Thursday 16 May 2024
Python Coding challenge - Day 206 | What is the output of the following Python Code?
Python Coding May 16, 2024 Python Coding Challenge No comments
Code:
dict_a = {"a": 1, "b": 2}
dict_b = {"a": 1, "b": 2}
print(dict_a is dict_b)
print(dict_a == dict_b)
Solution and Explanation:
This code creates two dictionaries, dict_a and dict_b, with identical key-value pairs. Then it prints the results of two different comparisons:
print(dict_a is dict_b): This checks whether dict_a and dict_b refer to the same object in memory. In this case, they are two separate dictionary objects, so the output will be False.
print(dict_a == dict_b): This checks whether the contents of dict_a and dict_b are the same. Since they have the same key-value pairs, the output will be True.
Tuesday 14 May 2024
Python Coding challenge - Day 205 | What is the output of the following Python Code?
Python Coding May 14, 2024 Python Coding Challenge No comments
Code:
num = [5, 6]
*midd, lst = num, num[-1]
print(midd, lst)
Solution and Explanation:
Let's break down the code step by step:
num = [5, 6]: This line creates a list called num containing two integers, 5 and 6.
*midd, lst = num, num[-1]: Here, we're using extended iterable unpacking. Let's dissect this line:
*midd: The * operator is used to gather any remaining items in the iterable (in this case, the list num) into a list. So, midd will contain all elements of num except the last one.
, lst: This part assigns the last item of the num list to the variable lst. In this case, it's assigning 6 to lst.
Therefore, after this line executes, midd will be [5] and lst will be 6.
print(midd, lst): This line prints the variables midd and lst. So, it will output [5] 6.
So, overall, the code snippet initializes a list num with two elements [5, 6], then it unpacks this list into two variables: midd, which contains all elements of num except the last one ([5]), and lst, which contains the last element of num (6). Finally, it prints the values of midd and lst.
Monday 13 May 2024
Python Coding challenge - Day 204 | What is the output of the following Python Code?
Python Coding May 13, 2024 Python Coding Challenge No comments
Code:
num = [7, 8, 9]
*mid, last = num[:-1]
print(mid, last)
Solution and Explanation:
Python Libraries for Financial Analysis and Portfolio Management
Python Coding May 13, 2024 Finance, Python No comments
Sunday 12 May 2024
Python Coding challenge - Day 203 | What is the output of the following Python Code?
Python Coding May 12, 2024 Python Coding Challenge No comments
Code:
num = [1, 2, 3]
*middle, last = num
print(middle, last)
Solution and Explanation:
Saturday 11 May 2024
Happy Mother's Day!
Python Coding May 11, 2024 Python No comments
Code:
import pyfiglet
from termcolor import colored
import random
def get_random_font_style():
# List of available Figlet font styles
font_styles = pyfiglet.FigletFont.getFonts()
# Choose a random font style from the list
return random.choice(font_styles)
def get_random_color():
# List of available colors
colors = ['red', 'green', 'yellow', 'blue', 'magenta', 'cyan', 'white']
# Choose a random color from the list
return random.choice(colors)
def wish_mothers_day():
# Get a random font style and color
random_font_style = get_random_font_style()
random_color = get_random_color()
# Create a Figlet font object with the random style
font = pyfiglet.Figlet(font=random_font_style)
# Print the decorative greeting in the chosen color
print(colored(font.renderText("Happy Mother's Day!"), random_color))
wish_mothers_day()
#clcoding.com
Solution and Explanation:
Type Hints in Python
Python Coding May 11, 2024 Python No comments
Type hints in Python are an excellent tool for improving code quality and maintainability, especially in larger projects.
from typing import Optional
class TreeNode:
def __init__(self, value: int) -> None:
self.value = value
self.left: Optional['TreeNode'] = None
self.right: Optional['TreeNode'] = None
#clcoding.com
class LinkedListNode:
def __init__(self, value: int, next_node: 'LinkedListNode' = None) -> None:
self.value = value
self.next = next_node
#clcoding.com
from typing import Optional
class TreeNode:
def __init__(self, value: int) -> None:
self.value = value
self.left: Optional['TreeNode'] = None
self.right: Optional['TreeNode'] = None
#clcoding.com
from typing import TypeVar
class Animal:
def speak(self) -> str:
raise NotImplementedError
class Dog(Animal):
def speak(self) -> str:
return "Woof!"
