2. [Fall 2022] Homework-2#

2.1. Total number of points: 70#

3. Due date: September 22nd, 2022#

Before you submit this homework, make sure everything runs as expected. First, restart the kernel (in the menu, select Kernel → Restart) and then run all cells (in the menubar, select Cell → Run All). You can discuss with others regarding the homework but all work must be your own.

This homework will test your knowledge on basics of Python. The Python notebooks shared will be helpful to solve these problems.

Steps to evaluate your solutions:

Step-1: Ensure you have installed Anaconda (Windows: https://docs.anaconda.com/anaconda/install/windows/ ; Mac:https://docs.anaconda.com/anaconda/install/mac-os/ ; Linux: https://docs.anaconda.com/anaconda/install/linux/)

Step-2: Open the Jupyter Notebook by first launching the anaconda software console

Step-3: Open the .ipynb file and write your solutions at the appropriate location “# YOUR CODE HERE”

Step-4: You can restart the kernel and click run all (in the menubar, select Cell → Run All) on the center-right on the top of this window.

Step-5: Now go to “File” then click on “Download as” then click on “Notebook (.ipynb)” Please DO NOT change the file name and just keep it as .ipynb file format

Step-6: Go to lms.rpi.edu and upload your homework at the appropriate link to submit this homework.

4. Please note that for any question in this assignment you will receive points ONLY if your solution passes all the test cases including hidden testcases as well. So please make sure you try to think all possible scenarios before submitting your answers.#

  • Note that hidden tests are present to ensure you are not hardcoding.

  • If caught cheating:

    • you will receive a score of 0 for the 1st violation.

    • for repeated incidents, you will receive an automatic ‘F’ grade and will be reported to the dean of Lally School of Management.

5. Q1 [10 points]. Write a function that takes a number and checks if it is a composite number. Return True if its a composite number or else False.#

  • A number is composite when it has more than two factors – which means apart from getting divided by 1 and the number itself, it can also be divided by at least one positive integer.

def isComposite(num):
    '''Write a program to check if a given number is a composite number or not.
    A number is composite if there are more than two factors 1, itself, and atleast one positive integer. 
    The program returns -- True, if it is a composite number; otherwise False. Assume that you will be receiving only positive integers (>=0) as the input parameters. 
    '''
    # YOUR CODE HERE
    raise NotImplementedError()

#Test cell-1 [6 pts]
#DO NOT MODIFY/DELETE THIS CELL 

'''case-1'''
number=1
assert isComposite(number) == True

'''case-2'''
number = 10
assert isComposite(number)== True

'''case-3'''
number = 97
assert isComposite(number) == False

#Test cell-2 [2 pts]
#DO NOT MODIFY/DELETE THIS CELL 

#2 [2 pts]
#DO NOT MODIFY/DELETE THIS CELL

6. Q2 [5 points]. import the numpy package as np.#

'''Note that ONLY if you get this solution right all the below questions will be executed'''

# YOUR CODE HERE
raise NotImplementedError()

#Test cell-3 [5 pts]
#DO NOT MODIFY/DELETE THIS CELL 
assert np.prod([1,2,3])==6

7. Q3 [5 points]. Create a numpy array called arr3 of zeros of size 10 where the sixth element is 1.#

# YOUR CODE HERE
raise NotImplementedError()

#Test cell-4 [3 pts]
#DO NOT MODIFY/DELETE THIS CELL 

assert isinstance(arr3, np.ndarray)
assert arr3[:5].all() == 0
assert arr3[5] == 1

#Test cell-5 [2 pts]
#DO NOT MODIFY/DELETE THIS CELL

8. Q4 [5 points]. Create a numpy array arr4 with elements 1,3,5,7,9,11 (in the same order)#

9. Now create a new array arr41 whose elements are twice the value of each element in arr4 at the same index respectively.#

# YOUR CODE HERE
raise NotImplementedError()

#Test cell-6 [4 pts]
#DO NOT MODIFY/DELETE THIS CELL 

assert isinstance(arr4, np.ndarray)
assert arr4[2] == 5
assert arr41[2] == 10
assert arr41[1] == 6

