pandas-pro
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation tasks such as joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, or performance optimization of large datasets.
npx skills add Jeffallan/claude-skills --skill pandas-pro --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Pandas Pro Expert pandas developer specializing in efficient data manipulation, analysis, and transformation workflows with production-grade performance patterns. ## Core Workflow 1. **Assess data structure** — Examine dtypes, memory usage, missing values, data quality: ```python print(df.dtypes) print(df.memory_usage(deep=True).sum() / 1e6, "MB") print(df.isna().sum()) print(df.describe(include="all")) ``` 2. **Design transformation** — Plan vectorized operations, avoid loops, identify indexing strategy 3. **Implement efficiently** — Use vectorized methods, method chaining, proper indexing 4. **Validate results** — Check dtypes, shapes, null counts, and row counts: ```python assert result.shape[0] == expected_rows, f"Row count mismatch: {result.shape[0]}" assert result.isna().sum().sum() == 0, "Unexpected nulls after transform" assert set(result.columns) == expected_cols ``` 5. **Optimize** — Profile memory, apply categorical types, use chunking if needed ## Reference Guide Load detailed guidance based on context: | Topic | Reference | Load When | |-------|-----------|-----------| | DataFrame Operations | `references/dataframe-operations.md` | Indexing, selection, filtering, sor
- Core Workflow
- Reference Guide
- Code Patterns
- Vectorized Operations (before/after)
- Safe Subsetting with .copy()
- GroupBy Aggregation
- Merge with Validation
- Missing Value Handling
- Time Series Resampling
- Pivot Table
- Memory Optimization
- Constraints
- MUST DO
- MUST NOT DO
What does the pandas-pro skill do?
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation tasks such as joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, or performance optimization of large datasets.
How do I install it?
Run `npx skills add Jeffallan/claude-skills --skill pandas-pro --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Jeffallan/claude-skills, a repository with 10,871 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.