T = TypeVar('T', bound=Animal)
def make_sound(animal: T) -> str:
return animal.speak()
#clcoding.com
from typing import Callable
def apply_func(func: Callable[[int, int], int], a: int, b: int) -> int:
return func(a, b)
#clcoding.com
from typing import Iterable, TypeVar
T = TypeVar('T')
def process_items(items: Iterable[T]) -> None:
for item in items:
# Process each item
pass
#clcoding.com
from typing import TypeVar, Iterable
T = TypeVar('T')
def first_element(items: Iterable[T]) -> T:
return next(iter(items))
#clcoding.com
from typing import List, Tuple
Point = Tuple[int, int]
Polygon = List[Point]
def area(polygon: Polygon) -> float:
# Calculate area of polygon
pass
#clcoding.com
Automating File Compression with gzip
Python Coding May 11, 2024 Python No comments
Code:
import gzip
import shutil
def compress_file(input_file, output_file):
with open(input_file, 'rb') as f_in:
with gzip.open(output_file, 'wb') as f_out:
shutil.copyfileobj(f_in, f_out)
# Example usage
input_filename = 'clcoding.txt'
output_filename = 'clcoding.txt.gz'
compress_file(input_filename, output_filename)
#clcoding.com
Explanation:
Python Coding challenge - Day 202 | What is the output of the following Python Code?
Python Coding May 11, 2024 Python Coding Challenge No comments
Code:
Solution and Explanation:
Sunday 5 May 2024
Donut Charts using Python
Python Coding May 05, 2024 Data Science, Python No comments
Code:
Explanation:
Code:
Explanation:
Code:
Explanation:
Saturday 4 May 2024
Python Coding challenge - Day 201 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
class Powerizer(int):
def __pow__(self, other):
return super().__pow__(other ** 2)
p = Powerizer(2)
result = p ** 3
print(result)
Solution and Explanation:
Python Coding challenge - Day 200 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
class Decrementer(int):
def __sub__(self, other):
return super().__sub__(other - 1)
d = Decrementer(5)
result = d - 3
print(result)
Solution and Explanation:
Class Definition:
class Decrementer(int):
def __sub__(self, other):
return super().__sub__(other - 1)
Decrementer(int): This line creates a class called Decrementer which inherits from the int class. Instances of Decrementer will inherit all the properties and methods of integers.
def __sub__(self, other): This method overrides the subtraction behavior (__sub__) for instances of the Decrementer class. It is called when the - operator is used with instances of Decrementer.
return super().__sub__(other - 1): Inside the __sub__ method, it subtracts 1 from the other operand and then calls the __sub__ method of the superclass (which is int). It passes the modified other operand to the superclass method. Essentially, it performs subtraction of the Decrementer instance with the modified value of other.
Object Instantiation:
d = Decrementer(5)
This line creates an instance of the Decrementer class with the value 5.
Subtraction Operation:
result = d - 3
This line performs a subtraction operation using the - operator. Since d is an instance of Decrementer, the overridden __sub__ method is invoked. The value 3 is passed as other. Inside the overridden __sub__ method, 1 is subtracted from other, making it 2. Then, the superclass method (int.__sub__) is called with the modified other value. Essentially, it subtracts 2 from d, resulting in the final value.
print(result)
This line prints the value of result, which is the result of the subtraction operation performed in the previous step.
So, the output of this code will be 3, which is the result of subtracting 3 - 1 from 5.
