Saturday 20 January 2024
Top 20 Python Dictionary Questions with answer
Python Coding January 20, 2024 Python Coding Challenge No comments
Question 1:
What is a dictionary in Python?
a) A collection of ordered elements
b) A collection of unordered elements
c) A single element
d) A data type
Question 2:
How do you create an empty dictionary in Python?
a) empty_dict = {}
b) empty_dict = dict()
c) empty_dict = new dict()
d) Both a and b
Question 3:
How do you access the value associated with a specific key in a dictionary?
a) dictionary.value(key)
b) dictionary[key]
c) dictionary.get(key)
d) dictionary.retrieve(key)
Question 4:
What is the purpose of the len() function when used with a dictionary?
a) It returns the total number of key-value pairs in the dictionary
b) It returns the last key in the dictionary
c) It returns the length of each value in the dictionary
d) It returns the sum of all values in the dictionary
Question 5:
How do you add a new key-value pair to a dictionary?
a) dictionary.add(key, value)
b) dictionary[key] = value
c) dictionary.insert(key, value)
d) dictionary.append(key, value)
Question 6:
What is the key difference between a dictionary and a list in Python?
a) Dictionaries are ordered, while lists are unordered
b) Dictionaries are mutable, while lists are immutable
c) Dictionaries can contain only numeric elements
d) Dictionaries are unordered and do not allow duplicate keys
Question 7:
How do you check if a key is present in a dictionary?
a) key in dictionary
b) dictionary.contains(key)
c) dictionary.exists(key)
d) key.exists(dictionary)
Question 8:
What does the dictionary.keys() method return?
a) The values of the dictionary
b) The keys of the dictionary
c) The key-value pairs of the dictionary
d) The length of the dictionary
Question 9:
How do you remove a key-value pair from a dictionary?
a) dictionary.remove(key)
b) dictionary.discard(key)
c) dictionary.delete(key)
d) All of the above
Question 10:
Which method is used to retrieve the value associated with a key, and if the key is not present, it returns a default value?
a) dictionary.get(key, default)
b) dictionary.retrieve(key, default)
c) dictionary.value(key, default)
d) dictionary.fetch(key, default)
Question 11:
What is the purpose of the pop() method in Python dictionaries?
a) Adds an element to the dictionary
b) Removes the last element from the dictionary and returns its value
c) Removes the first occurrence of the specified element
d) Removes the key-value pair for a specified key
Question 12:
How do you update the value associated with a key in a dictionary?
a) dictionary.update(key, new_value)
b) dictionary[key] = new_value
c) dictionary.modify(key, new_value)
d) dictionary.change_value(key, new_value)
Question 13:
What is the output of the following code?
my_dict = {"a": 1, "b": 2, "c": 3}
del my_dict["b"]
print(my_dict)
a) {"a": 1, "b": 2, "c": 3}
b) {"a": 1, "c": 3}
c) {"a": 1, "b": 2}
d) Raises an error
Question 14:
How do you iterate over the keys of a dictionary?
a) for key in dictionary.keys():
b) for key in dictionary:
c) for key in dictionary.values():
d) for key in dictionary.items():
Question 15:
What is the purpose of the values() method in Python dictionaries?
a) Returns the keys of the dictionary
b) Returns the values of the dictionary
c) Returns the key-value pairs of the dictionary
d) Returns the length of the dictionary
Question 16:
Which method is used to clear all key-value pairs from a dictionary?
a) dictionary.clear()
b) dictionary.remove_all()
c) dictionary.delete()
d) dictionary.empty()
Question 17:
What is the purpose of the items() method in Python dictionaries?
a) Returns the keys of the dictionary
b) Returns the values of the dictionary
c) Returns the key-value pairs of the dictionary
d) Returns the length of the dictionary
Question 18:
What is the output of the following code?
my_dict = {"apple": 3, "banana": 5, "cherry": 2}
sorted_dict = dict(sorted(my_dict.items()))
print(sorted_dict)
a) {"apple": 3, "banana": 5, "cherry": 2}
b) {"cherry": 2, "apple": 3, "banana": 5}
c) {"banana": 5, "apple": 3, "cherry": 2}
d) Raises an error
Question 19:
How do you create a dictionary with keys as numbers from 1 to 5 and values as their squares?
a) squares = {i: i ** 2 for i in range(1, 6)}
b) squares = {i: i * i for i in range(1, 6)}
c) squares = {i: i ** 2 for i in [1, 2, 3, 4, 5]}
d) All of the above
Question 20:
What is the purpose of the copy() method in Python dictionaries?
