skills.rest
wp931120
wp931120COMMUNITY
Explore all skills by this author →
WebsiteGitHub

data-analysis

Analyze CSV, Excel, JSON, and SQL datasets to generate profiles, statistics, visuals, and an HTML report.

55|7|Updated Mar 2, 2026
Search Tags:#profiling#visualization#statistics#data-analysis#analyze#report-generation
One-click install
npx skills add https://github.com/wp931120/tiny_agent --skill data-analysis-wp931120
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/wp931120/tiny_agent/tree/main/workspace/skills/data-analysis
Command: npx skills add https://github.com/wp931120/tiny_agent --skill data-analysis-wp931120

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Data analysts and teams struggle with extracting insights from raw data, performing quality checks, and generating repeatable reports.

Core Features & Use Cases

  • Data profiling, cleaning, visualization, and statistical analysis across CSV, Excel, JSON, and SQL datasets.
  • Automated reporting and reproducible workflows for data insights in business contexts.
  • Use Case: A data scientist quickly profiles a dataset, cleans it, visualizes distributions, and produces an HTML report.

Quick Start

Load a dataset (CSV/Excel/JSON) and run the analysis to generate a comprehensive report.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I automatically generate an HTML report from a CSV dataset?▼

To generate an HTML report from CSV data, load the dataset to compute statistics, visualize distributions, and assemble a final report. It uses pandas and matplotlib to process data and output a viewable HTML file.

What is data profiling and how does it work for Excel files?▼

Data profiling for Excel files involves loading the data to compute descriptive statistics and checking data quality. Using pandas, it extracts structural summaries and distributions to help you understand the dataset before deeper analysis.

Can I use pandas and seaborn to perform EDA on SQL data sources?▼

Yes, you can perform exploratory data analysis on SQL data sources. The workflow loads SQL data, computes statistics, and uses seaborn to create plots for visualizing distributions, enabling comprehensive data insights.

Does this data analysis workflow support JSON data formats?▼

Yes, this data analysis workflow supports JSON data formats. It loads JSON files alongside CSV, Excel, and SQL sources to generate data profiles, compute statistics, and produce visual plots.

What's the best way to clean raw data and compute statistics in Python?▼

The best way to clean raw data and compute statistics in Python is using pandas and numpy. This workflow loads your dataset, performs quality checks, calculates statistical distributions, and visualizes the results.

Do I need numpy and matplotlib installed to visualize data distributions?▼

Yes, you need numpy and matplotlib installed to visualize data distributions. These dependencies are required to load data, compute underlying statistics, and render the visual plots included in the final report.

Related Skills

Explore More Data & Analytics Skills→
louloulinlouloulin
19

data-analyst

Analyze raw datasets from CSV, Excel, and SQL sources with Python.

Community
Intermediate
weirdgmeweirdgme
4

platform-engineering

Design and implement scalable platform engineering patterns for internal developer platforms.

Community
Advanced
AradotsoAradotso
5

harvard-artifacts-etl-analytics

Extract, transform, and visualize Harvard Art Museums API data into SQL and Streamlit dashboards.

Official
Advanced
finsilabsfinsilabs
44

financial-analytics-dashboard

Create interactive financial KPI dashboards with drill-down analysis and threshold-based alerts.

Official
Intermediate