Python Coding challenge - Day 199 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
class Incrementer(int):
def __add__(self, other):
return super().__add__(other + 1)
i = Incrementer(5)
result = i + 3
print(result)
Solution and Explanation:
Python Coding challenge - Day 198 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
Solution and Explanation:
Python Coding challenge - Day 197 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
Solution and Explanation:
Python Coding challenge - Day 196 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
class Doubler(int):
def __mul__(self, other):
return super().__mul__(other + 3)
d = Doubler(3)
result = d * 5
print(result)
Solution and Explanation:
Python Coding challenge - Day 195 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
Solution and Explanation:
Python Coding challenge - Day 194 | What is the output of the following Python Code?
Python Coding May 04, 2024 Python Coding Challenge No comments
Code:
Solution and Explanation:
Data Science: The Hard Parts: Techniques for Excelling at Data Science
Python Coding May 04, 2024 Books, Data Science No comments
This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.
Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.
With this book, you will:
Understand how data science creates value
Deliver compelling narratives to sell your data science project
Build a business case using unit economics principles
Create new features for a ML model using storytelling
Learn how to decompose KPIs
Perform growth decompositions to find root causes for changes in a metric
Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).
PDF: Data Science: The Hard Parts: Techniques for Excelling at Data Science
Hard Copy: Data Science: The Hard Parts: Techniques for Excelling at Data Science
Streamgraphs using Python
Python Coding May 04, 2024 Data Science No comments
Code:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)
plt.stackplot(x, y1, y2, baseline='wiggle')
plt.title('Streamgraph')
plt.show()
Explanation:
Statistical Inference and Probability
Python Coding May 04, 2024 Books, Data Science No comments
An experienced author in the field of data analytics and statistics, John Macinnes has produced a straight-forward text that breaks down the complex topic of inferential statistics with accessible language and detailed examples. It covers a range of topics, including:
· Probability and Sampling distributions
· Inference and regression
· Power, effect size and inverse probability
Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
Hard Copy: Statistical Inference and Probability
PDF: Statistical Inference and Probability (The SAGE Quantitative Research Kit)
Friday 3 May 2024
Python Coding challenge - Day 193 | What is the output of the following Python Code?
Python Coding May 03, 2024 Python Coding Challenge No comments
Code:
class Doubler(int):
def __mul__(self, other):
return super().__mul__(other * 2)
# Create an instance of Doubler
d = Doubler(3)
# Multiply by another number
result = d * 5
print(result)
Solution and Explanation:
Thursday 2 May 2024
Python Coding challenge - Day 192 | What is the output of the following Python Code?
Python Coding May 02, 2024 Python Coding Challenge No comments
Code:
class MyClass:
def __init__(self, x):
self.x = x
def __call__(self, y):
return self.x * y
p1 = MyClass(2)
print(p1(3))
Solution and Explanation:
Wednesday 1 May 2024
Python Coding challenge - Day 191 | What is the output of the following Python Code?
Python Coding May 01, 2024 Python Coding Challenge No comments
Code:
class MyClass:
def __init__(self, x):
self.x = x
p1 = MyClass(1)
p2 = MyClass(2)
p1.x = p2.x
del p2.x
print(p1.x)
Solution with Explanation:
Popular Posts
-
This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of Cali...
-
1. Basic Math Operations Pipeline def add(x, y): return x + y def multiply(x, y): return x * y def subtract(x, y): return x - y ...
-
1. Basic Tuple Unpacking person = ("John", 28, "Engineer") name, age, profession = person print(f"Name: {name}&qu...
-
Build your subject-matter expertise This course is part of the Mathematics for Machine Learning Specialization When you enroll in this cou...
-
Code: a = [1, 2, 3] b = a[:] a.append(4) print(b) Solution and Explanation: Step 1: a = [1, 2, 3] This creates a list a containing the el...
-
1. Use List Comprehensions for Cleaner Code List comprehensions are a compact way to generate lists from existing lists or other iterable ...
-
What you'll learn Create basic visualizations such as line graphs, bar graphs, and pie charts using Excel spreadsheets. Explain the im...
-
What you'll learn Describe what data science and machine learning are, their applications & use cases, and various types of tasks ...
-
There are 5 modules in this course Data science courses contain math—no avoiding that! This course is designed to teach learners the basic...
-
What you'll learn Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and...