a) Creates a shallow copy of the dictionary
b) Creates a deep copy of the dictionary
c) Returns the reversed dictionary
d) Appends a copy of the dictionary to itself
Answer Key:
- b) A collection of unordered elements
- d) Both a and b
- b) dictionary[key]
- a) It returns the total number of key-value pairs in the dictionary
- b) dictionary[key] = value
- d) Dictionaries are unordered and do not allow duplicate keys
- a) key in dictionary
- b) The keys of the dictionary
- d) All of the above
- a) dictionary.get(key, default)
- b) Removes the last element from the dictionary and returns its value
- b) dictionary[key] = new_value
- b) {"a": 1, "c": 3}
- b) for key in dictionary:
- b) Returns the values of the dictionary
- a) dictionary.clear()
- c) Returns the key-value pairs of the dictionary
- b) {"cherry": 2, "apple": 3, "banana": 5}
- a) squares = {i: i ** 2 for i in range(1, 6)}
- a) Creates a shallow copy of the dictionary
Top 20 Python Set Questions with answer
Python Coding January 20, 2024 Python Coding Challenge No comments
Question 1:
What is a set in Python?
a) A collection of ordered elements
b) A collection of unordered elements
c) A single element
d) A data type
Question 2:
How do you create an empty set in Python?
a) set()
b) empty_set = {}
c) empty_set = set()
d) Both b and c
Question 3:
How do you add an element to a set in Python?
a) set.insert(element)
b) set.add(element)
c) set.append(element)
d) set.include(element)
Question 4:
What is the key difference between a set and a list in Python?
a) Sets are ordered, while lists are unordered
b) Sets are mutable, while lists are immutable
c) Sets can contain only numeric elements
d) Sets are unordered and do not allow duplicate elements
Question 5:
How do you check if an element is present in a set?
a) element in set
b) set.contains(element)
c) set.exists(element)
d) element.exists(set)
Question 6:
What happens when you try to add a duplicate element to a set?
a) The element is added successfully
b) Python raises an exception
c) The duplicate element is ignored, and the set remains unchanged
d) The set is automatically sorted
Question 7:
How do you remove an element from a set?
a) set.remove(element)
b) set.delete(element)
c) set.pop(element)
d) set.discard(element)
Question 8:
What is the purpose of the len() function when used with a set?
a) It returns the total number of elements in the set
b) It returns the last element of the set
c) It returns the length of each element in the set
d) It returns the sum of all elements in the set
Question 9:
How do you create a set with elements from 1 to 5 in Python?
a) set = {1, 2, 3, 4, 5}
b) set = range(1, 6)
c) set = set(1, 6)
d) set = {range(1, 6)}
Question 10:
What is the purpose of the pop() method in Python sets?
a) Removes the last element from the set
b) Removes a random element from the set and returns it
c) Removes the first occurrence of the specified element
d) Sorts the elements of the set
Question 11:
What is the difference between a set and a frozenset in Python?
a) Sets are mutable, while frozensets are immutable
b) Sets are unordered, while frozensets are ordered
c) Sets can contain only numeric elements
d) Sets allow duplicate elements, while frozensets do not
Question 12:
Which of the following statements is true regarding the union of two sets?
a) The union operator for sets is +
b) The union of two sets is the intersection of their elements
c) The union of two sets contains all unique elements from both sets
d) The union of two sets results in an empty set
Question 13:
What is the purpose of the clear() method in Python sets?
a) Clears all elements from the set
b) Returns a clear copy of the set
c) Clears only the first element from the set
d) Clears the set if a specific element is provided
Question 14:
Which method is used to find the intersection of two sets in Python?
a) set.intersection(set2)
b) set.intersect(set2)
c) set.common(set2)
d) set.and(set2)
Question 15:
What is the output of the following code?
set1 = {1, 2, 3}
set2 = {3, 4, 5}
result = set1.union(set2)
print(result)
a) {1, 2, 3, 4, 5}
b) {1, 2, 3}
c) {3, 4, 5}
d) {1, 2, 4, 5}
Question 16:
How do you check if a set is a subset of another set?
a) set.is_subset(other_set)
b) set.subset_of(other_set)
c) set.issubset(other_set)
d) set.contains_subset(other_set)
Question 17:
What does the difference() method do when applied to two sets?
a) Returns the union of the two sets
b) Returns the intersection of the two sets
c) Returns the difference between the two sets
d) Returns the symmetric difference between the two sets
Question 18:
What is the purpose of the symmetric_difference() method in Python sets?
a) Returns the union of the two sets
b) Returns the intersection of the two sets
c) Returns the difference between the two sets
d) Returns the symmetric difference between the two sets
Question 19:
What is the output of the following code?
set1 = {1, 2, 3}
set2 = {3, 4, 5}
result = set1.difference(set2)
print(result)
a) {1, 2, 3, 4, 5}
b) {1, 2}
c) {3}
d) {4, 5}
Question 20:
What is the purpose of the issuperset() method in Python sets?
a) Checks if the set is a proper superset of another set
b) Checks if the set is a subset of another set
c) Checks if the set is equal to another set
d) Checks if the set contains all elements of another set
Answer Key:
- b) A collection of unordered elements
- c) empty_set = set()
- b) set.add(element)
- d) Sets are unordered and do not allow duplicate elements
- a) element in set
- c) The duplicate element is ignored, and the set remains unchanged
- a) set.remove(element)
- a) It returns the total number of elements in the set
- a) set = {1, 2, 3, 4, 5}
- b) Removes a random element from the set and returns it
- a) Sets are mutable, while frozensets are immutable
- c) The union of two sets contains all unique elements from both sets
- a) Clears all elements from the set
- a) set.intersection(set2)
- a) {1, 2, 3, 4, 5}
- c) set.issubset(other_set)
- d) Returns the symmetric difference between the two sets
- d) Returns the symmetric difference between the two sets
- b) {1, 2}
- a) Checks if the set is a proper superset of another set
Friday 19 January 2024
Introducing Microsoft Power BI Alberto Ferrari and Marco Russo (Free PDF)
Python Coding January 19, 2024 Books No comments
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book.
