Results for “data-structure”

Use HasData APIs for web scraping and structured web data extraction.

Redis caching patterns, pub/sub, sessions, rate limiting, and data structures.

Guide users building a personal CRM from simple files to structured database.

Generate CSV, Markdown, and XLSX spreadsheets from structured tabular data.

Extract structured data from documents using AI-powered field extraction.

Extract structured fields from ro e-factura documents.

Extract structured fields from schedule k 1 documents.

Extract structured fields from bill of entry documents.

Generate validated JSON-LD structured data markup for any page type

Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions.

Profiles datasets automatically to assess data quality, structure, and completeness, generating reports with ydata-profiling, pandera, or manual pandas methods.

Audit and fix HTML metadata including page titles, meta descriptions, canonical URLs, Open Graph tags, Twitter cards, favicons, JSON-LD structured data, and robots directives.

Search scientific papers via the BGPT MCP server and retrieve structured experimental data — methods, results, conclusions, quality scores, and 25+ metadata fields per paper.

Transform raw data into compelling narratives with structured story frameworks, visualization techniques, and presentation templates for executive audiences.

Expert en optimisation recherche vocale (structured data, featured snippets, queries conversationnelles)

Extract structured data from LLM responses with Pydantic validation, automatic retries, and streaming support across multiple providers.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion to catch O(n²), N+1, and brute-force defaults.

Create clear, effective charts and dashboards from structured data using matplotlib, seaborn, and plotly. Use when the user requests data visualization or provides relevant inputs for this workflow.

Use when users need webpage scraping, structured data extraction, crawling strategy, anti-bot handling, selector design, or repeatable web data collection workflows.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion, catching O(n^2), N+1, and brute-force defaults.

Turns websites into CLI commands, reusing an existing Chrome login session for browser-backed data extraction and structured output.

Audit AEM Edge Delivery Services commerce product pages for search engine crawlability and indexing, then remediate issues with meta tags, structured data, canonical URLs, and image optimization.

Validates NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors using the `tao-daft validate` CLI tool.

End-to-end data pipeline for empirical research: fetch economic data from APIs (FRED, World Bank, IMF, BLS, OECD, Yahoo Finance), clean and transform raw data, construct strategy-specific variables, and validate panel structure. Use when asked to fetch data, download data, clean data, merge datasets, prepare analysis-ready data.

Prepares, audits, and organizes fundraising materials for investor due diligence, generating a readiness checklist and folder structure.

Write, optimize, and debug Apache Spark jobs for high-performance distributed data processing, ETL pipelines, and big data workloads.

Create data-driven charts with Vega-Lite and Vega, covering bar, line, scatter, heatmap, area, radar, and word cloud visualizations from structured data arrays.

Creating Excel spreadsheets programmatically with openpyxl — worksheets, data, formulas, charts, formatting, and named ranges. Use when generating financial models, data reports, dashboards, or any structured spreadsheet from data or templates.

Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-patterns).

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

在Vue3环境中，将包含多个字典（对象）的列表转换为仅包含值的列表（[[],[]]）或包含索引的字典列表（[{0:{}}, {1:{}}]）。

Audit datasets for structure, missingness, labeling, suspicious values, duplicate identifiers, and documentation readiness. Use when a researcher asks for data QA, codebook review, sanity checks, or pre-analysis cleanup guidance.

Guide through a structured data analysis workflow: define the question, validate data quality, select the appropriate analytical method, and produce decision-ready findings with caveats.

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

Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.