Python Question / Quiz;
What is the output of the following Python code, and why? π€π Comment your answers below! π
What is the output of the following Python code, and why? π€π Comment your answers below! π
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming
https://t.iss.one/DataScienceQ
π2
π§ What is a Generator in Python?
A generator is a special type of iterator that produces values lazilyβone at a time, and only when neededβwithout storing them all in memory.
---
β How do you create a generator?
β Correct answer:
Option 1: Use the
π₯ Simple example:
When you call this function:
Each time you call
---
β Why are the other options incorrect?
- Option 2 (class with
It works, but itβs more complex. Using
- Options 3 & 4 (
Loops are not generators themselves. They just iterate over iterables.
---
π‘ Pro Tip:
Generators are perfect when working with large or infinite datasets. Theyβre memory-efficient, fast, and clean to write.
---
π #Python #Generator #yield #AdvancedPython #PythonTips #Coding
πBy: https://t.iss.one/DataScienceQ
A generator is a special type of iterator that produces values lazilyβone at a time, and only when neededβwithout storing them all in memory.
---
β How do you create a generator?
β Correct answer:
Option 1: Use the
yield keyword inside a function.π₯ Simple example:
def countdown(n):
while n > 0:
yield n
n -= 1
When you call this function:
gen = countdown(3)
print(next(gen)) # 3
print(next(gen)) # 2
print(next(gen)) # 1
Each time you call
next(), the function resumes from where it left off, runs until it hits yield, returns a value, and pauses again.---
β Why are the other options incorrect?
- Option 2 (class with
__iter__ and __next__): It works, but itβs more complex. Using
yield is simpler and more Pythonic.- Options 3 & 4 (
for or while loops): Loops are not generators themselves. They just iterate over iterables.
---
π‘ Pro Tip:
Generators are perfect when working with large or infinite datasets. Theyβre memory-efficient, fast, and clean to write.
---
π #Python #Generator #yield #AdvancedPython #PythonTips #Coding
πBy: https://t.iss.one/DataScienceQ
π6β€2π₯2β€βπ₯1
Question 1 (Intermediate):
In Python, which of these is the correct way to create a virtual environment?
A)
B)
C)
D)
#Python #Development #VirtualEnv #Coding
In Python, which of these is the correct way to create a virtual environment?
A)
python create venv B)
python -m venv myenv C)
pip install virtualenv D)
conda make env #Python #Development #VirtualEnv #Coding
β€2
Forwarded from Data Science Jupyter Notebooks
π₯ Trending Repository: tech-interview-handbook
π Description: π― Curated coding interview preparation materials for busy software engineers
π Repository URL: https://github.com/yangshun/tech-interview-handbook
π Website: https://www.techinterviewhandbook.org
π Readme: https://github.com/yangshun/tech-interview-handbook#readme
π Statistics:
π Stars: 130K stars
π Watchers: 2.2k
π΄ Forks: 15.8K forks
π» Programming Languages: TypeScript - JavaScript - Python
π·οΈ Related Topics:
==================================
π§ By: https://t.iss.one/DataScienceM
π Description: π― Curated coding interview preparation materials for busy software engineers
π Repository URL: https://github.com/yangshun/tech-interview-handbook
π Website: https://www.techinterviewhandbook.org
π Readme: https://github.com/yangshun/tech-interview-handbook#readme
π Statistics:
π Stars: 130K stars
π Watchers: 2.2k
π΄ Forks: 15.8K forks
π» Programming Languages: TypeScript - JavaScript - Python
π·οΈ Related Topics:
#algorithm #algorithms #interview_practice #interview_questions #coding_interviews #interview_preparation #system_design #algorithm_interview #behavioral_interviews #algorithm_interview_questions
==================================
π§ By: https://t.iss.one/DataScienceM
β€1
Here are links to the most important free Python courses with a brief description of their value.
1. Coursera: Python for Everybody
Link: https://www.coursera.org/specializations/python
Importance: A perfect starting point for absolute beginners. Covers Python fundamentals and basic data structures, leading to web scraping and database access.
2. freeCodeCamp: Scientific Computing with Python
Link: https://www.freecodecamp.org/learn/scientific-computing-with-python/
Importance: Project-based certification. You build applications like a budget app or a time calculator, reinforcing learning through practical, portfolio-worthy projects.
3. Harvard's CS50P: CS50's Introduction to Programming with Python
Link: https://cs50.harvard.edu/python/2022/
Importance: A rigorous university-level course. Teaches core concepts and problem-solving skills with exceptional depth and clarity, preparing you for complex programming challenges.
