Problem 2 Your second and final task is to write a function called Assign Grades , which has the following two inputs df grades w final perc This is the df grades dataframe with the Final Perc column added to it In other words, you may assume that df grades w final perc has a column called Final perc which is each student's final percentage cutoffs This is a list that always has 4 entries The first entry is the minimum score needed for an A , the second entry is the minumum score needed for a B , the third entry is the minumum score needed for a C and the last entry is the miminum score needed for a D Any score below this fourth entry is awarded an F You may assume that all cutoffs are unique so you don't have to worry about ties Finally, you may assume that the cutoffs for better grades are always higher than the cutoffs for lower grades Your goal is to add to df grades w final perc a column called letter , which contains each student's letter grade ( as a string, i e , an A should added as A ) according to the inputted cutoff points Hint The pandas method cut could be very helpful here

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Question: Problem 2 Your second and final task is to write a function called Assign _ Grades, which has the following two inputs: df _ grades

Problem

2

Your second and final task is to write a function called "Assign

_

Grades", which has the following two inputs:

_

grades

_

_

final

_

perc: This is the df

_

grades dataframe with the Final

_

Perc column added to it

.

In other words, you may assume that df

_

grades

_

_

final

_

perc has a column called Final

_

perc which is each student's final percentage.

cutoffs: This is a list that always has

4

entries. The first entry is the minimum score needed for an

"

",

the second entry is the minumum score needed for a

"

",

the third entry is the minumum score needed for a

"

"

and the last entry is the miminum score needed for a

"

" .

Any score below this fourth entry is awarded an

"

" .

You may assume that all cutoffs are unique so you don't have to worry about ties. Finally, you may assume that the cutoffs for better grades are always higher than the cutoffs for lower grades.

Your goal is to add to df

_

grades

_

_

final

_

perc a column called "letter", which contains each student's letter grade

(

as a string, i

.

.,

an A should added as

"

")

according to the inputted cutoff points.

Hint: The pandas method "cut" could be very helpful here.

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