✅ Question:
Explain data manipulation in Python using Pandas, covering DataFrame/Series objects, indexing/selection, operating on data, missing value handling, hierarchical indexing, combining datasets (concat, merge, join), aggregation & group‑by, pivot tables, and vectorized string operations.
This question comprehensively covers all major Python Pandas topics from Unit II and has appeared repeatedly in question banks and exam preparation materials—making it the most reliable 16‑mark question to expect.
✅ 1. Explain in detail the major data manipulation topics using Pandas in Python
✅ 2. Demonstrate how to combine datasets in Pandas using concat, merge, join, and append, and explain grouping and aggregation with pivot tables
These two questions encompass the entire core of Unit II content using Pandas and are most likely to appear in the upcoming exam. Let me know if you’d like top 5 questions or concise Python code snippets for revision!
✅ 1. Explain in detail the major data manipulation topics using Pandas in Python
✅ 2. Demonstrate how to combine datasets in Pandas using concat, merge, join, and append, and explain grouping and aggregation with pivot tables.
✅ 3. Discuss handling missing data, hierarchical indexing, and vectorized string operations in Pandas for EDA.
These three questions comprehensively cover the core Pandas functionalities from Unit II and are repeatedly featured in exam preparation materials, making them the most probable 16‑mark questions in your upcoming exam.
✅ 1. Explain in detail the major data manipulation topics using Pandas in Python.
✅ 2. Demonstrate how to combine datasets in Pandas using concat, merge, join, and append, and explain grouping and aggregation via pivot tables.
✅ 3. Discuss handling missing data, hierarchical indexing, and vectorized string operations in Pandas for EDA.
✅ 4. Explain data indexing, selection, and operations on Pandas Series and DataFrames (e.g., slicing, masking, fancy indexing).
✅ 5. Describe pivot tables, aggregation, and grouping methods in Pandas and their role in summarizing datasets.
These five questions are most likely to appear on the 16-mark portion of your upcoming exam, as they align exactly with the key Pandas-based EDA functionalities emphasized in Unit II. Let me know if you’d like concise notes or code snippets for any of these!
✅ 1. Explain in detail the major data manipulation topics using Pandas in Python
✅ 2. Demonstrate how to combine datasets in Pandas using concat, merge, join, and append, and explain grouping and aggregation using pivot tables.
✅ 3. Discuss handling missing data, hierarchical indexing, and vectorized string operations in Pandas for EDA.
✅ 4. Explain data indexing/selecting and operating on Pandas Series and DataFrames (e.g. slicing, masking, fancy indexing).
✅ 5. Describe pivot tables, aggregation, and grouping methods in Pandas, and their role in summarizing datasets.
✅ 6. Explain the difference between concat, append, merge, and join operations in Pandas.
✅ 7. What are hierarchical indexes (MultiIndex) in Pandas? Explain methods like swaplevel() and xs() with examples.
✅ 8. Demonstrate aggregation and grouping with multiple aggregation functions using groupby() and agg().
✅ 9. Explain vectorized string operations using .str accessor in Pandas.
✅ 10. Demonstrate handling missing data in Pandas using methods like dropna(), fillna(), forward/backward fill.
These questions are highly likely to appear in your exam’s 16‑mark section since they encompass the full spectrum of essential Pandas functionality in Unit II. Let me know if you’d like crisp notes or code examples for any topic.
EDA USING PYTHON
Data manipulation using Pandas - Pandas objects - Data indexing and selection - Operating on data - Handling missing data - Hierarchical indexing - Combining datasets: Concat, Append, Merge and Join - Aggregation and grouping - Pivot tables - Vectorized string operations refer CCS346 EXPLORATORY DATA ANALYSIS previous year question paper and give me one important 16 question that has 100% possiblikllty on upcming exam no explanation please give top 10 most high priority on unit 2 and list no based on proirity And no of times repeated in previous year question papers