4. Real Python Tutorials
Link: https://realpython.com/
Importance: An extensive resource for all levels. Offers in-depth articles, tutorials, and code examples on nearly every Python topic, from basics to advanced specialized libraries.
5. W3Schools Python Tutorial
Link: https://www.w3schools.com/python/
Importance: Excellent for quick reference and interactive learning. Allows you to read a concept and test code directly in the browser, ideal for fast learning and checking syntax.
6. Google's Python Class
Link: https://developers.google.com/edu/python
Importance: A concise, fast-paced course for those with some programming experience. Includes lecture videos and well-designed exercises to quickly get up to speed.
#Python #LearnPython #PythonProgramming #Coding #FreeCourses #PythonForBeginners #Developer #Programming
By: t.iss.one/DataScienceQ π
Coursera
Python for Everybody
Offered by University of Michigan. Learn to Program and ... Enroll for free.
β€2π1
1. What is the primary data structure in pandas?
2. How do you create a DataFrame from a dictionary?
3. Which method is used to read a CSV file in pandas?
4. What does the
5. How can you check the data types of columns in a DataFrame?
6. Which function drops rows with missing values in pandas?
7. What is the purpose of the
8. How do you filter rows based on a condition in pandas?
9. What does the
10. How can you sort a DataFrame by a specific column?
11. Which method is used to rename columns in pandas?
12. What is the difference between
13. How do you handle duplicate rows in pandas?
14. What function converts a column to datetime format?
15. How do you apply a custom function to a DataFrame?
16. What is the use of the
17. How can you concatenate two DataFrames?
18. What does the
19. How do you calculate summary statistics in pandas?
20. Which method is used to export a DataFrame to a CSV file?
#οΈβ£ #pandas #dataanalysis #python #dataframe #coding #programming #datascience
By: t.iss.one/DataScienceQ π
2. How do you create a DataFrame from a dictionary?
3. Which method is used to read a CSV file in pandas?
4. What does the
head() function do in pandas? 5. How can you check the data types of columns in a DataFrame?
6. Which function drops rows with missing values in pandas?
7. What is the purpose of the
merge() function in pandas? 8. How do you filter rows based on a condition in pandas?
9. What does the
groupby() method do? 10. How can you sort a DataFrame by a specific column?
11. Which method is used to rename columns in pandas?
12. What is the difference between
loc and iloc in pandas? 13. How do you handle duplicate rows in pandas?
14. What function converts a column to datetime format?
15. How do you apply a custom function to a DataFrame?
16. What is the use of the
apply() method in pandas? 17. How can you concatenate two DataFrames?
18. What does the
pivot_table() function do? 19. How do you calculate summary statistics in pandas?
20. Which method is used to export a DataFrame to a CSV file?
#οΈβ£ #pandas #dataanalysis #python #dataframe #coding #programming #datascience
By: t.iss.one/DataScienceQ π
Telegram
Python Data Science Jobs & Interviews
Your go-to hub for Python and Data Scienceβfeaturing questions, answers, quizzes, and interview tips to sharpen your skills and boost your career in the data-driven world.
Admin: @Hussein_Sheikho
Admin: @Hussein_Sheikho
1. What is the primary purpose of PHP?
2. How do you declare a variable in PHP?
3. Which symbol starts a PHP code block?
4. What is the difference between
5. How do you create an array in PHP?
6. Which function is used to get the length of a string in PHP?
7. What is the use of the
8. How do you handle form data in PHP?
9. What does the
10. How can you include another PHP file in your script?
11. What is the purpose of the
12. How do you define a function in PHP?
13. What is the difference between
14. How do you connect to a MySQL database using PHP?
15. Which function executes a SQL query in PHP?
16. What is the use of the
17. How do you start a session in PHP?
18. What is the purpose of the
19. How do you redirect a user to another page in PHP?
20. What is the use of the
#οΈβ£ #php #webdevelopment #coding #programming #backend #scripting #serverside #dev
By: t.iss.one/DataScienceQπ
2. How do you declare a variable in PHP?
3. Which symbol starts a PHP code block?
4. What is the difference between
echo and print in PHP? 5. How do you create an array in PHP?
6. Which function is used to get the length of a string in PHP?
7. What is the use of the
isset() function in PHP? 8. How do you handle form data in PHP?
9. What does the
$_GET superglobal contain? 10. How can you include another PHP file in your script?
11. What is the purpose of the
require_once statement? 12. How do you define a function in PHP?
