Python

🛠️ Skills & Knowledge

Python for Data Engineering (Practice)

• Data Cleansing: Using .strip(), .upper(), and .split() to clean and format malformed string data, and f-strings for reporting.

• Error Handling & Type Casting: Implementing try-except-finally blocks to catch exceptions, handling specific workflows like ZeroDivisionError, and using float() for safe data conversion.

• Object-Oriented Programming (OOP) for Pipelines: Implementing class structures using @dataclass, initializing internal states, and defining post-initialization hooks via __post_init__ for automated data standardization.

• Dynamic Data Ingestion (*args): Using dynamic positional arguments to handle and unpack variable numbers of data batches seamlessly within methods.

• List & Dict Comprehensions: Utilizing List Comprehensions and for loops with if-else conditionals to filter data based on business rules, and Dictionary Comprehensions for transforming structured data formats (Key-Value mappings).

• Data Structures:

• Lists: Creating via list(), adding elements with .append() / .extend(), and duplicating states using .copy().

• Dictionaries: Initializing empty dictionaries {} and mapping structured key-value pairs.

• Sets: Initializing with set() and using .add() to eliminate duplicates (Deduplication).

• Built-in Functions: Using round() for decimal formatting, sum() and len() for aggregations, and enumerate() for custom loop indexing.

• Memory Optimization: Applying .clear() to wipe out datasets and optimize memory usage after processing.

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📂 Project Structure

1. python-data-cleaning-practice.py

• Content: A 10-step Python data processing workflow.
• Focus: Hands-on practice with core Python data structures, error safety, and list comprehension techniques.

2. Python-OOP.py

• Content: Designing a reliable sales data pipeline with Python classes and exception handling..
• Focus: Harnessing the power of Python @dataclass, dynamic argument packing (*args), dictionary transformations via comprehensions, and resilient try-except error management to process multi-batch transactions safely.

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