This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://news.1rj.ru/str/addlist/8_rRW2scgfRhOTc0

✅ https://news.1rj.ru/str/Codeprogrammer

Today I am 3️⃣0️⃣ years old, I am excited to make more successes and achievements

My previous year was full of exciting events and economic, political and programmatic noise, but I kept moving forward

Best regards
Eng. @HusseinSheikho 🔤

Lambdas are not just one-line functions, they also preserve context

The logic is right where it is needed. No need to jump between lines.

# Without lambda — you have to jump around the code
def get_name(user):
    return user['name']

# Imagine there are 100–200 lines of code here...

users.sort(key=get_name)


# Sorting conditions right in place
users.sort(key=lambda user: user['name'])

👉 @DataScience4

Tuples use less memory than lists of the same size

>>> import sys
>>> sys.getsizeof(tuple(iter(range(20))))
200
>>> sys.getsizeof(list(iter(range(20))))
216

The difference is small, but when working with large amounts of data — it matters. 🤕

👉 @DataScience4

🏳️‍🌈 Notes "Mastering Python"
✅ From Basic to Advanced

👨🏻‍💻 An excellent note that teaches everything from basic concepts to building professional projects with Python.

⭕️ Basic concepts like variables, data types, and control flow

⏺ Functions, modules, and writing reusable code

⭕️ Data structures like lists, dictionaries, sets, and tuples

⏺ Object-oriented programming: classes, inheritance, and polymorphism

⭕️ Working with files, error handling, and debugging

⬅️ Alongside, with practical projects like data analysis, web scraping, and working with APIs, you learn how to apply Python in the real world.

🌐 #Data_Science #DataScience
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Clean code tip for Python:

Use a dictionary to remove duplicates from a list while preserving the order of elements.

names = ["John", "Daisy", "Bob", "Lilly", "Bob", "Daisy"]

unique_names = list({name: name for name in names}.values())

print(unique_names)
# ['John', 'Daisy', 'Bob', 'Lilly']

The point is that dictionary keys are unique, and starting from Python 3.7, the order of insertion is preserved.
So this is a concise way to remove duplicates without losing order.

👉  @DataScience4