#Test cell-7 [1 pts]
#DO NOT MODIFY/DELETE THIS CELL

10. Q5 [10 points]. Return the sum of absolute values of elements that occur maximum number of times and minimum number of times in a numpy array.#

  • abs() is a function used to return absolute values of a given number. For example, abs(-3) = 3 and abs(3) = 3

  • if there are two (or more) elements occuring with same frequency and are occurring maximum number of times, choose the element that is smaller in value

  • if there are two (or more) elements occuring with same frequency and are occurring minimum number of times, choose the element that is smaller in value

def SumMinMax(arr5):
    """Returns the difference between 
    element that occurs maximum number of times and element that occurs minimum number of times
    """
    # YOUR CODE HERE
    raise NotImplementedError()

#Test cell-8 [10 pts]
#DO NOT MODIFY/DELETE THIS CELL 

arr3=np.array([1,0,1,0,2,1])
assert SumMinMax(arr3)==3

arr3=np.array([0])
assert SumMinMax(arr3)==0

arr3=np.array([1,2,3,1,2,3,1,1,0,0,4])
assert SumMinMax(arr3)==5

arr3=np.array([1,2,3,0])
assert SumMinMax(arr3)==0

import pandas as pd

'''Make sure you run this cell before executing the cells below'''

11. Q6 [5 points]. Please follow the instructions very carefully#

  • Create a list l6 and assign values 1, 2, 3, 4, 5, 6 to this list in the same order as listed here.

  • Use l6 to create a series S6 with a default index

 # YOUR CODE HERE
 raise NotImplementedError()

#Test cell-9 [3 pts]
#DO NOT MODIFY/DELETE THIS CELL 

assert len(l6)==6
assert max(l6)==6
assert S6[3]==4

#Test cell-10 [2 pts]
#DO NOT MODIFY/DELETE THIS CELL

12. Q7 [10 points]. This function takes a list l7 as an input and creates 2 more lists (l71 and l72) by manipulating l7 as follows#

  • l71 – copy l7 into l71 and add the 1st element of l7 to the end of l71

  • l72 – copy l71 into l72 and add the mean value of l71 to the end of l72

  • Now use l7, l71 and l72 to create a data frame df with corresponding column names as first, second and third

  • return this dataframe df

def createDF(l7):
    """Returns the dataframe that is built using an original list
    """
    # YOUR CODE HERE
    raise NotImplementedError()

#Test cell-11 [5 pts]
#DO NOT MODIFY/DELETE THIS CELL 

'''case-1'''
list7=[2,4,6,8]
assert list(createDF(list7)['second'])[:5]==[2.0,4.0,6.0,8.0,2.0]

'''case-2'''
list7=[2,4,6,8]
assert list(createDF(list7)['first'])[:4]==[2,4,6,8]

#Test cell-12 [5 pts]
#DO NOT MODIFY/DELETE THIS CELL

13. Q8 [10 points]. Read the .csv file from this url and load it into dataframe ‘df’#

  • Using pandas dataframe operations, output the total number of rows with survived==1 and gender is female as var81.

  • Using pandas dataframe operations, output the total number of rows with survived==1 and gender is male as var82.

url='https://raw.githubusercontent.com/lmanikon/lmanikon.github.io/master/teaching/datasets/titanic.csv'
# YOUR CODE HERE
raise NotImplementedError()

#Test cell-13 [6 pts]
#DO NOT MODIFY/DELETE THIS CELL 

assert df['age'].sum()==21205.17
assert df.isnull().sum().sum()==869
assert var82==109

#Test cell-14 [4 pts]
#DO NOT MODIFY/DELETE THIS CELL

14. Q9 [10 points]. Read the .csv file from this url and load it into dataframe df#

15. Using groupby operation over embark_town and gender,#

  • assign var9 as the total number of people survived (survived is 1), where they embarked (embark_town) at Southampton and are female (gender is female).

url='https://raw.githubusercontent.com/lmanikon/lmanikon.github.io/master/teaching/datasets/titanic.csv'
# YOUR CODE HERE
raise NotImplementedError()

#Test cell-15 [10 pts]
#DO NOT MODIFY/DELETE THIS CELL 

assert df['age'].sum()==21205.17
assert df.isnull().sum().sum()==869
assert len(df.columns)==15
assert var9==140