उपयोग तब करें जब उपयोगकर्ता प्रयोगों, खोजों, या ट्यूटोरियल्स के लिए Jupyter

वापरा जेव्हा वापरकर्ता प्रयोग, अन्वेषण किंवा ट्यूटोरियलसाठी Jupyter नोटबुक्स

ಬಳಕೆದಾರರು ಪ್ರಯೋಗಗಳು, ಅನ್ವೇಷಣೆಗಳು ಅಥವಾ ಟ್ಯುಟೋರಿಯಲ್‌ಗಳಿಗಾಗಿ Jupyter ನೋಟ್ಬುಕ್‌ಗಳು

زمانی استفاده شود که کاربر درخواست ایجاد، ساختاردهی یا ویرایش دفترچه‌های

Използвайте, когато потребителят иска да създаде, да изгради основна

Користити када корисник затражи да се креира, структурира или уреди Jupyter

Export a Google Sheets spreadsheet as a CSV file for local backup or processing.

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.

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.

Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.

'Automates the Privacy Impact Assessment (PIA) workflow including data flow mapping, privacy risk scoring matrices,

Chinese mutual fund intelligent advisor with real-time valuation, buy/sell suggestions, profit tracking, SIP planning, OCR recognition, and stock-fund linkage. Supports offline mode and multi-source caching.

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Read, write, append, and list local files in the session's working directory. Use when you need to persist output to disk, read input files, or manipulate file system safely. Supports text files, JSON, CSV, Markdown.

Scrape a public Letterboxd user's watchlist into a CSV/JSONL list of titles and film URLs without logging in. Use when a user asks to export, scrape, or mirror a Letterboxd watchlist, or to build watch-next queues.

AI-powered B2B lead scoring model. Predicts conversion probability for potential customers using machine learning (LightGBM + SHAP). CSV upload or API integration.

Analyzes sentiment from social media, news headlines, and financial text. Outputs positive/negative/neutral scores with confidence levels and key phrase extraction.

You are a senior FP&A professional. You build financial models, run variance analysis, produce board-ready reports, and turn raw numbers into strategic decisions. You work with whatever data the user

Interpret CSV, JSON, and structured data, extract insights, identify patterns, and recommend appropriate visualizations.

Track leads locally, manage outreach campaigns, and export as CSV for download.

Double-entry, full-cycle accounting suite built for AI agents. Converts bank CSVs, OFX, and QBO files into balanced, auditable books — balance sheet, income statement, general ledger, trial balance. All data stays in a single local SQLite file.

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Use this skill when Alex says:

Create project timeline visualizations for grant proposals

Create beautiful maps in seconds. Geocode addresses, visualize GeoJSON/CSV data, search places, and build shareable map URLs. No GIS skills needed. Agents earn points for contributions.

Analyze bank transactions, categorize spending, track monthly budgets, detect overspending and anomalies. Outputs interactive HTML report.

Financial analysis and research workflows for market research, equity research, comparable companies, precedent transactions, and DCF valuation. Use when asked to build or critique DCF models, comps/precedents tables, competitor or strategy analysis, market sizing, or to deliver analyst-ready outputs in Excel, PowerPoint, or Markdown from CSV/Excel/SQL/API/web data.

Analyze AWS Cost & Usage Reports to identify top cost drivers, waste, and anomalies across all linked accounts

"Convert CSV data to JSON array of objects"

Data processing pipelines for OpenClaw. Deploy skills from the Expanso marketplace to transform, analyze, and process data locally.

Sentiment analysis for brands and products across Twitter, Reddit, and Instagram. Monitor public opinion, track brand reputation, detect PR crises, surface complaints and praise at scale — analyze 70K+ posts with bulk CSV export and Python/pandas. Social listening and brand monitoring powered by 1.5B+ indexed posts.

Convert PDF bank statements to CSV/JSON.

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scanning-market-movers

clay-architecture-variants

finta-local-dev-loop

finta-sdk-patterns

fondo-local-dev-loop

linear-data-handling

vercel-data-handling

windsurf-data-handling

Scan for GDPR compliance issues in data handling and privacy practices. Use when ensuring EU data protection compliance. Trigger with 'scan GDPR compliance', 'check data privacy', or 'validate GDPR'.

csv-processor

Process and validate data inputs

Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.

Detects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling. Checks if features/statistics would be available at prediction time.

Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.

Reactive streams and event-driven programming in Golang using samber/ro — ReactiveX implementation with 150+ type-safe operators, cold/hot observables, 5 subject types (Publish, Behavior, Replay, Async, Unicast), declarative pipelines via Pipe, 40+ plugins (HTTP, cron, fsnotify, JSON, logging), automatic backpressure, error propagation, and Go context integration. Apply when using or adopting samber/ro, when the codebase imports github.com/samber/ro, or when building asynchronous event-driven pipelines, real-time data processing, streams, or reactive architectures in Go. Not for finite slice transforms (-> See golang-samber-lo skill).