13. What is the difference between
== and === in PHP? 14. How do you connect to a MySQL database using PHP?
15. Which function executes a SQL query in PHP?
16. What is the use of the
mysqli_fetch_assoc() function? 17. How do you start a session in PHP?
18. What is the purpose of the
session_start() function? 19. How do you redirect a user to another page in PHP?
20. What is the use of the
header() function in PHP? #οΈβ£ #php #webdevelopment #coding #programming #backend #scripting #serverside #dev
By: t.iss.one/DataScienceQ
Please open Telegram to view this post
VIEW IN TELEGRAM
β Interview question
What is the output of the following code?
Answer:
[1, 2, 3, 4]
tags: #python #interview #coding #programming #datastructures #list #mutable #dev
By: t.iss.one/DataScienceQ π
What is the output of the following code?
x = [1, 2, 3]
y = x
y.append(4)
print(x)
Answer:
tags: #python #interview #coding #programming #datastructures #list #mutable #dev
By: t.iss.one/DataScienceQ π
β Interview question
**What will be the output of this code?**
```python
x = [1, 2, 3]
y = x[:]
y[0] = 10
print(x)
```
Answer:
<spoiler>||[1, 2, 3]||</spoiler>
tags: #python #interview #coding #programming #list #slicing #mutable #dev
By: t.iss.one/DataScienceQ π
**What will be the output of this code?**
```python
x = [1, 2, 3]
y = x[:]
y[0] = 10
print(x)
```
Answer:
<spoiler>||[1, 2, 3]||</spoiler>
tags: #python #interview #coding #programming #list #slicing #mutable #dev
By: t.iss.one/DataScienceQ π
Telegram
Python Data Science Jobs & Interviews
Your go-to hub for Python and Data Scienceβfeaturing questions, answers, quizzes, and interview tips to sharpen your skills and boost your career in the data-driven world.
Admin: @Hussein_Sheikho
Admin: @Hussein_Sheikho
β Interview question
What is the output of the following code?
Answer:
<class 'tuple'>
tags: #python #interview #coding #programming #function #returnvalues #tuple #dev
By: t.iss.one/DataScienceQ π
What is the output of the following code?
def my_func():
return "hello", "world"
result = my_func()
print(type(result))
Answer:
tags: #python #interview #coding #programming #function #returnvalues #tuple #dev
By: t.iss.one/DataScienceQ π
β Interview question
What does the following code do?
Answer:
Creates a directory named 'folder' with a subdirectory 'subfolder' if it doesn't already exist
tags: #python #os #filehandling #coding #programming #directory #makedirs #dev
By: t.iss.one/DataScienceQ π
What does the following code do?
import os
os.makedirs("folder/subfolder", exist_ok=True)
Answer:
tags: #python #os #filehandling #coding #programming #directory #makedirs #dev
By: t.iss.one/DataScienceQ π
β€1
KMeans Interview Questions
β What is the primary goal of KMeans clustering?
Answer:
To partition data into K clusters based on similarity, minimizing intra-cluster variance
β How does KMeans determine the initial cluster centers?
Answer:
By randomly selecting K data points as initial centroids
β What is the main limitation of KMeans regarding cluster shape?
Answer:
It assumes spherical and equally sized clusters, struggling with non-spherical shapes
β How do you choose the optimal number of clusters (K) in KMeans?
Answer:
Using methods like the Elbow Method or Silhouette Score
β What is the role of the inertia metric in KMeans?
Answer:
Measures the sum of squared distances from each point to its cluster center
β Can KMeans handle categorical data directly?
Answer:
No, it requires numerical data; categorical variables must be encoded
β How does KMeans handle outliers?
Answer:
Outliers can distort cluster centers and increase inertia
β What is the difference between KMeans and KMedoids?
Answer:
KMeans uses mean of points, while KMedoids uses actual data points as centers
β Why is feature scaling important for KMeans?
Answer:
To ensure all features contribute equally and prevent dominance by large-scale features
β How does KMeans work in high-dimensional spaces?
Answer:
It suffers from the curse of dimensionality, making distance measures less meaningful
β What is the time complexity of KMeans?
Answer:
O(n * k * t), where n is samples, k is clusters, and t is iterations
β What is the space complexity of KMeans?
Answer:
O(k * d), where k is clusters and d is features
β How do you evaluate the quality of KMeans clustering?
Answer:
Using metrics like silhouette score, within-cluster sum of squares, or Davies-Bouldin index
β Can KMeans be used for image segmentation?
