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Python code
data.csv
import pandas as pd from sklearn.linear_model import LinearRegression cars = pd.read_csv('data.csv') ohe_cars = pd.get_dummies(cars[['Car']]) X = pd.concat([cars[['Volume', 'Weight']], ohe_cars], axis=1) y = cars['CO2'] regr = LinearRegression() regr.fit(X, cars['CO2']) predictedCO2 = regr.predict([[2300, 1300,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]]) print(predictedCO2)
Car,Model,Volume,Weight,CO2 Toyoty,Aygo,1000,790,99 Mitsubishi,Space Star,1200,1160,95 Skoda,Citigo,1000,929,95 Fiat,500,900,865,90 Mini,Cooper,1500,1140,105 VW,Up!,1000,929,105 Skoda,Fabia,1400,1109,90 Mercedes,A-Class,1500,1365,92 Ford,Fiesta,1500,1112,98 Audi,A1,1600,1150,99 Hyundai,I20,1100,980,99 Suzuki,Swift,1300,990,101 Ford,Fiesta,1000,1112,99 Honda,Civic,1600,1252,94 Hundai,I30,1600,1326,97 Opel,Astra,1600,1330,97 BMW,1,1600,1365,99 Mazda,3,2200,1280,104 Skoda,Rapid,1600,1119,104 Ford,Focus,2000,1328,105 Ford,Mondeo,1600,1584,94 Opel,Insignia,2000,1428,99 Mercedes,C-Class,2100,1365,99 Skoda,Octavia,1600,1415,99 Volvo,S60,2000,1415,99 Mercedes,CLA,1500,1465,102 Audi,A4,2000,1490,104 Audi,A6,2000,1725,114 Volvo,V70,1600,1523,109 BMW,5,2000,1705,114 Mercedes,E-Class,2100,1605,115 Volvo,XC70,2000,1746,117 Ford,B-Max,1600,1235,104 BMW,216,1600,1390,108 Opel,Zafira,1600,1405,109 Mercedes,SLK,2500,1395,120
[122.45153299]
