Results for “data-tables”

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time systems, tables, and WCS.

Extracts structured data from PDF documents including tables, forms, and scanned images using OCR

Access and manage NocoDB databases, tables, and records via REST API. Use when the user wants to view bases, list tables, inspect column schemas, query or filter row data, or insert new records into a self-hosted NocoDB instance. Also use for spreadsheet-style database lookups and data entry.

Query external data from Oxla — Kafka topics via catalogs, Apache Iceberg tables, and S3/GCS/Azure parquet/ORC files — alongside native Oxla tables. Use when querying Kafka topics with CREATE KAFKA CATALOG or CREATE REDPANDA CATALOG, reading Apache Iceberg tables with the catalog=>path.table syntax, loading or.

Automate Snowflake data warehouse operations: list databases, schemas, and tables, execute SQL statements, and manage data workflows via the Composio MCP integration.

Diagnose and observe an Oxla distributed analytical database using system catalog tables, Prometheus metrics, runtime log-level changes, and troubleshooting workflows for slow queries, node health, and memory/OOM pressure. Also covers debugging Oxla's external data sources, including the Redpanda/Kafka ingestion path.

Create a structured quarterly business report with table of contents, data tables, and page numbers.

Manage datasets, tables, and jobs in BigQuery. Run SQL queries, manage BigQuery resources, and perform basic data ingestion and analysis.

Converts CSV, Excel, or JSON data into a polished, interactive visual report page with KPI cards, charts, data tables, and insights.

Design normalized database schemas with tables, relationships, indexes, and constraints for any application domain. Use when the user requests database schema design or provides relevant inputs for this workflow.

A powerful data table component for displaying structured tabular data with features like sorting, filtering, pagination, selection, tree data, virtual scrolling, and more.

Compacts and prunes LanceDB tables in StaticFlow databases to merge fragment files, reduce open file descriptors, and reclaim storage.

Provision Bigtable instances, design performant schemas, and query data using gcloud, cbt, or client libraries.

Design and format publication-quality tables: column order, row grouping, notes, precision, reproducibility.

Guides Lightning Web Component developers in setting up lightning-datatable with stable row identity, typed columns, row actions, inline edit, and bounded infinite loading.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Documents MariaDB-specific UPDATE syntax and behavior, including single-table vs multi-table forms, assignment evaluation order, RETURNING with OLD_VALUE(), temporal tables, and common pitfalls. Use when writing, generating, or reviewing UPDATE statements targeting MariaDB.

Write and run analytical SQL queries against Redpanda SQL (Oxla), a distributed PostgreSQL-wire-compatible columnar database, including data loading, external sources, and type handling.

Provides safe, reversible database schema change patterns for PostgreSQL, MySQL, and common ORMs, with guidance on zero-downtime deployments, rollbacks, and migration tooling.

**Structure:**

Use this skill for tables, grids, filters, sorting, density, keyboard navigation, responsive behavior. Trigger when the task involves web design work related to Data Table Grid UX, implementation, audits, debugging, strategy, or validation.

Time-Series Data

Configure the Data Table screen component in Salesforce Screen Flows for row selection, including single/multi-select, column setup, and downstream consumption of selected rows.

Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

DataFrame operations with pandas and polars — groupby, joins, reshaping, performance. Use when manipulating tabular data, choosing between pandas and polars, optimizing DataFrame code, or translating between the two libraries.

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

`task-agent`: use when physical relational schema or database-enforced integrity changes; skip conceptual-model, repository-only, or unchanged relational-storage work.

Structured data + RAG. NL2SQL hybrid patterns (text-to-SQL then execute vs embed rows), table embedding strategies (row-level, schema-level, hybrid), semantic layer integration (Cube, dbt metrics), LangChain SQLDatabaseChain, LlamaIndex PandasQueryEngine, safe SQL execution (read-only, sandboxed), schema-aware retrieval. Full PostgreSQL + pgvector hybrid code. USE WHEN: user mentions "tabular RAG", "NL2SQL", "text to SQL", "RAG on tables", "database RAG", "SQL RAG", "semantic layer", "structured data RAG" DO NOT USE FOR: unstructured doc RAG - use `rag-architecture`; metadata filtering only - use `self-querying-retriever`; KG retrieval - use `graph-rag`

Database management and queries. Connect to SQL and NoSQL databases, run queries, and manage schemas.