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Pandas for time series analysis, OrcaFlex results processing, and marine engineering data workflows
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想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
基于 SOC 职业分类
正在显示 SKILL.md
| name | pandas-data-processing |
| version | 1.0.0 |
| description | Pandas for time series analysis, OrcaFlex results processing, and marine engineering data workflows |
| type | reference |
| author | workspace-hub |
| category | data |
| tags | ["pandas","data-processing","time-series","csv","engineering","orcaflex"] |
| platforms | ["python"] |
| capabilities | [] |
| requires | [] |
Use Pandas data processing when you need:
Avoid when:
import pandas as pd
import numpy as np
from pathlib import Path
import plotly.graph_objects as go
def process_orcaflex_results(
results_dir: Path,
output_dir: Path
) -> dict:
*See sub-skills for full details.*
### Example 2: Wave Scatter Diagram Analysis
```python
def process_wave_scatter_diagram(
scatter_csv: Path,
output_dir: Path
) -> pd.DataFrame:
"""
Process wave scatter diagram and calculate occurrence frequencies.
Args:
scatter_csv: Path to wave scatter CSV
*See sub-skills for full details.*
### Example 3: Fatigue Damage Calculation
```python
def calculate_fatigue_damage(
stress_ranges: pd.DataFrame,
sn_curve: dict,
design_life_years: float = 25
) -> pd.DataFrame:
"""
Calculate fatigue damage using stress range histogram.
Args:
*See sub-skills for full details.*
```python
() -> pd.DataFrame:
Benchmark different Pandas operations performance.
Args:
data_size: Number of rows to test
*See sub-skills full details.*
- **Pandas Documentation**: https://pandas.pydata.org/docs/
- **Pandas Cheat Sheet**: https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
- **Time Series Analysis**: https://pandas.pydata.org/docs/user_guide/timeseries.html
- **GroupBy Operations**: https://pandas.pydata.org/docs/user_guide/groupby.html
- **Performance Tips**: https://pandas.pydata.org/docs/user_guide/enhancingperf.html
---
**Use this skill time series analysis data processing DigitalModel!**
- [ Time Series Analysis](-time-series-analysis/SKILL.md)
- [ Statistical Analysis](-statistical-analysis/SKILL.md)
- [ Data Transformation](-data-transformation/SKILL.md)
- [ Multi-File Processing](-multi-file-processing/SKILL.md)
- [ GroupBy Operations](-groupby-operations/SKILL.md)
- [ Memory Efficiency (+)](-memory-efficiency/SKILL.md)