Frictionless Framework

Introduction
Getting Started
Basic Examples
Data Management
Working in Console
- Overview
- Describe
- Convert
- Explore
- Extract
- Index
- List
- Publish
- Query
- Script
- Validate
Working in Python
- Actions
- Catalog
- Package
- Resource
- Dialect
- Schema
- Checklist
- Pipeline
- Detector
- Inquiry
- Report
- Table
- Error
Advanced Topics
- Design
- System
- Extension
Data Resources
- File
- Text
- Json
- Table
Data Sources
- Aws
- Buffer
- Local
- Multipart
- Remote
- Stream
Data Formats
- Csv
- Erd
- Excel
- Gsheets
- Html
- Inline
- Json
- JsonSchema
- Markdown
- Ods
- Pandas
- Parquet
- Spss
- Sql
- Yaml
- Zip
Data Portals
- Ckan
- Github
- Zenodo
Data Checks
- Baseline
- Table
- Row
- Cell
Data Steps
- Resource
- Table
- Field
- Row
- Cell
Data Fields
- Any
- Array
- Boolean
- Date
- Datetime
- Duration
- Geojson
- Geopoint
- Integer
- Number
- Object
- String
- Time
- Year
- Yearmonth
Data Errors
- Metadata
- Resource
- Data
- File
- Table
- Header
- Label
- Row
- Cell
Codebase
- Authors
- License
- Migration
- Changelog
- Contributing
Universe
Blog

Edit page in Livemark
(2024-12-13 12:49)

Query

Wit this command Frictionless will drop all invalid data like type errors in cells. Use validate if needed.

With query command you can explore tabular files within a Sqlite database.

Installation

CLI

pip install frictionless[sql]
pip install frictionless[sql,zenodo] # for examples in this tutorial

Usage

frictionless query https://zenodo.org/record/3977957