e$)$ Suppose I have a new query: Qe: For every department, display the min, median, and max graduation years. Use your $.$txt file containing de$-$normalized data from part$-$b to answer Qe with python instead of SQL$.$ Note that this solution should not use SQLite or SQL language. Your solution should work for any input, not just for specific department in your data.

My text file contains

$(1,$ 'boars head', $\text{'}10$ main st$\text{'},2022,\text{'}$CSC$101\text{'},1,\text{'}$A$\text{'},\text{'}$CSC$101\text{'},$ 'Computer Science', $4)$

$(1,$ 'boars head', $\text{'}10$ main st$\text{'},2022,\text{'}$DSC$550\text{'},1,\text{'}$D$\text{'},\text{'}$DSC$550\text{'},$ 'Data Science', $4)$

$(2,$ 'taco king', $\text{'}20$ south st$\text{'},2022,\text{'}$CSC$101\text{'},2,\text{'}$B$\text{'},\text{'}$CSC$101\text{'},$ 'Computer Science', $4)$

$(2,$ 'taco king', $\text{'}20$ south st$\text{'},2022,\text{'}$DSC$550\text{'},2,\text{'}$B$\text{'},\text{'}$DSC$550\text{'},$ 'Data Science', $4)$

$(3,$ 'blue sky$\text{'},\text{'}30$ east st$\text{'},2020,$ 'ECON$110\text{'},3,\text{'}$B$\text{'},$ 'ECON$110\text{'},$ 'Economics', $4)$

$(3,$ 'blue sky$\text{'},\text{'}30$ east st$\text{'},2020,$ 'MATH$220\text{'},3,\text{'}$C$\text{'},$ 'MATH$220\text{'},$ 'Mathematics', $4)$

$(4,$ 'Blake eats', $\text{'}40$ north st$\text{'},2021,$ 'ECON$110\text{'},4,\text{'}$A$\text{'},$ 'ECON$110\text{'},$ 'Economics', $4)$

$(5,$ 'mike cheddar', $\text{'}50$ west st$\text{'},2020,$ 'MATH$220\text{'},5,\text{'}$A$\text{'},$ 'MATH$220\text{'},$ 'Mathematics', $4)$

my code so far is below, but it wont execute $-$ please advise the correct code

def compute$\_$median$($values$)$:

sorted$\_$values $=$ sorted $($values$)$

n $=$ len$($sorted$\_$values$)$

if n$\%2==1$:

return sorted$\_$values$[$n$//2]$

else:

mid $=$ n$//2$

return$($sorted$\_$values$[$mid $-1]+$ sorted$\_$values$[$mid$])/2\mathrm{.}0$

def run$\_$data$\_$file$($data$\_$file$)$:

department$\_$data $=\{\}$

with open$($data$\_$file,$\text{'}$r$\text{'})$ as file:

lines $=$ file.readlines$()$

lines $=$ lines$[1$:$]$

for line in lines:

parts $=$ line.strip$().$split$(\text{'}\backslash$t$\text{'})$

department,grad$\_$year$=$parts$[4],$float$($parts$[3])$

if department not in department$\_$data:

department$\_$data$[$department$]=[]$

department$\_$data$[$department$].$append$($grad$\_$year$)$

for department, grad$\_$years in department$\_$data.items$()$:

max$\_$grad$\_$year$=$max$($grad$\_$years$)$

median$\_$grad$\_$year$=$compute$\_$median$($grad$\_$years$)$

min$\_$grad$\_$year $=$ min$($grad$\_$year$)$

print$($f$"$Department:$\{$department$\}")$

print$($f$"$Max Graduation Year:$\{$max$\_$grad$\_$year$\}")$

print$($f$"$Median Graduation Year:$\{$median$\_$grad$\_$year$\}")$

print$($f$"$Min Graduation Year:$\{$min$\_$grad$\_$year$\}")$

print$()$

data$\_$file $=$ 'inputfile.txt$\text{'}$

run$\_$data$\_$file$($data$\_$file$)$