Answer:
Yes, by treating pixel values as features and clustering them
β How does KMeans initialize centroids differently in KMeans++?
Answer:
Centroids are initialized to be far apart, improving convergence speed and quality
β What happens if the number of clusters (K) is too small?
Answer:
Clusters may be overly broad, merging distinct groups
β What happens if the number of clusters (K) is too large?
Answer:
Overfitting occurs, creating artificial clusters
β Does KMeans guarantee a global optimum?
Answer:
No, it converges to a local optimum depending on initialization
β How can you improve KMeans performance on large datasets?
Answer:
Using MiniBatchKMeans or sampling techniques
β What is the effect of random seed on KMeans results?
Answer:
Different seeds lead to different initial centroids, affecting final clusters
#οΈβ£ #kmeans #machine_learning #clustering #data_science #ai #python #coding #dev
By: t.iss.one/DataScienceQ π
β What is the primary goal of KMeans clustering?
Answer:
β How does KMeans determine the initial cluster centers?
Answer:
β What is the main limitation of KMeans regarding cluster shape?
Answer:
β How do you choose the optimal number of clusters (K) in KMeans?
Answer:
β What is the role of the inertia metric in KMeans?
Answer:
β Can KMeans handle categorical data directly?
Answer:
β How does KMeans handle outliers?
Answer:
β What is the difference between KMeans and KMedoids?
Answer:
β Why is feature scaling important for KMeans?
Answer:
β How does KMeans work in high-dimensional spaces?
Answer:
β What is the time complexity of KMeans?
Answer:
β What is the space complexity of KMeans?
Answer:
β How do you evaluate the quality of KMeans clustering?
Answer:
β Can KMeans be used for image segmentation?
Answer:
β How does KMeans initialize centroids differently in KMeans++?
Answer:
β What happens if the number of clusters (K) is too small?
Answer:
β What happens if the number of clusters (K) is too large?
Answer:
β Does KMeans guarantee a global optimum?
Answer:
β How can you improve KMeans performance on large datasets?
Answer:
β What is the effect of random seed on KMeans results?
Answer:
#οΈβ£ #kmeans #machine_learning #clustering #data_science #ai #python #coding #dev
By: t.iss.one/DataScienceQ π
Genetic Algorithms Interview Questions
β What is the primary goal of Genetic Algorithms (GA)?
Answer:
To find optimal or near-optimal solutions to complex optimization problems using principles of natural selection
β How does a Genetic Algorithm mimic biological evolution?
Answer:
By using selection, crossover, and mutation to evolve a population of solutions over generations
β What is a chromosome in Genetic Algorithms?
Answer:
A representation of a potential solution encoded as a string of genes
β What is the role of the fitness function in GA?
Answer:
To evaluate how good a solution is and guide the selection process
β How does selection work in Genetic Algorithms?
Answer:
Better-performing individuals are more likely to be chosen for reproduction
β What is crossover in Genetic Algorithms?
Answer:
Combining parts of two parent chromosomes to create offspring
β What is the purpose of mutation in GA?
Answer:
Introducing small random changes to maintain diversity and avoid local optima
β Why is elitism used in Genetic Algorithms?
Answer:
To preserve the best solutions from one generation to the next
β What is the difference between selection and reproduction in GA?
Answer:
Selection chooses which individuals will reproduce; reproduction creates new offspring
β How do you represent real-valued variables in a Genetic Algorithm?
Answer:
Using floating-point encoding or binary encoding with appropriate decoding
β What is the main advantage of Genetic Algorithms?
Answer:
They can solve complex, non-linear, and multi-modal optimization problems without requiring derivatives
β What is the main disadvantage of Genetic Algorithms?
Answer:
They can be computationally expensive and may converge slowly
β Can Genetic Algorithms guarantee an optimal solution?
Answer:
No, they provide approximate solutions, not guaranteed optimality
β How do you prevent premature convergence in GA?
Answer:
Using techniques like adaptive mutation rates or niching
β What is the role of population size in Genetic Algorithms?
Answer:
Larger populations increase diversity but also increase computation time
β How does crossover probability affect GA performance?
Answer:
Higher values increase genetic mixing, but too high may disrupt good solutions
β What is the effect of mutation probability on GA?
Answer:
Too low reduces exploration; too high turns GA into random search
β Can Genetic Algorithms be used for feature selection?
Answer:
Yes, by encoding features as genes and optimizing subset quality
β How do you handle constraints in Genetic Algorithms?
