Video Link : https://drive.google.com/file/d/1CsrhEKdDcSxuG7JZpuHaQMfKMrlrX9le/view?usp=sharing

Question 1 : Create a class Employee and then do the following

• Create a data member to count the number of Employees
• Create a constructor to initialize name, family, salary, department
• Create a function to average salary
• Create a Fulltime Employeeclass and it should inherit the properties of Employee class
• Create the instances of Fulltime Employeeclass and Employee class and call their member functions.

Explanation:

• created a class Employee and requested details about of name, family, salary, department
• created a function for averaging salary by using below lines:

avg_sal = Employee.Total_Salary / Employee.count

• created Full_time_employee class and inherited the properties of Employee by using below lines:

class Full_time_employee(Employee): def init(self): print('Full time employee(sub class)')

• created instances and called the members.

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Write a simple program that parse a Wiki page mentioned below and follow the instructions:https://en.wikipedia.org/wiki/Deep_learning

• Print out the title of the page
• Find all thelinks in the page (‘a’ tag)
• Iterate over each tag(above) then return the link using attribute "href" using getSave all the links in the file

Explanation:

• imported beautifulSoup, requests, re
• scrapped the data using "html.parser" with a time interval of 5 seconds.
• initialized a word document and scrapped the data into that word document using below lines:

page_response = requests.get(wiki_link, timeout=5)

wiki_content = BeautifulSoup(page_response.content, "html.parser")

textContent = [] f = open('wiki_data.txt', 'w') f.write( "title is" + wiki_content.title.string+ '\n')

for links in wiki_content.find_all('a',attrs={'href': re.compile("^http://")}): textContent.append(links.get('href')) f.write( repr(links.get('href')) + '\n')

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Question 3 : Using NumPy create random vector of size 20having only floatin the range 1-20. Then reshape the array to 4by 5Then replace the max in each row by 0(axis=1)

Explanation:

• imported numpy
• generated random numbers using np.random.randint(1, 20, 20)
• reshaped the matrix to 4*5 using Random_Integers.reshape((4,5))
• replaced the maximum with 0 using np.where(Reshaping == np.amax(Reshaping, axis=1, keepdims=True), 0, Reshaping)

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Learnings from ICP:

1. Inheritance in classes and some functions in class

2. Web scrapping using BeautifulSoup4

3. Generating Random Numbers

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Challenge:

Everything looks good and simple.