Programming Data Structures And algorithms using Python Week 4 Solutions 2024

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Programming Data Structures And algorithms using Python Week 4 Solutions

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This course is an introduction to programming and problem solving in Python. It does not assume any prior knowledge of programming. Using some motivating examples, the course quickly builds up basic concepts such as conditionals, loops, functions, lists, strings and tuples. It goes on to cover searching and sorting algorithms, dynamic programming and backtracking, as well as topics such as exception handling and using files. As far as data structures are concerned, the course covers Python dictionaries as well as classes and objects for defining user defined datatypes such as linked lists and binary search trees.

Summary
Course Type Elective
Duration 8 weeks
Category
  • Computer Science and Engineering
  • Artificial Intelligence
  • Data Science
  • Foundations of Computing
  • Programming
Start Date 22 Jan 2024
End Date 15 Mar 2024
Exam Registration Ends 16 Feb 2024
Exam Date 24 Mar 2024 IST

Assignment Solutions : Week 4 Programming Assignment

Write Python functions as specified below. Paste the text for all functions together into the submission window.

  • You may define additional auxiliary functions as needed.
  • In all cases you may assume that the value passed to the function is of the expected type, so your function does not have to check for malformed inputs.
  • For each function, there are some public test cases and some (hidden) private test cases.
  • "Compile and run" will evaluate your submission against the public test cases.
  • "Submit" will evaluate your submission against the hidden private test cases and report a score on 100. There are 10 private testcases in all, each with equal weightage. You will get feedback about which private test cases pass or fail, though you cannot see the actual test cases.
  • Ignore warnings about "Presentation errors".

  1. We represent scores of batsmen across a sequence of matches in a two level dictionary as follows:

    {'match1':{'player1':57, 'player2':38}, 'match2':{'player3':9, 'player1':42}, 'match3':{'player2':41, 'player4':63, 'player3':91}
    

    Each match is identified by a string, as is each player. The scores are all integers. The names associated with the matches are not fixed (here they are 'match1', 'match2', 'match3'), nor are the names of the players. A player need not have a score recorded in all matches.

    Define a Python function orangecap(d) that reads a dictionary d of this form and identifies the player with the highest total score. Your function should return a pair (playername,topscore) where playername is a string, the name of the player with the highest score, and topscore is an integer, the total score of playername.

    The input will be such that there are never any ties for highest total score.

    For instance:

    >>> orangecap({'match1':{'player1':57, 'player2':38}, 'match2':{'player3':9, 'player1':42}, 'match3':{'player2':41, 'player4':63, 'player3':91}})
    ('player3', 100)
    
    >>> orangecap({'test1':{'Pant':84, 'Kohli':120}, 'test2':{'Pant':59, 'Gill':42}})
    ('Pant', 143)
    
  2. Let us consider polynomials in a single variable x with integer coefficients. For instance:

    3x4 - 17x2 - 3x + 5
    

    Each term of the polynomial can be represented as a pair of integers (coefficient,exponent). The polynomial itself is then a list of such pairs.

    We have the following constraints to guarantee that each polynomial has a unique representation:

    • Terms are sorted in descending order of exponent
    • No term has a zero cofficient
    • No two terms have the same exponent
    • Exponents are always nonnegative

    For example, the polynomial introduced earlier is represented as:

    [(3,4),(-17,2),(-3,1),(5,0)]
    

    The zero polynomial, 0, is represented as the empty list [], since it has no terms with nonzero coefficients.

    Write Python functions for the following operations:

    addpoly(p1,p2)
    multpoly(p1,p2)
    

    that add and multiply two polynomials, respectively.

    You may assume that the inputs to these functions follow the representation given above. Correspondingly, the outputs from these functions should also obey the same constraints.

    You can write auxiliary functions to "clean up" polynomials – e.g., remove zero coefficient terms, combine like terms, sort by exponent etc. Build a library of functions that can be combined to achieve the desired format.

    You may also want to convert the list representation to a dictionary representation and manipulate the dictionary representation, and then convert back.

    Some examples:

      
       >>> addpoly([(4,3),(3,0)],[(-4,3),(2,1)])
       [(2, 1),(3, 0)]
    
       Explanation: (4x^3 + 3) + (-4x^3 + 2x) = 2x + 3
    
       >>> addpoly([(2,1)],[(-2,1)])
       []
    
       Explanation: 2x + (-2x) = 0
    
       >>> multpoly([(1,1),(-1,0)],[(1,2),(1,1),(1,0)])
       [(1, 3),(-1, 0)]
    
       Explanation: (x - 1) * (x^2 + x + 1) = x^3 - 1
    
Solution : Copy & Paste
def orangecap(d):
    scr = dict()
    for msc in d:
        for p in d[msc]:
            if p in scr:
                scr[p] += d[msc][p]
            else:
                scr[p] = d[msc][p]

   
    pn=str()
    tscr=0
    for p in scr:
        if scr[p] > tscr:
            tscr = scr[p]
            pn = p

    return (pn, tscr)

def addpoly(p1, p2):
    r = list()
    for aq in range(len(p1)):
        
        for j in range(len(p2)):
            if p1[aq][1] == p2[j][1]:
                r += [(p1[aq][0] + p2[j][0], p1[aq][1])]

        
        for k in range(len(r)): 
            if r[k][1] == p1[aq][1]:
                break
        else:
            r += [p1[aq]]

    
    for j in range(len(p2)):
        for k in range(len(r)):
            if r[k][1] == p2[j][1]:
                break
        else:
            r += [p2[j]]

    r = [(c, e) for (c, e) in r if c != 0]  
    r.sort(key= lambda l : l[1], reverse=True) 

    return r

def multpoly(p1, p2):
    rv = list()
    for i in range(len(p1)):
        for j in range(len(p2)):
            rv = addpoly([(p1[i][0] * p2[j][0], p1[i][1] + p2[j][1])], rv)

    return(rv)

CRITERIA TO GET A CERTIFICATE :
  1. Average assignment score = 25% of average of best 6 assignments out of the total 8 assignments given in the course. (All assignments in a particular week will be counted towards final scoring - quizzes and programming assignments).
  2. Exam score = 75% of the proctored certification exam score out of 100
  3. Final score = Average assignment score + Exam score
YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met,you will not get the certificate even if the Final score >= 40/100.

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