Introducing Microsoft Power BI enables you to evaluate when and how to use Power BI. Get inspired to improve business processes in your company by leveraging the available analytical and collaborative features of this environment.
Be sure to watch for the publication of Alberto Ferrari and Marco Russo's upcoming retail book, Analyzing Data with Power BI and Power Pivot for Excel (ISBN 9781509302765).
Free PDF Download: Introducing Microsoft Power BI Alberto Ferrari and Marco Russo
Power Bi Report Development Crash Course
Python Coding January 19, 2024 BI, Coursera No comments
What you'll learn
Create Relationship in PowerBI
Create Visualization in PowerBI
Publish a report in powerbi service
Join Free: Power Bi Report Development Crash Course
About this Guided Project
All The Best !!
Prepare, Clean, Transform, and Load Data using Power BI
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What you'll learn
Prepare and Clean Data using Power BI
Transform and Load Data using Power BI
Join Free: Prepare, Clean, Transform, and Load Data using Power BI
About this Guided Project
Build an Income Statement Dashboard in Power BI
Python Coding January 19, 2024 BI, Coursera No comments
What you'll learn
Build an Income statement dashboard in Power BI
Visualize the income statement using cards, table and column charts
Transform & clean data in the Power Query editor
Join Free: Build an Income Statement Dashboard in Power BI
About this Guided Project
Create a Sales Dashboard using Power BI
Python Coding January 19, 2024 BI, Coursera No comments
What you'll learn
Build an attractive and interactive sales dashboard with all the necessary visualizations in a black and blue theme
Visualize sales data using bar charts & pie charts
Create interactive maps to visualize sales data by countries and markets
Join Free: Create a Sales Dashboard using Power BI
About this Guided Project
HR Analytics- Build an HR dashboard using Power BI
Python Coding January 19, 2024 BI, Coursera No comments
What you'll learn
Build an attractive and eye-catching HR dashboard
Visualize gender & racial diversity using graphs & charts in Power BI
Explore buttons, themes, filters & slicers to make the dashboard interactive & smart
Join Free: HR Analytics- Build an HR dashboard using Power BI
About this Guided Project
Data-Driven Decisions with Power BI
Python Coding January 19, 2024 BI, Coursera No comments
There are 5 modules in this course
New Power BI users will begin the course by gaining a conceptual understanding of the Power BI desktop application and the Power BI service. Learners will explore the Power BI interface while learning how to manage pages and understand the basics of visualizations. Learners can download a course dataset and engage in numerous hands-on experiences to discover how to import, connect, clean, transform, and model their own data in the Power BI desktop application.
Join Free: Data-Driven Decisions with Power BI
Learners will investigate reports, learn about workspaces, and practice viewing, creating, and publishing reports to the Power BI service. Finally, learners will become proficient in the creation and utilization dashboards.
Use Power Bi for Financial Data Analysis
Python Coding January 19, 2024 No comments
What you'll learn
Navigate and understand the process of importing data into Power Bi.
Use Power Query to clean data before constructing visuals and reports. Determine relationships between data and use reference tables in Power Bi.
Create and design a reporting dashboard with dynamic features. Publish and share your report
Join Free:Use Power Bi for Financial Data Analysis
About this Guided Project
Build Dashboards in Power BI
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What you'll learn
Build a Dashboard in Power BI by building a report and visuals.
Build a report with visuals.
Create a dashboard and pin visuals.
Join Free: Build Dashboards in Power BI
About this Guided Project
Getting Started with Power BI Desktop
Python Coding January 19, 2024 BI, Coursera No comments
What you'll learn
Import and Transform Data with Power BI Desktop
Visualize Data with Power BI Desktop
Join Free: Getting Started with Power BI Desktop
About this Guided Project
Top 20 Python Tuple Questions
Python Coding January 19, 2024 Python Coding Challenge No comments
What is a tuple in Python?
a) A collection of unordered elements
b) A collection of ordered elements
c) A single element
d) A data type
Question 2:
How do you create an empty tuple in Python?
a) tuple()
b) empty_tuple = ()
c) empty_tuple = tuple()
d) Both b and c
Question 3:
How do you access the first element of a tuple?
a) tuple[0]
b) tuple.first()
c) tuple.first
d) tuple.get(0)
Question 4:
Which of the following statements is used to add an element to a tuple?
