This repository is a hands-on guide to creating Pandas DataFrames using different methods.
It covers column-oriented (dict of lists), row-oriented (dict of dicts), mixed data types, missing values, and custom indexing.
Perfect for beginners who want to understand how DataFrames are constructed and how Pandas handles data types and indexing.
| 🧪 Task File | 📄 Description | 📷 Output Screenshot |
|---|---|---|
| task1.py | 📋 Dict of Lists (Basic) – Create DataFrame with column-oriented structure, custom index |  |
| task2.py | 🔍 Mixed Data Types – Float, string, boolean with .dtypes inspection |
 |
| task3.py | 📑 Dict of Dicts – Row-oriented data with inner keys as index |  |
| task4.py | ❓ Missing Values Handling – Dict of dicts with unequal keys → NaN filling |  |
| task5.py | 🔄 Custom Index & Column Order – Rearranging columns and labels |  |
| task6.py | ⚖️ Comparison – Dict of Lists vs Dict of Dicts (structure & transpose) |  |
- 📋 Creating DataFrames from Dictionary of Lists (column-first thinking)
- 📑 Creating DataFrames from Dictionary of Dictionaries (row-first thinking)
- 🔍 Inspecting mixed data types using
.dtypes - ❓ Handling missing values with NaN filling
- 🔄 Setting custom index and column ordering
- ⚖️ Understanding difference between column-oriented vs row-oriented structures
📊 Sunil Kumar Reddy Punnati
🎓 MCA Graduate | 💼 Data Analyst Intern
📍 Tirupati, India
💡 Passionate about Python, Pandas, and Data Analysis
🚀 Preparing for full-time roles in Data Analytics & Software Development
If you’re a recruiter, mentor, or fellow learner — let’s connect and grow together!
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A curated set of 6 Pandas DataFrame Creation Tasks covering beginner to advanced concepts.
Each task includes Python code (inside /pandas_dataframe_creation) and an output screenshot (inside /output) for easy reference.