Dataql Quick

by adrianolaselva

data

Quick data queries and previews. Use when user wants to see contents of a data file, check schema, or do simple filtering on CSV, JSON, or other data files.

Skill Details

Repository Files

1 file in this skill directory


name: dataql-quick description: Quick data queries and previews. Use when user wants to see contents of a data file, check schema, or do simple filtering on CSV, JSON, or other data files. tools:

  • Bash

DataQL Quick Query

For fast data inspection and simple queries using DataQL.

Quick Commands

Task Command
Preview file dataql run -f <file> -q "SELECT * FROM <table> LIMIT 5"
Count rows dataql run -f <file> -q "SELECT COUNT(*) FROM <table>"
Check schema dataql run -f <file> -q ".schema <table>"
List tables dataql run -f <file> -q ".tables"
Distinct values dataql run -f <file> -q "SELECT DISTINCT <column> FROM <table>"
Filter rows dataql run -f <file> -q "SELECT * FROM <table> WHERE <condition> LIMIT 10"

File Naming Convention

  • Table name = filename without extension
  • users.csv -> table name is users
  • orders.json -> table name is orders
  • data.parquet -> table name is data

Examples

Preview a CSV file

dataql run -f users.csv -q "SELECT * FROM users LIMIT 5"

Count records

dataql run -f orders.json -q "SELECT COUNT(*) as total FROM orders"

Check structure

dataql run -f data.parquet -q ".schema data"

Simple filter

dataql run -f products.csv -q "SELECT name, price FROM products WHERE price > 100 LIMIT 10"

Read from stdin

cat data.csv | dataql run -f - -q "SELECT * FROM stdin_data LIMIT 5"

Note: When reading from stdin, the default table name is stdin_data.

Supported Formats

  • CSV (with custom delimiter: -d ";")
  • JSON (arrays or objects)
  • JSONL/NDJSON
  • XML
  • YAML
  • Parquet
  • Excel (.xlsx, .xls)
  • Avro
  • ORC

Output Options

  • Default: formatted table
  • JSON output: pipe to jq or use export
  • CSV export: -e output.csv -t csv
  • JSONL export: -e output.jsonl -t jsonl

Exploratory Statistics

# Get comprehensive statistics for a file
dataql describe -f data.csv

# Describe specific table after loading
dataql run -f data.csv -q ".describe data"

Quick Troubleshooting

Problem Solution
"column not found" Check column names with .schema (case sensitive)
"table not found" Table name = filename without extension
Too much output Add LIMIT 10 or LIMIT 5 to query
File too large Use --cache flag to cache imported data
Wrong delimiter Use -d ";" for semicolon-separated files

Notes

  • Always use LIMIT for large files to avoid overwhelming output
  • Use .schema first to understand column names and types
  • For stdin input with non-CSV format: -i json or -i jsonl
  • Use --cache for repeated queries on the same file
  • Use -Q (quiet) to suppress progress bar in scripts

Related Skills

Xlsx

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

data

Clickhouse Io

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

datacli

Clickhouse Io

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

datacli

Analyzing Financial Statements

This skill calculates key financial ratios and metrics from financial statement data for investment analysis

data

Data Storytelling

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

data

Kpi Dashboard Design

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.

designdata

Dbt Transformation Patterns

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

testingdocumenttool

Sql Optimization Patterns

Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

designdata

Anndata

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

arttooldata

Xlsx

Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.

tooldata

Skill Information

Category:Data
Last Updated:1/23/2026