a) tuple.insert(0, element)
b) Tuples are immutable, so elements cannot be added once a tuple is created
c) tuple.add(element)
d) tuple.extend(element)
Question 5:
What is the key difference between a tuple and a list in Python?
a) Tuples are mutable, while lists are immutable
b) Tuples are ordered, while lists are unordered
c) Tuples are immutable, while lists are mutable
d) Tuples can contain only numeric elements
Question 6:
How do you check if an element is present in a tuple?
a) element in tuple
b) tuple.contains(element)
c) tuple.exists(element)
d) element.exists(tuple)
Question 7:
What does the tuple.count(element) method do?
a) Counts the total number of elements in the tuple
b) Counts the occurrences of a specific element in the tuple
c) Counts the sum of all elements in the tuple
d) Counts the average value of elements in the tuple
Question 8:
How do you concatenate two tuples in Python?
a) tuple1 + tuple2
b) tuple1.concat(tuple2)
c) concat(tuple1, tuple2)
d) combine(tuple1, tuple2)
Question 9:
How do you create a tuple with a single element?
a) single_tuple = (1)
b) single_tuple = 1,
c) single_tuple = (1,)
d) Both a and b
Question 10:
Which method is used to find the index of the first occurrence of a specified element in a tuple?
a) tuple.index(element)
b) tuple.find(element)
c) tuple.search(element)
d) tuple.loc(element)
Question 11:
What happens when you try to modify an element in a tuple?
a) It is not possible to modify elements in a tuple as they are immutable
b) The element is updated successfully
c) Python raises an exception
d) The element is deleted from the tuple
Question 12:
How do you create a tuple with elements from 1 to 5 in Python?
a) tuple = (1, 2, 3, 4, 5)
b) tuple = range(1, 6)
c) tuple = tuple(1, 6)
d) tuple = (range(1, 6))
Question 13:
What is the purpose of the len() function when used with a tuple?
a) It returns the total number of elements in the tuple
b) It returns the last element of the tuple
c) It returns the length of each element in the tuple
d) It returns the sum of all elements in the tuple
Question 14:
How do you check if two tuples are equal?
a) tuple1.is_equal(tuple2)
b) tuple1 == tuple2
c) tuple1.equals(tuple2)
d) tuple1.equals(tuple2, strict=True)
Question 15:
What is the purpose of the max() function when used with a tuple?
a) It returns the maximum element in the tuple
b) It returns the index of the maximum element in the tuple
c) It returns the sum of all elements in the tuple
d) It returns the average value of elements in the tuple
Question 16:
Which method is used to remove the last element from a tuple?
a) tuple.remove_last()
b) tuple.pop()
c) tuple.delete_last()
d) Tuples are immutable, so elements cannot be removed
Question 17:
How do you convert a list to a tuple in Python?
a) tuple(list)
b) tuple = list
c) tuple.from_list(list)
d) tuple.convert(list)
Question 18:
What is the purpose of the sorted() function when applied to a tuple?
a) Reverses the order of elements in the tuple
b) Sorts the elements of the tuple in ascending order
c) Removes duplicate elements from the tuple
d) Shuffles the elements of the tuple randomly
Question 19:
What does the tuple.index(element) method return if the element is not found in the tuple?
a) None
b) -1
c) 0
d) Raises a ValueError
Question 20:
What is the output of the following code?
my_tuple = (3, 1, 4, 1, 5, 9, 2)
my_tuple.sort()
print(my_tuple)
a) (1, 1, 2, 3, 4, 5, 9)
b) (9, 5, 4, 3, 2, 1, 1)
c) (1, 1, 2, 3, 4, 5, 9, 2)
d) (1, 2, 3, 4, 5, 9)
Answer:
- b) A collection of ordered elements
- d) Both b and c
- a) tuple[0]
- b) Tuples are immutable, so elements cannot be added once a tuple is created
- c) Tuples are immutable, while lists are mutable
- a) element in tuple
- b) Counts the occurrences of a specific element in the tuple
- a) tuple1 + tuple2
- c) single_tuple = (1,)
- a) tuple.index(element)
- a) It is not possible to modify elements in a tuple as they are immutable
- a) tuple = (1, 2, 3, 4, 5)
- a) It returns the total number of elements in the tuple
- b) tuple1 == tuple2
- a) It returns the maximum element in the tuple
- d) Tuples are immutable, so elements cannot be removed
- a) tuple(list)
- b) Sorts the elements of the tuple in ascending order
- d) Raises a ValueError
- d) (1, 2, 3, 4, 5, 9)
The Big Book of Small Python Projects: 81 Easy Practice Programs
Python Coding January 19, 2024 Books, Python No comments
Best-selling author Al Sweigart shows you how to easily build over 80 fun programs with minimal code and maximum creativity.
If you’ve mastered basic Python syntax and you’re ready to start writing programs, you’ll find The Big Book of Small Python Projects both enlightening and fun. This collection of 81 Python projects will have you making digital art, games, animations, counting pro- grams, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches.
These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online.
