9,114,Petrol,2,2.84
41,9,125,Petrol,3,2.14
42,9,94,Petrol,1,2.47
43,11,97,Diesel,1,2.99
44,1,15,Diesel,1,9.08
45,10,90,Diesel,3,2.82
46,11,112,Petrol,2,1.03
47,4,44,Petrol,1,6.53
48,4,52,Petrol,1,6.23
49,2,19,Diesel,1,8.23
50,8,87,Diesel,1,4.03
51,2,34,Petrol,1,7.31
52,6,85,Diesel,2,5.18
53,8,87,Petrol,3,2.80
54,5,66,Diesel,1,6.06
55,11,104,Petrol,2,0.90
56,7,69,Petrol,1,4.79
57,9,126,Petrol,2,1.95
58,10,108,Petrol,1,2.34
59,5,67,Petrol,2,5.40
60,4,40,Petrol,2,6.04"""))Store your final answer in a variable named result.
Each hint gives a little more help. Try on your own first.
Run your code to see the output here.