Answer:
Using penalty functions or repair mechanisms to enforce feasibility
β What is the difference between steady-state and generational GA?
Answer:
Steady-state replaces only a few individuals per generation; generational replaces the entire population
#οΈβ£ #genetic_algorithms #optimization #machine_learning #ai #evolutionary_computing #coding #python #dev
By: t.iss.one/DataScienceQ π
β What is the primary goal of Genetic Algorithms (GA)?
Answer:
β How does a Genetic Algorithm mimic biological evolution?
Answer:
β What is a chromosome in Genetic Algorithms?
Answer:
β What is the role of the fitness function in GA?
Answer:
β How does selection work in Genetic Algorithms?
Answer:
β What is crossover in Genetic Algorithms?
Answer:
β What is the purpose of mutation in GA?
Answer:
β Why is elitism used in Genetic Algorithms?
Answer:
β What is the difference between selection and reproduction in GA?
Answer:
β How do you represent real-valued variables in a Genetic Algorithm?
Answer:
β What is the main advantage of Genetic Algorithms?
Answer:
β What is the main disadvantage of Genetic Algorithms?
Answer:
β Can Genetic Algorithms guarantee an optimal solution?
Answer:
β How do you prevent premature convergence in GA?
Answer:
β What is the role of population size in Genetic Algorithms?
Answer:
β How does crossover probability affect GA performance?
Answer:
β What is the effect of mutation probability on GA?
Answer:
β Can Genetic Algorithms be used for feature selection?
Answer:
β How do you handle constraints in Genetic Algorithms?
Answer:
β What is the difference between steady-state and generational GA?
Answer:
#οΈβ£ #genetic_algorithms #optimization #machine_learning #ai #evolutionary_computing #coding #python #dev
By: t.iss.one/DataScienceQ π
β Interview question
What is the output of the following code?
Answer:
15
tags: #python #advanced #coding #programming #interview #nonlocal #function #dev
By: t.iss.one/DataScienceQ π
What is the output of the following code?
def outer():
x = 10
def inner():
nonlocal x
x += 5
return x
return inner()
result = outer()
print(result)
Answer:
tags: #python #advanced #coding #programming #interview #nonlocal #function #dev
By: t.iss.one/DataScienceQ π
βοΈ Interview question
What is the output of the following code?
Answer:
3
#β£ tags: #python #advanced #coding #programming #interview #deepcopy #mutable #dev
By: t.iss.one/DataScienceQ π
What is the output of the following code?
import copy
a = [1, 2, [3, 4]]
b = copy.deepcopy(a)
b[2][0] = 'X'
print(a[2][0])
Answer:
#β£ tags: #python #advanced #coding #programming #interview #deepcopy #mutable #dev
By: t.iss.one/DataScienceQ π
Telegram
Python Data Science Jobs & Interviews
Your go-to hub for Python and Data Scienceβfeaturing questions, answers, quizzes, and interview tips to sharpen your skills and boost your career in the data-driven world.
Admin: @Hussein_Sheikho
Admin: @Hussein_Sheikho
βοΈ Interview question
What is the output of the following code?
Answer:
[1, 2]
#β£ tags: #python #advanced #coding #programming #interview #defaultarguments #mutable #dev
By: t.iss.one/DataScienceQ π
What is the output of the following code?
def func(a, b=[]):
b.append(a)
return b
print(func(1))
print(func(2))
Answer:
#β£ tags: #python #advanced #coding #programming #interview #defaultarguments #mutable #dev
By: t.iss.one/DataScienceQ π
βοΈ Interview question
What is the output of the following code?
Answer:
1
#οΈβ£ tags: #python #advanced #coding #programming #interview #strmethod #object #dev
By: t.iss.one/DataScienceQ π
What is the output of the following code?
class A:
def __init__(self):
self.x = 1
def __str__(self):
return str(self.x)
a = A()
print(a)
Answer:
#οΈβ£ tags: #python #advanced #coding #programming #interview #strmethod #object #dev
By: t.iss.one/DataScienceQ π
1. What is a database?
2. Why do we use databases in Python?
3. Name a popular database library for Python.
4. How do you connect to a SQLite database in Python?
5. What is the purpose of
6. How do you execute a query in Python using SQLite?
---
Explanation with Code Example (Beginner Level):
This example shows how to:
- Connect to a SQLite database.
- Create a table.
- Insert and retrieve data.
Answer:
1. A database is an organized collection of data.
2. We use databases to store, manage, and retrieve data efficiently.
3.
4. Use
5.