You’ll create:
• Hangman, Blackjack, and other games to play against your friends or the computer
• Simulations of a forest fire, a million dice rolls, and a Japanese abacus
• Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver
• A first-person 3D maze game
• Encryption programs that use ciphers like ROT13 and Vigenère to conceal text
If you’re tired of standard step-by-step tutorials, you’ll love the learn-by-doing approach of The Big Book of Small Python Projects. It’s proof that good things come in small programs!
Hard Copy : The Big Book of Small Python Projects: 81 Easy Practice Programs
Thursday 18 January 2024
Top 20 Python List Questions
Python Coding January 18, 2024 Python Coding Challenge No comments
Question 1:
What is a list in Python?
a) A collection of unordered elements
b) A collection of ordered elements
c) A single element
d) A data type
Question 2:
How do you create an empty list in Python?
a) list()
b) empty_list = []
c) empty_list = list()
d) Both b and c
Question 3:
How do you access the first element of a list?
a) list[0]
b) list.first()
c) list.first
d) list.get(0)
Question 4:
Which of the following statements is used to add an element to the end of a list?
a) list.insert(0, element)
b) list.add(element)
c) list.append(element)
d) list.extend(element)
Question 5:
What is the purpose of the len() function when used with a list?
a) It returns the total number of elements in the list
b) It returns the last element of the list
c) It returns the length of each element in the list
d) It returns the sum of all elements in the list
Question 6:
How do you check if an element is present in a list?
a) element in list
b) list.contains(element)
c) list.exists(element)
d) element.exists(list)
Question 7:
What does the list.remove(element) function do?
a) Removes the first occurrence of the specified element from the list
b) Removes all occurrences of the specified element from the list
c) Removes the last element from the list
d) Removes the element at the specified index
Question 8:
How do you reverse the order of elements in a list?
a) list.reverse()
b) list.sort(reverse=True)
c) list.reorder()
d) list.flip()
Question 9:
What is the difference between the append() and extend() methods in Python lists?
a) There is no difference, and the terms are interchangeable
b) append() adds a single element, while extend() adds multiple elements
c) extend() adds a single element, while append() adds multiple elements
d) Both methods are used for removing elements from a list
Question 10:
What is the output of the following code?
my_list = [1, 2, 3]
new_list = my_list * 2
print(new_list)
a) [1, 2, 3, 1, 2, 3]
b) [2, 4, 6]
c) [1, 4, 9]
d) [1, 2, 3, 6, 9]
Question 11:
Which method is used to find the index of the first occurrence of a specified element in a list?
a) list.index(element)
b) list.find(element)
c) list.search(element)
d) list.loc(element)
Question 12:
How do you copy the elements of one list to another list in Python?
a) new_list = old_list.copy()
b) new_list = old_list.clone()
c) new_list = copy(old_list)
d) new_list = old_list[:]
Question 13:
What is the purpose of the pop() method in Python lists?
a) Adds an element to the end of the list
b) Removes the last element from the list and returns it
c) Removes the first occurrence of the specified element
d) Sorts the elements of the list
Question 14:
What is the difference between a list and a tuple in Python?
a) Lists are mutable, while tuples are immutable
b) Lists are immutable, while tuples are mutable
c) Both lists and tuples are mutable
d) Both lists and tuples are immutable
Question 15:
How do you insert an element at a specific index in a list?
a) list.add(index, element)
b) list.insert(index, element)
c) list.insert(element, index)
d) list.put(index, element)
Question 16:
Which method is used to clear all elements from a list?
a) list.clear()
b) list.remove_all()
c) list.delete()
d) list.empty()
Question 17:
What does the sorted() function do when applied to a list?
a) Reverses the order of elements in the list
b) Sorts the elements of the list in ascending order
c) Removes duplicate elements from the list
d) Shuffles the elements of the list randomly
Question 18:
What is the purpose of the count() method in Python lists?
a) Counts the total number of elements in the list
b) Counts the occurrences of a specific element in the list
c) Counts the sum of all elements in the list
d) Counts the average value of elements in the list
Question 19:
How do you create a list of numbers from 1 to 5 in Python?
a) list = [1, 2, 3, 4, 5]
b) list = range(1, 6)
c) list = list(1, 6)
d) list = [range(1, 6)]
Question 20:
What is the output of the following code?
my_list = [3, 1, 4, 1, 5, 9, 2]
my_list.sort()
print(my_list)
a) [1, 1, 2, 3, 4, 5, 9]
b) [9, 5, 4, 3, 2, 1, 1]
c) [1, 1, 2, 3, 4, 5, 9, 2]
d) [1, 2, 3, 4, 5, 9]
Answer :
Question 1: b) A collection of ordered elements
Question 2: d) Both b and c
Question 3: a) list[0]
Question 4: c) list.append(element)
Question 5: a) It returns the total number of elements in the list
Question 6: a) element in list
Question 7: a) Removes the first occurrence of the specified element from the list
Question 8: a) list.reverse()
Question 9: b) append() adds a single element, while extend() adds multiple elements
Question 10: a) [1, 2, 3, 1, 2, 3]
Question 11: a) list.index(element)
Question 12: d) new_list = old_list[:]
Question 13: b) Removes the last element from the list and returns it
Question 14: a) Lists are mutable, while tuples are immutable
Question 15: b) list.insert(index, element)
Question 16: a) list.clear()
Question 17: b) Sorts the elements of the list in ascending order
Question 18: b) Counts the occurrences of a specific element in the list
Question 19: b) list = range(1, 6)
Question 20: a) [1, 1, 2, 3, 4, 5, 9]
Python Coding challenge - Day 116 | What is the output of the following Python Code?
