I am having difficulty with #2 and # 4. i realize I could go through the data to find it but I believe the point is for me to write a code to find it. I am using R. Below are the directions and the data set below that. Thanks!

Copy the mtcars dataset into a new variable (called it myCars ), so that if you mess up, you can start again very easily (by copying mtcars into myCars again).

Step 1:

1)What is the highest hp?

2)Which car has the highest hp?

Step 2

3) What is the highest mpg?

4)Which car has the highest mpg?

5)Create a sorteddataframe, based on mpg

Step 3:

Which car has the best combination of mpg and hp?

6) What logic did you use?

7) Which car?

Step 4:

Which car has best car combination of mpg and hp, where mpg and hp must be given equal weight?

myCars mpg cyl disp hp drat wt qsec vs am gear carb 21.0 6 160.0 110 3.90 2.620 16.46 0 144 21.0 6 160.0 110 3.90 2.875 17.02 0 1 22.8 4 108.0 93 3.85 2.320 18.61 1 141 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 32 Valiant Duster 360 Merc 240D Merc 230 Merc 280 Merc 280C Merc 450SE Merc 450SL Merc 450SLO Cadillac Fleetwood 10. 8 472.0 205 2.93 5.250 17.98 0 0 3 4 Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 034 Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 003 4 Fiat 128 Honda Civic Toyota Corolla Toyota Corona Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 AMC Javelin Camaro Z28 Pontiac Firebird 19.2 8 400.0 175 3.08 3. 845 17.05 0 03 2 Fiat X1-9 Porsche 914-2 Lotus Europa Ford Pantera L Ferrari Ding Maserati Bora Volvo 142E 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 14.3 8 360.0 245 3.21 3.570 15. 84 0 0 3 4 24.4 4 146.7 62 3.69 3.190 20.00 1 0 42 22.8 4 140.8 95 3.92 3.150 22.90 1 0 42 19.2 6 167.6 123 3.92 3.440 18.30 1 0 17.8 6 167.6 123 3.92 3.440 18.90 1 0 44 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 17.3 8 275.8 180 3.07 3.730 17.60 0 0 15.2 8 275.8 180 3.07 3.780 18.00 0 03 32.4 4 78.7 66 4.08 2.200 19.47 1 1 41 30.4 4 75.7 52 4.93 1.615 18.52 1 1 33.9 4 71.1 65 4.22 1.835 19.90 1 1 41 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 13.3 8 350.0 245 3.73 3.840 15.41 0 0 27.3 4 79.0 66 4.08 1.935 18.90 1 141 26.0 4 120.3 91 4.43 2.140 16.70 0 1 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 15.8 8 351.0 264 4.22 3.170 14.50 0 15 19.7 6 145.0 175 3.62 2.770 15.50 0 1 15.0 8 301.0 335 3.54 3.570 14.60 0 15 21. 4 121.0 109 4.11 2.780 18.60 1 142