Python Projects & Free Books
38K subscribers
604 photos
93 files
305 links
Python Interview Projects & Free Courses

Admin: @Coderfun
Download Telegram
Python Interview Questions:

Ready to test your Python skills? Letโ€™s get started! ๐Ÿ’ป


1. How to check if a string is a palindrome?

def is_palindrome(s):
return s == s[::-1]

print(is_palindrome("madam")) # True
print(is_palindrome("hello")) # False

2. How to find the factorial of a number using recursion?

def factorial(n):
if n == 0 or n == 1:
return 1
return n * factorial(n - 1)

print(factorial(5)) # 120

3. How to merge two dictionaries in Python?

dict1 = {'a': 1, 'b': 2}
dict2 = {'c': 3, 'd': 4}

# Method 1 (Python 3.5+)
merged_dict = {**dict1, **dict2}

# Method 2 (Python 3.9+)
merged_dict = dict1 | dict2

print(merged_dict)

4. How to find the intersection of two lists?

list1 = [1, 2, 3, 4]
list2 = [3, 4, 5, 6]

intersection = list(set(list1) & set(list2))
print(intersection) # [3, 4]

5. How to generate a list of even numbers from 1 to 100?

even_numbers = [i for i in range(1, 101) if i % 2 == 0]
print(even_numbers)

6. How to find the longest word in a sentence?

def longest_word(sentence):
words = sentence.split()
return max(words, key=len)

print(longest_word("Python is a powerful language")) # "powerful"

7. How to count the frequency of elements in a list?

from collections import Counter

my_list = [1, 2, 2, 3, 3, 3, 4]
frequency = Counter(my_list)
print(frequency) # Counter({3: 3, 2: 2, 1: 1, 4: 1})

8. How to remove duplicates from a list while maintaining the order?

def remove_duplicates(lst):
return list(dict.fromkeys(lst))

my_list = [1, 2, 2, 3, 4, 4, 5]
print(remove_duplicates(my_list)) # [1, 2, 3, 4, 5]

9. How to reverse a linked list in Python?

class Node:
def __init__(self, data):
self.data = data
self.next = None

def reverse_linked_list(head):
prev = None
current = head
while current:
next_node = current.next
current.next = prev
prev = current
current = next_node
return prev

# Create linked list: 1 -> 2 -> 3
head = Node(1)
head.next = Node(2)
head.next.next = Node(3)

# Reverse and print the list
reversed_head = reverse_linked_list(head)
while reversed_head:
print(reversed_head.data, end=" -> ")
reversed_head = reversed_head.next

10. How to implement a simple binary search algorithm?

def binary_search(arr, target):
low, high = 0, len(arr) - 1
while low <= high:
mid = (low + high) // 2
if arr[mid] == target:
return mid
elif arr[mid] < target:
low = mid + 1
else:
high = mid - 1
return -1

print(binary_search([1, 2, 3, 4, 5, 6, 7], 4)) # 3


Here you can find essential Python Interview Resources๐Ÿ‘‡
https://t.iss.one/pythonproz

Like for more resources like this ๐Ÿ‘ โ™ฅ๏ธ

Share with credits: https://t.iss.one/sqlspecialist

Hope it helps :)
๐Ÿ‘3
Forwarded from Artificial Intelligence
๐„๐š๐ซ๐ง ๐…๐‘๐„๐„ ๐Ž๐ซ๐š๐œ๐ฅ๐ž ๐‚๐ž๐ซ๐ญ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง๐ฌ ๐ข๐ง ๐Ÿ๐ŸŽ๐Ÿ๐Ÿ“ โ€” ๐‚๐ฅ๐จ๐ฎ๐, ๐€๐ˆ & ๐ƒ๐š๐ญ๐š!๐Ÿ˜

Oracleโ€™s Race to Certification is here โ€” your chance to earn globally recognized certifications for FREE!๐Ÿ’ฅ

๐Ÿ’ก Choose from in-demand certifications in:
โ˜๏ธ Cloud
๐Ÿค– AI
๐Ÿ“Š Data
โ€ฆand more!

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4lx2tin

โšกBut hurry โ€” spots are limited, and the clock is ticking!โœ…๏ธ
๐Ÿ‘1
๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฟ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ ๐˜๐—ผ ๐˜€๐—ต๐—ฎ๐—ฝ๐—ฒ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฐ๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ: ๐Ÿ‘‡

-> 1. Learn the Language of Data
Start with Python or R. Learn how to write clean scripts, automate tasks, and manipulate data like a pro.

-> 2. Master Data Handling
Use Pandas, NumPy, and SQL. These are your weapons for data cleaning, transformation, and querying.
Garbage in = Garbage out. Always clean your data.

-> 3. Nail the Basics of Statistics & Probability
You canโ€™t call yourself a data scientist if you donโ€™t understand distributions, p-values, confidence intervals, and hypothesis testing.

-> 4. Exploratory Data Analysis (EDA)
Visualize the story behind the numbers with Matplotlib, Seaborn, and Plotly.
EDA is how you uncover hidden gold.

-> 5. Learn Machine Learning the Right Way

Start simple:

Linear Regression

Logistic Regression

Decision Trees
Then level up with Random Forest, XGBoost, and Neural Networks.