Python Coding January 18, 2024 Python Coding Challenge No comments
Code:
my_list = [1, 2]
new_list = my_list * 2
print(new_list)
Solution and Explanation:
The above code creates a new list new_list by repeating the elements of my_list twice using the * operator. Here's the output of the code:
my_list = [1, 2]
new_list = my_list * 2
print(new_list)
Output:
[1, 2, 1, 2]
As you can see, the elements [1, 2] from my_list are repeated, resulting in a new list [1, 2, 1, 2]. The * operator in this context duplicates the elements of the list the specified number of times.
Wednesday 17 January 2024
How much do you know about Pandas library?
Python Coding January 17, 2024 Python Coding Challenge No comments
Question 1:
What is Pandas?
a) A species of bear
b) A data manipulation and analysis library in Python
c) A programming language
d) A web development framework
Question 2:
Which of the following data structures is used to store one-dimensional labeled data in Pandas?
a) Series
b) DataFrame
c) Array
d) List
Question 3:
How can you import the Pandas library in Python?
a) import panda
b) import pandas as pd
c) from pandas import *
d) import pd
Question 4:
What is the primary purpose of a Pandas DataFrame?
a) Storing only numerical data
b) Storing two-dimensional labeled data
c) Storing images and multimedia files
d) Storing text data
Question 5:
Which Pandas function is used to read a CSV file into a DataFrame?
a) read_csv()
b) load_csv()
c) import_csv()
d) read_file()
Question 6:
How can you access a specific column in a Pandas DataFrame?
a) By using the column's index
b) By using the column's label or name
c) By using the row number
d) By using the DataFrame's index
Question 7:
What does the head() function do in Pandas?
a) Prints the first few rows of a DataFrame
b) Prints the last few rows of a DataFrame
c) Prints a summary statistics of the DataFrame
d) Prints the shape of the DataFrame
Question 8:
Which Pandas method is used to check for missing values in a DataFrame?
a) find_missing()
b) check_missing()
c) missing_values()
d) isnull()
Question 9:
What is the purpose of the iloc method in Pandas?
a) Selects columns based on their labels
b) Selects rows and columns based on their integer positions
c) Performs element-wise operations on a DataFrame
d) Checks for duplicate values in a DataFrame
Question 10:
How can you drop a column named "Column_A" from a Pandas DataFrame called df?
a) df.remove("Column_A")
b) df.drop("Column_A", axis=1)
c) df.delete("Column_A")
d) df.remove_column("Column_A")
Question 11:
Which Pandas function is used to filter rows based on a condition?
a) filter_rows()
b) select_rows()
c) filter()
d) query()
Question 12:
In Pandas, what is the purpose of the groupby() function?
a) Groups data based on unique values in a column
b) Reverses the order of rows in a DataFrame
c) Computes the mean of each column
d) Reshapes a DataFrame into a pivot table
Question 13:
How can you rename a specific column in a Pandas DataFrame?
a) rename_column()
b) change_column_name()
c) df.rename()
d) df.change_name()
Question 14:
What does the merge() function in Pandas do?
a) Merges two DataFrames based on a specified column or index
b) Adds a new column to a DataFrame
c) Sorts the rows of a DataFrame
d) Reshapes a DataFrame into a long format
Question 15:
Which Pandas function is used to pivot a DataFrame?
a) pivot()
b) reshape()
c) pivot_table()
d) transpose()
Question 16:
What is the purpose of the to_csv() function in Pandas?
a) Converts a DataFrame to a CSV file
b) Converts a CSV file to a DataFrame
c) Checks if a CSV file is valid
d) Counts the number of occurrences of each value in a DataFrame
Question 17:
Which method is used to fill missing values in a Pandas DataFrame with a specific value?
a) fillna()
b) fill_missing()
c) replace()
d) impute()
Question 18:
How can you sort a Pandas DataFrame based on a specific column?
a) df.sort_by("column_name")
b) df.sort("column_name")
c) df.sort_values("column_name")
d) df.order_by("column_name")
Question 19:
What is the purpose of the pivot_table() function in Pandas?
a) Pivots a DataFrame from long to wide format
b) Computes the sum of each column in a DataFrame
c) Transposes a DataFrame
d) Aggregates data based on one or more columns
Question 20:
Which Pandas function is used to calculate summary statistics of a DataFrame?
a) describe()
b) summary()
c) stats()
d) analyze()
Answer :
How much do you know about NumPy library?