6. Use
#Python #Databases #SQLite #Beginner #Programming #Coding #LearnToCode
By: @DataScienceQ π
2. Why do we use databases in Python?
3. Name a popular database library for Python.
4. How do you connect to a SQLite database in Python?
5. What is the purpose of
cursor() in database operations? 6. How do you execute a query in Python using SQLite?
---
Explanation with Code Example (Beginner Level):
import sqlite3
# 1. Create a connection to a database (or create it if not exists)
conn = sqlite3.connect('example.db')
# 2. Create a cursor object to interact with the database
cursor = conn.cursor()
# 3. Create a table
cursor.execute('''
CREATE TABLE IF NOT EXISTS users (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
age INTEGER
)
''')
# 4. Insert data into the table
cursor.execute("INSERT INTO users (name, age) VALUES ('Alice', 25)")
cursor.execute("INSERT INTO users (name, age) VALUES ('Bob', 30)")
# 5. Commit changes
conn.commit()
# 6. Query the data
cursor.execute("SELECT * FROM users")
rows = cursor.fetchall()
for row in rows:
print(row)
# Close connection
conn.close()
This example shows how to:
- Connect to a SQLite database.
- Create a table.
- Insert and retrieve data.
Answer:
1. A database is an organized collection of data.
2. We use databases to store, manage, and retrieve data efficiently.
3.
sqlite3 is a popular library. 4. Use
sqlite3.connect() to connect. 5.
cursor() allows executing SQL commands. 6. Use
cursor.execute() to run queries.#Python #Databases #SQLite #Beginner #Programming #Coding #LearnToCode
By: @DataScienceQ π
β€1
1. What is a GUI?
2. Why use GUI in Python?
3. Name a popular GUI library for Python.
4. How do you create a window using Tkinter?
5. What is the purpose of
6. How do you add a button to a Tkinter window?
---
Explanation with Code Example (Beginner Level):
This code creates a simple GUI window with a label and button.
Answer:
1. GUI stands for Graphical User Interface.
2. To create interactive applications with buttons, forms, etc.
3. Tkinter is a popular library.
4. Use
5.
6. Use
#Python #GUI #Tkinter #Beginner #Programming #Coding #LearnToCode
By: @DataScienceQ π
2. Why use GUI in Python?
3. Name a popular GUI library for Python.
4. How do you create a window using Tkinter?
5. What is the purpose of
mainloop() in Tkinter? 6. How do you add a button to a Tkinter window?
---
Explanation with Code Example (Beginner Level):
import tkinter as tk
# 1. Create the main window
root = tk.Tk()
root.title("My First GUI")
# 2. Add a label
label = tk.Label(root, text="Hello, World!")
label.pack()
# 3. Add a button
def on_click():
print("Button clicked!")
button = tk.Button(root, text="Click Me", command=on_click)
button.pack()
# 4. Run the application
root.mainloop()
This code creates a simple GUI window with a label and button.
Answer:
1. GUI stands for Graphical User Interface.
2. To create interactive applications with buttons, forms, etc.
3. Tkinter is a popular library.
4. Use
tk.Tk() to create a window. 5.
mainloop() keeps the window open and responsive. 6. Use
tk.Button() and .pack() to add a button.#Python #GUI #Tkinter #Beginner #Programming #Coding #LearnToCode
By: @DataScienceQ π
Python Tip: Tuple Unpacking for Multiple Assignments
Assigning multiple variables at once from a sequence can be done elegantly using tuple unpacking (also known as sequence unpacking). It's clean and efficient.
Traditional way:
Using Tuple Unpacking:
This also works with lists and functions that return multiple values. It's often used for swapping variables without a temporary variable:
#PythonTip #TupleUnpacking #Assignment #Pythonic #Coding
---
By: @DataScienceQ β¨
Assigning multiple variables at once from a sequence can be done elegantly using tuple unpacking (also known as sequence unpacking). It's clean and efficient.
Traditional way:
coordinates = (10, 20)
x = coordinates[0]
y = coordinates[1]
print(f"X: {x}, Y: {y}")
Using Tuple Unpacking:
coordinates = (10, 20)
x, y = coordinates
print(f"X: {x}, Y: {y}")
This also works with lists and functions that return multiple values. It's often used for swapping variables without a temporary variable:
a = 5
b = 10
a, b = b, a # Swaps values of a and b
print(f"a: {a}, b: {b}") # Output: a: 10, b: 5
#PythonTip #TupleUnpacking #Assignment #Pythonic #Coding
---
By: @DataScienceQ β¨