Profile Parquet or CSV datasets with Polars to surface data quality issues.
npx skills add https://github.com/lowmason/agent-skills --skill explore-data-lowmason
Please help me install this Agent Skill. Skill: explore-data Source: https://github.com/lowmason/agent-skills/tree/main/explore-data Command: npx skills add https://github.com/lowmason/agent-skills --skill explore-data-lowmason
Profile a dataset with Polars before analysis to surface data-quality issues and guardrails that prevent modeling on flawed data.
Run the profiling script on a dataset (Parquet/CSV) to generate a concise quality report with flags and suggested next steps.
High-intent search queries and answers about installing and using this skill.
You can profile a dataset with Polars to surface data quality issues by running a script that generates per-column statistics, quality flags, and checks for nulls, duplicates, and schema problems before modeling.
To check candidate keys for uniqueness and identify duplicates in a CSV, apply a profiling script to assess cardinality, uniques, and silos, which flags duplicate rows and sentinel values in your data.
Yes, you can use Polars to assess panel balance and vintage as-of readiness for time-series data by profiling microdata to evaluate balance across periods and guide cleansing and modeling decisions.
Yes, the data profiling script works with both Parquet and CSV file formats, applying lazy Polars queries to new scrapes or microdata to assess shape, schema, nulls, and uniques.
The best way to generate a machine-readable summary of nulls and schema issues is to use a Polars profiling script that outputs an optional machine-readable summary with per-column statistics and quality flags.
ovachieverPerform lazy, expression-based DataFrame operations with Polars for CSV and Parquet pipelines.
edwifiguyValidate tabular dataset shape, dtypes, nulls, duplicates, and statistics before analysis.
lowmasonValidate datasets and analyses for publication readiness with Polars.
CuriousLearnerValidate data against JSON schemas, business rules, and quality standards.