Python Coding January 17, 2024 Python Coding Challenge No comments
What is NumPy?
a) A programming language
b) A machine learning library
c) A numerical computing library in Python
d) A deep learning framework
Question 2:
Which of the following is the primary purpose of NumPy?
a) Web development
b) Data manipulation and analysis
c) Game development
d) Network programming
Question 3:
What does the term "NumPy" stand for?
a) Numerical Python
b) Nonlinear Python
c) Neural Python
d) Numeral Python
Question 4:
Which of the following is the correct way to import NumPy in Python?
a) import np
b) import numpy as np
c) from numpy import *
d) include numpy
Question 5:
What is the core data structure in NumPy for representing arrays?
a) Lists
b) Tuples
c) Arrays
d) Sets
Question 6:
Which NumPy function is used to create an array with a range of values?
a) numpy.linspace()
b) numpy.range()
c) numpy.aranges()
d) numpy.arange()
Question 7:
What is the result of the following NumPy expression: numpy.zeros(5)?
a) An array with five elements, all set to 1
b) An array with five elements, all set to 0
c) An empty array
d) An array with five elements, all set to 5
Question 8:
Which NumPy function is used to find the mean of an array?
a) numpy.mean()
b) numpy.average()
c) numpy.median()
d) numpy.mean_value()
Question 9:
In NumPy, what does the function numpy.random.rand() do?
a) Generates random integers
b) Generates random floats in the half-open interval [0.0, 1.0)
c) Computes the standard deviation of an array
d) Creates an array with a specified shape and all elements initialized to the same value
Question 10:
What does the term "broadcasting" mean in the context of NumPy?
a) Sending data over a network
b) Extending the dimensions of an array
c) Performing element-wise operations on arrays of different shapes and sizes
d) Converting data types in an array
Question 11:
Which NumPy function is used to perform element-wise multiplication of two arrays?
a) numpy.multiply()
b) numpy.dot()
c) numpy.cross()
d) numpy.product()
Question 12:
How can you reshape a NumPy array with dimensions (4, 5) into a new array with dimensions (2, 10)?
a) array.reshape((2, 10))
b) numpy.resize(array, (2, 10))
c) numpy.reshape(array, (2, 10))
d) array.resize((2, 10))
Question 13:
What is the purpose of the NumPy function numpy.linalg.inv()?
a) Computes the determinant of a matrix
b) Finds the eigenvalues of a matrix
c) Computes the inverse of a matrix
d) Calculates the singular value decomposition of a matrix
Question 14:
Which NumPy function is used to concatenate two or more arrays along a specified axis?
a) numpy.append()
b) numpy.concatenate()
c) numpy.concat()
d) numpy.merge()
Question 15:
How can you find the index of the maximum value in a NumPy array?
a) numpy.max_index()
b) numpy.argmax()
c) numpy.index_max()
d) numpy.maximum_index()
Question 16:
What is the purpose of the NumPy function numpy.fft.fft()?
a) Finds the fast file transfer of an array
b) Computes the fast Fourier transform of an array
c) Calculates the flip-flop transform of an array
d) Performs the fuzzy frequency transformation of an array
Question 17:
Which NumPy function is used to calculate the dot product of two arrays?
a) numpy.dot()
b) numpy.multiply()
c) numpy.cross()
d) numpy.product()
Question 18:
In NumPy, what does the function numpy.where() do?
a) Filters elements of an array based on a condition
b) Finds the index of a specified element in an array
c) Transposes the elements of an array
d) Sorts the elements of an array
Question 19:
What is the purpose of the NumPy function numpy.save()?
a) Saves an array to a text file
b) Saves an array to a binary file in NumPy's .npy format
c) Saves an array to a CSV file
d) Saves an array to an Excel file
Question 20:
How can you find the unique elements in a NumPy array?
a) numpy.unique()
b) numpy.distinct()
c) numpy.uniq()
d) numpy.elements()
Question 1: c) A numerical computing library in Python
Question 2: b) Data manipulation and analysis
Question 3: a) Numerical Python
Question 4: b) import numpy as np
Question 5: c) Arrays
Question 6: d) numpy.arange()
Question 7: b) An array with five elements, all set to 0
Question 8: a) numpy.mean()
Question 9: b) Generates random floats in the half-open interval [0.0, 1.0)
Question 10: c) Performing element-wise operations on arrays of different shapes and sizes
Question 11: a) numpy.multiply()
Question 12: a) array.reshape((2, 10))
Question 13: c) Computes the inverse of a matrix
Question 14: b) numpy.concatenate()
Question 15: b) numpy.argmax()
Question 16: b) Computes the fast Fourier transform of an array
Question 17: a) numpy.dot()
Question 18: a) Filters elements of an array based on a condition
Question 19: b) Saves an array to a binary file in NumPy's .npy format
Question 20: a) numpy.unique()
Managing Machine Learning Projects
Python Coding January 17, 2024 Coursera, Machine Learning No comments
Build your subject-matter expertise
This course is part of the AI Product Management Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate
Join Free: Managing Machine Learning Projects
There are 5 modules in this course
Python, Bash and SQL Essentials for Data Engineering Specialization
Python Coding January 17, 2024 Python, SQL No comments
What you'll learn
Develop data engineering solutions with a minimal and essential subset of the Python language and the Linux environment
Design scripts to connect and query a SQL database using Python
Use a scraping library in Python to read, identify and extract data from websites
Join Free: Python, Bash and SQL Essentials for Data Engineering Specialization
Specialization - 4 course series
Spark, Hadoop, and Snowflake for Data Engineering
Python Coding January 17, 2024 Coursera, Hadoop No comments
What you'll learn
Create scalable data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data handling.
