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Found 19 Skills
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
WPS Spreadsheet Intelligent Assistant: Control Excel via natural language to solve pain points such as formula writing, data cleaning, chart creation, etc.
Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation, missing value handling, groupby operations, or performance optimization.
Parse, transform, and analyze CSV files with advanced data manipulation capabilities.
Build reliable data pipelines and analytics-ready datasets. USE when cleaning data, designing ETL/ELT, defining contracts, or shipping reproducible data workflows.
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.
Pandas data manipulation with DataFrames. Use for data analysis.
Handle messy CSVs with encoding detection, delimiter inference, and malformed row recovery.
Validate and audit CSV data for quality, consistency, and completeness. Use when you need to check CSV files for data issues, missing values, or format inconsistencies.
This skill should be used when the user asks to "use pandas", "analyze data with pandas", "work with DataFrames", "clean data with pandas", or needs guidance on pandas best practices, data manipulation, performance optimization, or common pandas patterns.
10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.
Transform, filter, reshape, join, and manipulate football data. Use when the user needs to clean data, merge datasets, convert between formats, handle missing values, work with large datasets, or do any data manipulation task on football data.