Results for “pr”

Manage AWS RDS relational databases: provision instances, configure backups, manage replicas, troubleshoot connectivity, and optimize performance.

Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.

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

Creates, edits, and analyzes spreadsheet files with professional formatting, formula-based calculations, and error-free delivery.

Query, filter, transform, and aggregate JSON data using jq, with practical patterns for shell pipelines and CLI integration.

Creates, edits, converts, and automates LibreOffice Calc spreadsheets in ODS format, including formulas, charts, and batch processing.

Designs analytics architecture, plans events, defines KPIs, sets attribution boundaries, and reviews instrumentation across product and growth.

Creates, edits, converts, and automates spreadsheet workflows using LibreOffice Calc, including formulas, charts, and batch processing.

Provides PostgreSQL query patterns covering SELECT, JOINs, subqueries, CTEs, window functions, and advanced SQL techniques.

Use when optimizing SQL queries, designing database schemas, or tuning database performance. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis.

Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.

Expert patterns for Segment Customer Data Platform including Analytics.js, server-side tracking, tracking plans with Protocols, identity resolution, destinations configuration, and data governance ...

Set up, audit, and improve analytics tracking so marketing data is trustworthy.

Design PostgreSQL schemas with best practices for data types, indexing, constraints, and performance patterns.

Sets up a Node.js project to use the AWS SDK for JavaScript v3 and make DynamoDB service calls.

Creates, edits, and analyzes spreadsheet files using pandas and openpyxl, with formula-based calculations and professional formatting standards.

Designs an edit blueprint and uncertainty register for video projects, following a narrative loop and schema constraints.

Fetches stock quotes, search, history, comparisons, and crypto prices from Yahoo Finance via a read-only Python script.

Applies quantitative and qualitative analysis techniques, interprets experimental data, validates procedures, and selects appropriate methods with uncertainty quantification.

Query, filter, transform, and aggregate JSON data using jq, with practical patterns for shell pipelines and CLI integration.

Computes the Anderson-Darling test statistic and p-value using scipy.stats.anderson for evaluating predictions against ground truth.

Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.

Provides Python tools for biological computation, including sequence manipulation, file I/O, database access, structural bioinformatics, and phylogenetics.

Provides ClickHouse schema design, query optimization, and data ingestion patterns for high-performance analytical workloads.

Provides guidance on using the Aeon library for time series forecasting, covering model selection, implementation, and evaluation.

Query, filter, transform, and aggregate JSON data using jq, with practical patterns for shell pipelines and integration with CLI tools.

Computação paralela/distribuída. Escale pandas/NumPy além da memória disponível, DataFrames/Arrays paralelos, processamento multi-arquivo, grafos de tarefas, para datasets maiores que RAM e workflows paralelos.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.

Your won/lost/churn pattern analyst. Connect a CRM plus a product-analytics tool, then turn retrospective data into forward-looking action. Three modes. (1) WON, win pattern recognition that feeds your ICP and lookalike search. (2) LOST, loss pattern plus competitive intel that feeds a messaging refresh. (3) CHURN, churn theme extraction plus predictive scoring (which active accounts look like recent churners?). Trigger on "why are we winning?", "why are we losing?", "closed-lost autopsy", "churn patterns", "competitive intel rollup", "who do we lose to most?", "show me lookalike candidates to {winning customer}", "predictive churn", "which active accounts look like churners?", or any portfolio-level pattern recognition.

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

Prüft Frist, Form, Zuständigkeit, Rechtsweg und Sofortmaßnahmen für Behörden-, Gerichts- oder Registerwege in der Liquiditätsplanung und liefert eine Fristen- und Risikoampel mit Sofortschritten.

Calculates the mean, standard deviation, and P-value for user-provided numerical datasets, with optional result-only output.

Provides a lightweight local SQLite database access layer for AI agents via an MCP server, with installation and usage guidance.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.

Queries EVM blockchain data across 8 chains with USD pricing, including wallet portfolios, token info, transactions, gas, and contract inspection.