Python for Data Analysts
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Find top Python resources from global universities, cool projects, and learning materials for data analytics.

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Useful links: heylink.me/DataAnalytics
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Python Pandas 🐼
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🚀 Essential Python/ Pandas snippets to explore data:
 
1.   .head() - Review top rows
2.   .tail() - Review bottom rows
3.   .info() - Summary of DataFrame
4.   .shape - Shape of DataFrame
5.   .describe() - Descriptive stats
6.   .isnull().sum() - Check missing values
7.   .dtypes - Data types of columns
8.   .unique() - Unique values in a column
9.   .nunique() - Count unique values
10.   .value_counts() - Value counts in a column
11.   .corr() - Correlation matrix
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🔥 Guys, Another Big Announcement!

I’m launching a Python Interview Series 🐍💼 — your complete guide to cracking Python interviews from beginner to advanced level!

This will be a week-by-week series designed to make you interview-ready — covering core concepts, coding questions, and real interview scenarios asked by top companies.

Here’s what’s coming your way 👇

🔹 Week 1: Python Fundamentals (Beginner Level)
• Data types, variables & operators
• If-else, loops & functions
• Input/output & basic problem-solving
💡 *Practice:* Reverse string, Prime check, Factorial, Palindrome

🔹 Week 2: Data Structures in Python
• Lists, Tuples, Sets, Dictionaries
• Comprehensions (list, dict, set)
• Sorting, searching, and nested structures
💡 *Practice:* Frequency count, remove duplicates, find max/min

🔹 Week 3: Functions, Modules & File Handling
*args, *kwargs, lambda, map/filter/reduce
• File read/write, CSV handling
• Modules & imports
💡 *Practice:* Create custom functions, read data files, handle errors

🔹 Week 4: Object-Oriented Programming (OOP)
• Classes, objects, inheritance, polymorphism
• Encapsulation & abstraction
• Magic methods (__init__, __str__)
💡 *Practice:* Build a simple class like BankAccount or StudentSystem

🔹 Week 5: Exception Handling & Logging
try-except-else-finally
• Custom exceptions
• Logging errors & debugging best practices
💡 *Practice:* File operations with proper error handling

🔹 Week 6: Advanced Python Concepts
• Decorators, generators, iterators
• Closures & context managers
• Shallow vs deep copy
💡 *Practice:* Create your own decorator, generator examples

🔹 Week 7: Pandas & NumPy for Data Analysis
• DataFrame basics, filtering & grouping
• Handling missing data
• NumPy arrays, slicing, and aggregation
💡 *Practice:* Analyze small CSV datasets

🔹 Week 8: Python for Analytics & Visualization
• Matplotlib, Seaborn basics
• Data summarization & correlation
• Building simple dashboards
💡 *Practice:* Visualize sales or user data

🔹 Week 9: Real Interview Questions (Intermediate–Advanced)
• 50+ Python interview questions with answers
• Common logical & coding tasks
• Real company-style questions (Infosys, TCS, Deloitte, etc.)
💡 *Practice:* Solve daily problem sets

🔹 Week 10: Final Interview Prep (Mock & Revision)
• End-to-end mock interviews
• Python project discussion tips
• Resume & GitHub portfolio guidance

📌 Each week includes:
Key Concepts & Examples
Coding Snippets & Practice Tasks
Real Interview Q&A
Mini Quiz & Discussion

👍 React ❤️ if you’re ready to master Python interviews!

👇 You can access it from here: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/2099
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