PD-Explain: A Unified Python-native Framework for Query Explanations Over DataFrames
Summary: PD-Explain: Python-native, Pandas-integrated toolkit unifying literature-backed query-explanation methods as configurable functions for DataFrame analysis. Automatically detects interesting result parts and emits visualizations plus natural-language summaries across four explanation types to aid exploration. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Itay Elyashiv
- 2. Amir Gilad
- 3. Edna Isakov
- 4. Tal Tikochinsky
- 5. Amit Somech
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 214 | Scorpion: Explaining Away Outliers in Aggregate Queries | 2013 | VLDB | 0.0003363692 |
| 942 | A Formal Approach to Finding Explanations for Database Queries | 2014 | SIGMOD | 0.00015155714 |
| 1,119 | The Complexity of Causality and Responsibility for Query Answers and non-Answers | 2011 | VLDB | 0.0001386199 |
| 2,602 | Tracing Data Errors with View-Conditioned Causality | 2011 | SIGMOD | 8.4667197e-05 |
| 2,868 | Computing the Shapley Value of Facts in Query Answering | 2022 | SIGMOD | 7.9816425e-05 |
| 3,393 | Lux: Always-on Visualization Recommendations for Exploratory Dataframe Workflows | 2022 | VLDB | 7.1483239e-05 |
| 7,364 | ExplainED: Explanations for EDA Notebooks | 2020 | VLDB | 4.7519211e-05 |
| 8,388 | FEDEX: An Explainability Framework for Data Exploration Steps | 2022 | VLDB | 4.5297787e-05 |
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| 8,388 | FEDEX: An Explainability Framework for Data Exploration Steps | 2022 | VLDB | 4.5297787e-05 |
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| 7,364 | ExplainED: Explanations for EDA Notebooks | 2020 | VLDB | 4.7519211e-05 |
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