-> 6. Build Real Projects
Kaggle, personal projects, domain-specific problemsโ€”donโ€™t just learn, apply.
Make a portfolio that speaks louder than your resume.

-> 7. Learn Deployment (Optional but Powerful)
Use Flask, Streamlit, or FastAPI to deploy your models.
Turn models into real-world applications.

-> 8. Sharpen Soft Skills
Storytelling, communication, and business acumen are just as important as technical skills.
Explain your insights like a leader.


๐—ฌ๐—ผ๐˜‚ ๐—ฑ๐—ผ๐—ปโ€™๐˜ ๐—ต๐—ฎ๐˜ƒ๐—ฒ ๐˜๐—ผ ๐—ฏ๐—ฒ ๐—ฝ๐—ฒ๐—ฟ๐—ณ๐—ฒ๐—ฐ๐˜.
๐—ฌ๐—ผ๐˜‚ ๐—ท๐˜‚๐˜€๐˜ ๐—ต๐—ฎ๐˜ƒ๐—ฒ ๐˜๐—ผ ๐—ฏ๐—ฒ ๐—ฐ๐—ผ๐—ป๐˜€๐—ถ๐˜€๐˜๐—ฒ๐—ป๐˜.

Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

Like if you need similar content ๐Ÿ˜„๐Ÿ‘

Hope this helps you ๐Ÿ˜Š
๐Ÿ‘3
๐Ÿฏ ๐—š๐—ฎ๐—บ๐—ฒ-๐—–๐—ต๐—ฎ๐—ป๐—ด๐—ถ๐—ป๐—ด ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฟ๐—ฒ๐—ฒ๐Ÿ˜

Want to break into Data Science or Tech?

Python is the #1 skill you need โ€” and starting is easier than you think.๐Ÿง‘โ€๐Ÿ’ปโœจ๏ธ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/3JemBIt

Your career upgrade starts today โ€” no excuses!โœ…๏ธ
๐Ÿ‘1
๐Ÿ’ ๐๐ž๐ฌ๐ญ ๐๐จ๐ฐ๐ž๐ซ ๐๐ˆ ๐‚๐จ๐ฎ๐ซ๐ฌ๐ž๐ฌ ๐ข๐ง ๐Ÿ๐ŸŽ๐Ÿ๐Ÿ“ ๐ญ๐จ ๐’๐ค๐ฒ๐ซ๐จ๐œ๐ค๐ž๐ญ ๐˜๐จ๐ฎ๐ซ ๐‚๐š๐ซ๐ž๐ž๐ซ๐Ÿ˜

In todayโ€™s data-driven world, Power BI has become one of the most in-demand tools for businessesใ€ฝ๏ธ๐Ÿ“Š

The best part? You donโ€™t need to spend a fortuneโ€”there are free and affordable courses available online to get you started.๐Ÿ’ฅ๐Ÿง‘โ€๐Ÿ’ป

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4mDvgDj

Start learning today and position yourself for success in 2025!โœ…๏ธ
๐Ÿ‘1
๐Ÿ“Š Top 10 Data Analytics Concepts Everyone Should Know ๐Ÿš€

1๏ธโƒฃ Data Cleaning ๐Ÿงน
Removing duplicates, fixing missing or inconsistent data.
๐Ÿ‘‰ Tools: Excel, Python (Pandas), SQL

2๏ธโƒฃ Descriptive Statistics ๐Ÿ“ˆ
Mean, median, mode, standard deviationโ€”basic measures to summarize data.
๐Ÿ‘‰ Used for understanding data distribution

3๏ธโƒฃ Data Visualization ๐Ÿ“Š
Creating charts and dashboards to spot patterns.
๐Ÿ‘‰ Tools: Power BI, Tableau, Matplotlib, Seaborn

4๏ธโƒฃ Exploratory Data Analysis (EDA) ๐Ÿ”
Identifying trends, outliers, and correlations through deep data exploration.
๐Ÿ‘‰ Step before modeling

5๏ธโƒฃ SQL for Data Extraction ๐Ÿ—ƒ๏ธ
Querying databases to retrieve specific information.
๐Ÿ‘‰ Focus on SELECT, JOIN, GROUP BY, WHERE

6๏ธโƒฃ Hypothesis Testing โš–๏ธ
Making decisions using sample data (A/B testing, p-value, confidence intervals).
๐Ÿ‘‰ Useful in product or marketing experiments

7๏ธโƒฃ Correlation vs Causation ๐Ÿ”—
Just because two things are related doesnโ€™t mean one causes the other!

8๏ธโƒฃ Data Modeling ๐Ÿง 
Creating models to predict or explain outcomes.
๐Ÿ‘‰ Linear regression, decision trees, clustering

9๏ธโƒฃ KPIs & Metrics ๐ŸŽฏ
Understanding business performance indicators like ROI, retention rate, churn.

๐Ÿ”Ÿ Storytelling with Data ๐Ÿ—ฃ๏ธ

Translating raw numbers into insights stakeholders can act on.
๐Ÿ‘‰ Use clear visuals, simple language, and real-world impact

โค๏ธ React for more
๐Ÿ‘1
Python Statements ๐Ÿ‘†
๐Ÿ‘1