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Found 25 Skills
Parse, transform, and analyze CSV files with advanced data manipulation capabilities.
Standardize and format phone numbers with international support, validation, and multiple output formats.
Track product champions for job changes and qualify their new companies against ICP. Takes a CSV of known champions (with LinkedIn URLs), creates a baseline snapshot via Apify enrichment, then detects when champions move to new companies. Scores new companies on a 0-4 ICP fit scale. Outputs a downloadable CSV of movers with qualification verdicts.
Reconcile Venmo business transactions and separate personal from business.
Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data.
This skill should be used when analyzing CSV datasets, handling missing values through intelligent imputation, and creating interactive dashboards to visualize data trends. Use this skill for tasks involving data quality assessment, automated missing value detection and filling, statistical analysis, and generating Plotly Dash dashboards for exploratory data analysis.
Use this skill any time the user wants to analyze data, create charts, or build data visualizations. This includes: sales analysis, financial modeling, cohort analysis, funnel analysis, A/B test results, KPI tracking, data reports, revenue breakdowns, user retention analysis, conversion rate analysis, CSV summarization, and dashboard creation. Also trigger when: user says 分析这组数据, 做个图表, 数据可视化, 销售分析, 漏斗分析, 留存分析, 做个数据报表. If data needs to be analyzed or visualized, use this skill.
This skill should be used when analyzing sector rotation patterns and market cycle positioning. It fetches sector uptrend data from CSV (no API key required) and optionally accepts chart images for supplementary analysis. Use this skill when the user requests sector rotation analysis, cyclical vs defensive assessment, overbought/oversold identification, or market cycle phase estimation. All analysis and output are conducted in English.
Expert in high-performance CSV processing, parsing, and data cleaning using Python, DuckDB, and command-line tools. Use when working with CSV files, cleaning data, transforming datasets, or processing large tabular data files.
Handle messy CSVs with encoding detection, delimiter inference, and malformed row recovery.
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
This skill should be used when users need to analyze CSV or Excel files, understand data patterns, generate statistical summaries, or create data visualizations. Trigger keywords include "analyze CSV", "analyze Excel", "data analysis", "CSV analysis", "Excel analysis", "data statistics", "generate charts", "data visualization", "分析CSV", "分析Excel", "数据分析", "CSV分析", "Excel分析", "数据统计", "生成图表", "数据可视化".