stock-data-skill
OpenClaw Skill for stock data analysis
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.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install gitgoodordietrying/csv-pipelineExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Process tabular data (CSV, TSV, JSON, JSON Lines) using standard command-line tools and Python. No external dependencies required beyond Python 3.
# 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
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 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
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...
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# 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...OpenClaw Skill for stock data analysis
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