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csv-pipeline

Process, transform, analyze, and report on CSV and JSON data files. Use when the user needs to filter rows, join datasets, compute aggregates, convert formats, deduplicate, or generate summary reports from tabular data. Works with any CSV, TSV, or JSON Lines file.

gitgoodordietrying0 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install gitgoodordietrying/csv-pipeline

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

CSV Data Pipeline

Process tabular data (CSV, TSV, JSON, JSON Lines) using standard command-line tools and Python. No external dependencies required beyond Python 3.

When to Use

  • User provides a CSV/TSV/JSON file and asks to analyze, transform, or report on it
  • Joining, filtering, grouping, or aggregating tabular data
  • Converting between formats (CSV to JSON, JSON to CSV, etc.)
  • Deduplicating, sorting, or cleaning messy data
  • Generating summary statistics or reports
  • ETL workflows: extract from one format, transform, load into another

Quick Operations with Standard Tools

Inspect
# Preview first rows
head -5 data.csv

# Count rows (excluding header)
tail -n +2 data.csv | wc -l

# Show column headers
head -1 data.csv

# Count unique values in a column (column 3)
tail -n +2 data.csv | cut -d',' -f3 | sort -u | wc -l
Filter with awk
# Filter rows where column 3 > 100
awk -F',' 'NR==1 || $3 > 100' data.csv > filtered.csv

# Filter rows matching a pattern in column 2
awk -F',' 'NR==1 || $2 ~ /pattern/' data.csv > matched.csv

# Sum column 4
awk -F',' 'NR>1 {sum += $4} END {print sum}' data.csv
Sort and Deduplicate
# Sort by column 2 (numeric)
head -1 data.csv > sorted.csv && tail -n +2 data.csv | sort -t',' -k2 -n >> sorted.csv

# Deduplicate by all columns
head -1 data.csv > deduped.csv && tail -n +2 data.csv | sort -u >> deduped.csv

# Deduplicate by specific column (keep first occurrence)
awk -F',' '!seen[$2]++' data.csv > deduped.csv

Python Operations (for complex transforms)

Read and Inspect
import csv, json, sys
from collections import Counter

def read_csv(path, delimiter=','):
    """Read CSV/TSV into list of dicts."""
    with open(path, newline='', encoding='utf-8') as f:
        return list(csv.DictReader(f, delimiter=delimiter))

def write_csv(rows, path, delimiter=','):
    """Write list of dicts to CSV."""
    if not rows:
        return
    with open(path, 'w', newl...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/gitgoodordietrying/csv-pipeline
Version
—
Commit
b2db10a5e54ceacedba5dc60f73fe0e588a45f2d
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

SKILL.md
# CSV Data Pipeline

Process tabular data (CSV, TSV, JSON, JSON Lines) using standard command-line tools and Python. No external dependencies required beyond Python 3.

## When to Use

- User provides a CSV/TSV/JSON file and asks to analyze, transform, or report on it
- Joining, filtering, grouping, or aggregating tabular data
- Converting between formats (CSV to JSON, JSON to CSV, etc.)
- Deduplicating, sorting, or cleaning messy data
- Generating summary statistics or reports
- ETL workflows: extract from one format, transform, load into another

## Quick Operations with Standard Tools

### Inspect

```bash
# Preview first rows
head -5 data.csv

# Count rows (excluding header)
tail -n +2 data.csv | wc -l

# Show column headers
head -1 data.csv

# Count unique values in a column (column 3)
tail -n +2 data.csv | cut -d',' -f3 | sort -u | wc -l
```

### Filter with `awk`

```bash
# Filter rows where column 3 > 100
awk -F',' 'NR==1 || $3 > 100' data.csv > filtered.csv

# Filter rows matching a pattern in column 2
awk -F',' 'NR==1 || $2 ~ /pattern/' data.csv > matched.csv

# Sum column 4
awk -F',' 'NR>1 {sum += $4} END {print sum}' data.csv
```

### Sort and Deduplicate

```bash
# Sort by column 2 (numeric)
head -1 data.csv > sorted.csv && tail -n +2 data.csv | sort -t',' -k2 -n >> sorted.csv

# Deduplicate by all columns
head -1 data.csv > deduped.csv && tail -n +2 data.csv | sort -u >> deduped.csv

# Deduplicate by specific column (keep first occurrence)
awk -F',' '!seen[$2]++' data.csv > deduped.csv
```

## Python Operations (for complex transforms)

### Read and Inspect

```python
import csv, json, sys
from collections import Counter

def read_csv(path, delimiter=','):
    """Read CSV/TSV into list of dicts."""
    with open(path, newline='', encoding='utf-8') as f:
        return list(csv.DictReader(f, delimiter=delimiter))

def write_csv(rows, path, delimiter=','):
    """Write list of dicts to CSV."""
    if not rows:
        return
    with open(path, 'w', newl...

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