### Read the pickle file

with open$(\text{'}$fuel$\_$economy.data.pickle', $\text{'}$rb$\text{'})$ as fid:

$($data$\_$var$\_$names, manufacturer$\_$names, mpgData$)=$ pickle.load$($fid$)$

comp$116.$array$\_$to$\_$html$($mpgData$,$ row$\_$names$=$manufacturer$\_$names, col$\_$names$=$data$\_$var$\_$names,

title$=\text{'}2017$ Fuel Economy data by Manufacturer'$)2017$ Fuel Economy data by Manufacturer

Real$-$World Comb MPG Real$-$World Comb CO$2$ g$/$mi Weight $($lbs$)$ HP $0-60$ Time $($s$)$

GM $22\mathrm{.}9388\mathrm{.}04520\mathrm{.}0265\mathrm{.}08\mathrm{.}0$

Toyota $25\mathrm{.}3351\mathrm{.}04059\mathrm{.}0216\mathrm{.}08\mathrm{.}5$

Ford $22\mathrm{.}9388\mathrm{.}04360\mathrm{.}0262\mathrm{.}07\mathrm{.}9$

FCA $21\mathrm{.}2420\mathrm{.}04510\mathrm{.}0280\mathrm{.}07\mathrm{.}5$

Nissan$-$Mitsubishi $27\mathrm{.}1327\mathrm{.}03770\mathrm{.}0201\mathrm{.}08\mathrm{.}9$

Honda $29\mathrm{.}4302\mathrm{.}03595\mathrm{.}0203\mathrm{.}08\mathrm{.}1$

Hyundai $28\mathrm{.}6311\mathrm{.}03458\mathrm{.}0176\mathrm{.}08\mathrm{.}9$

Subaru $28\mathrm{.}5312\mathrm{.}03724\mathrm{.}0181\mathrm{.}09\mathrm{.}3$

VW $26\mathrm{.}5335\mathrm{.}03894\mathrm{.}0225\mathrm{.}07\mathrm{.}9$

Kia $27\mathrm{.}2327\mathrm{.}03592\mathrm{.}0186\mathrm{.}08\mathrm{.}8$

Mercedes $23\mathrm{.}1385\mathrm{.}04536\mathrm{.}0288\mathrm{.}07\mathrm{.}0$

BMW $25\mathrm{.}9341\mathrm{.}04107\mathrm{.}0257\mathrm{.}07\mathrm{.}0$

Mazda $29\mathrm{.}0306\mathrm{.}03569\mathrm{.}0178\mathrm{.}08\mathrm{.}9$ For the rest of this quistion, you should use comparisons and boolean values to select subsets. You should not make use of the absolute index of the data.

For example, you know that "Real$-$World Comb MPG$"$ is in the column with index $0,$ and "Ford" is the row with index $2$ in mpgData. But do not use mpgData$[2,0]$ to get to the real$-$world mpg data for Ford. Look at the course lecture on this topic to refresh.

Compute the list of all manufacturers whose "Real$-$World Comb MPG$"$ was higher than $25.$

# Your code here

Find the list of all manufacturers whose real$-$world comb MPG was higher that $25$ AND whose $0-60$ time is less than $8$ seconds

# Your code here

What was the HP for GM vehicles?

# Your code here

What were the real$-$world comb MPG and weight for VW$?$

# Your code here

Create a Numpy array that has the real$-$world comb MPG$,$ weight and $0-60$ time $($in that order$)$ for Ford, VW and Honda $($in that order$)$

# Your code here

Click to add a cell.