Sample
Explode multiple DataFrame columns simultaneously with matching element counts and fill empty iterables with NaN
sha256:b2f645a2f8dcdf7e90bd3e5aa07e236bb884289dbfe359e1a7f1b28ce3b40c3e
PUBLISHED
L3_CONTRACT_PASS
MIT-0
Execution evidence
Declared environment and signed verification runs are separated so you can see exactly what this sample proves.
Evidence basisSigned contract pass
Verification receipts1
Verification levelL3_CONTRACT_PASS
Declared environment
- Execution context
- python
- Operating system
- linux
- Architecture
- x64
- Runtime
- python
- Language
- python
- Package manager
- pip
Verification-run environments
- Execution context
- python 3.12
- Operating system
- linux alpine · musl
- Architecture
- x64
- Runtime
- python 3.12
- Language
- python
- Package manager
- pip
- Execution
- container · docker
CONTAINER_RUN · compile:SKIPPED · contract:PASS · load:PASS · resolve:PASS · python@1 · 2026-08-17
Case
- Goal
- Explode multiple DataFrame columns simultaneously with matching element counts and fill empty iterables with NaN HOW
- Packages
-
pandas 2.3.3
- Environment
- python
- Created
- 2026-08-17T12:44:12Z
Contract
- Exploding multiple list-like columns simultaneously with DataFrame.explode unrolls corresponding elements row-wise while preserving row index labels.
- Exploding rows with mismatched collection lengths across target columns raises ValueError: columns must have matching element counts.
- Exploding an empty iterable yields a single row containing NaN for the exploded columns while preserving non-exploded column values.
- Passing ignore_index=True reindexes the unrolled DataFrame with a consecutive RangeIndex starting at 0.
Files
- NOTES.md
- csx.json
- requirements.lock
- requirements.txt
- test/contract.py
Download the source artifact (tar.gz)
Origin Seeder
csx-seed
Verification receipts
- python 3.12 · linux alpine/x64 · docker · CONTAINER_RUN · compile:SKIPPED · contract:PASS · load:PASS · resolve:PASS · python@1 · 2026-08-17 · ed25519:d91480838ac982c9