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taishan1994
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data-analysis

Analyze CSV, Excel, or JSON datasets and generate plots with Python.

30|7|Updated Nov 10, 2025
Search Tags:#python#visualization#statistics#data-analysis#matplotlib#numpy#data-cleaning
One-click install
npx skills add https://github.com/taishan1994/Agent-Handbook --skill data-analysis-taishan1994
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/taishan1994/Agent-Handbook/tree/main/mini-agents/Mini_Agents/skills/data-analysis
Command: npx skills add https://github.com/taishan1994/Agent-Handbook --skill data-analysis-taishan1994

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, matplotlib, and includes scripts (resource) components.

What problem does it solve?

Data analysis and visualization tasks can be streamlined with Python scripts for statistics, visualization, and data cleaning.

Core Features & Use Cases

  • Data loading and exploration
  • Statistical analysis
  • Data visualization
  • Data cleaning and preprocessing
  • Use Case: quickly analyze datasets (CSV, Excel, JSON) and generate plots for reports.

Quick Start

Run the basic_stats.py script to compute statistics on your dataset, or run visualization.py to generate plots from your data.

Frequently Asked Questions about data-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute descriptive statistics from a CSV dataset using Python?▼

You can compute descriptive statistics by running the basic_stats.py Python script on your CSV, Excel, or JSON dataset. This data analysis process leverages numpy to calculate core statistical values directly from your loaded data.

Can I generate matplotlib visualizations from Excel or JSON data?▼

Yes, you can generate matplotlib visualizations from Excel or JSON data by running the visualization.py script. This data analysis workflow loads your dataset and creates plots suitable for reports using matplotlib.

Do I need numpy and matplotlib installed to run these data analysis scripts?▼

Yes, you need numpy and matplotlib installed in your Python environment to execute these data analysis scripts. These dependencies provide the core statistical computation and visualization functions required to process datasets and render plots.

What is the best way to clean and preprocess data before generating plots?▼

The best way to clean and preprocess data before plotting is to use Python scripts designed for data cleaning. This preprocessing prepares your raw CSV, Excel, or JSON datasets for accurate statistical analysis and visualization.

Does this data analysis approach work for large CSV files?▼

The data analysis approach uses Python with numpy to load and compute statistics on CSV files. While it handles standard dataset loading and visualization, performance with large CSV files depends on your local environment's memory and numpy's array processing limits.

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