Optimize data engineering with clustering and scaling to boost performance and resource use.
Build ML solutions (PySpark, MLFlow) on Databricks for seamless model development and deployment.
Implement DataOps and DevOps practices for continuous integration and deployment (CI/CD) of data-driven applications, including automating processes.
Join Free: Spark, Hadoop, and Snowflake for Data Engineering
There are 4 modules in this course
MLOps | Machine Learning Operations Specialization
Python Coding January 17, 2024 Coursera, Machine Learning No comments
What you'll learn
Master Python fundamentals, MLOps principles, and data management to build and deploy ML models in production environments.
Utilize Amazon Sagemaker / AWS, Azure, MLflow, and Hugging Face for end-to-end ML solutions, pipeline creation, and API development.
Fine-tune and deploy Large Language Models (LLMs) and containerized models using the ONNX format with Hugging Face.
Design a full MLOps pipeline with MLflow, managing projects, models, and tracking system features.
Join Free: MLOps | Machine Learning Operations Specialization
Specialization - 4 course series
Through this series, you will begin to learn skills for various career paths:
Applied Learning Project
Machine Learning Foundations for Product Managers
Python Coding January 17, 2024 Coursera, Machine Learning No comments
Build your subject-matter expertise
This course is part of the AI Product Management Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate
Join Free: Machine Learning Foundations for Product Managers
There are 6 modules in this course
Tuesday 16 January 2024
DevOps on AWS: Code, Build, and Test
Python Coding January 16, 2024 aws No comments
What you'll learn
Understand the DevOps philosophies and its lifecycle
Implement and manage continuous delivery systems and methodologies on AWS
How to use the right tools to measure code quality by identifying workflow steps
Join Free: DevOps on AWS: Code, Build, and Test
There are 2 modules in this course
Hands-on Machine Learning with AWS and NVIDIA
Python Coding January 16, 2024 aws, Machine Learning No comments
There are 4 modules in this course
Machine learning (ML) projects can be complex, tedious, and time consuming. AWS and NVIDIA solve this challenge with fast, effective, and easy-to-use capabilities for your ML project.
Join Free: Hands-on Machine Learning with AWS and NVIDIA
This course is designed for ML practitioners, including data scientists and developers, who have a working knowledge of machine learning workflows. In this course, you will gain hands-on experience on building, training, and deploying scalable machine learning models with Amazon SageMaker and Amazon EC2 instances powered by NVIDIA GPUs. Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality ML models quickly by bringing together a broad set of capabilities purpose-built for ML. Amazon EC2 instances powered by NVIDIA GPUs along with NVIDIA software offer high performance GPU-optimized instances in the cloud for efficient model training and cost effective model inference hosting.
In this course, you will first get an overview of Amazon SageMaker and NVIDIA GPUs. Then, you will get hands-on, by running a GPU powered Amazon SageMaker notebook instance. You will then learn how to prepare a dataset for model training, build a model, execute model training, and deploy and optimize the ML model. You will also learn, hands-on, how to apply this workflow for computer vision (CV) and natural language processing (NLP) use cases. After completing this course, you will be able to build, train, deploy, and optimize ML workflows with GPU acceleration in Amazon SageMaker and understand the key Amazon SageMaker services applicable to computer vision and NLP ML tasks.
Introduction to Designing Data Lakes on AWS
Python Coding January 16, 2024 aws No comments
What you'll learn
Where to start with a Data Lake?
How to build a secure and scalable Data Lake?
What are the common components of a Data Lake?
Why do you need a Data Lake and what it's value?
Join Free: Introduction to Designing Data Lakes on AWS
There are 4 modules in this course
Getting Started with Data Analytics on AWS
Python Coding January 16, 2024 aws, Data Science No comments
What you'll learn
Explain different types of data analyses – descriptive, diagnostic, predictive, prescriptive
Understand how to perform descriptive data analytics in the cloud with typical data sets
How to build simple visualizations in AWS QuickSight to do descriptive analytics (using S3, Cloudtrail, Athena)
Join Free: Getting Started with Data Analytics on AWS
There is 1 module in this course
DevOps on AWS Specialization
Python Coding January 16, 2024 aws, Coursera No comments
What you'll learn
Implement DevOps culture and practices in the AWS Cloud
Adopt and enforce Continuous Integration and Continuous
Delivery best practices on AWS
Explore deployment strategies for serverless applications
Join Free: DevOps on AWS Specialization
Specialization - 4 course series
Applied Learning Project
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