SKILL
---
name: data-analysis
description: Guidelines for reliable exploratory data analysis.
tags:
- data
- pandas
- analytics
version: "1.0"
---
## Data Loading
Always inspect shape, dtypes, and null counts before any analysis.
Document all data sources and their refresh cadence.
## Data Cleaning
Be explicit about how nulls are handled (drop, fill, flag).
Validate column ranges and categorical values before transforming.
Never modify the original DataFrame in-place without a backup.
## Visualisation
Use matplotlib or seaborn. Label all axes with units. Include a title.
Use colorblind-friendly palettes.when to use it
Community prompt sourced from the open-source GitHub repo AnikMallick/promptframe (MIT). A "SKILL" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
roleplaycommunitygeneral
source
AnikMallick/promptframe · MIT