EDA Report Generator

Pro v1.0.0 1 view

Generate comprehensive exploratory data analysis HTML reports with visualizations, statistics, and automated insights from CSV/Excel datasets.

What You Get

Automate 4-8 hours of manual data exploration into a professional HTML report with statistical summaries, distribution plots, correlation heatmaps, and key insights ready for stakeholder presentations.

The Problem

Data analysts spend hours manually exploring new datasets - calculating statistics, creating visualizations, checking data quality, and documenting findings. This repetitive work delays actual analysis and is error-prone when done manually.

The Solution

This skill runs a Python script that automatically performs comprehensive exploratory data analysis on any tabular dataset. It generates professional HTML reports with embedded visualizations including distribution plots, correlation heatmaps, missing data charts, and outlier detection. The report includes automated insights highlighting key patterns, data quality issues, and actionable recommendations.

How It Works

  1. 1 Provide dataset file (CSV, Excel, or TSV format)
  2. 2 Script analyzes dataset: statistics, correlations, missing data, outliers
  3. 3 Generates visualizations: distributions, heatmaps, categorical charts
  4. 4 Produces self-contained HTML report with embedded images
  5. 5 Summarizes key findings and recommendations for the user

What You'll Need

  • Dataset file in CSV, Excel (.xlsx, .xls), or TSV format
  • Python 3.7+ with pandas, numpy, matplotlib, seaborn, openpyxl

Get This Skill

Requires Pro subscription ($9/month)

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Examples

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Analyzing a 1,000-row sales dataset with revenue, units sold, profit margin, and discount rate columns. Demonstrates statistical summaries, outlier detection, correlation analysis, and actionable business recommendations.

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IoT Sensor Readings Analysis

Analyzing 6,000 sensor readings with temperature, humidity, vibration, and error count measurements. Demonstrates custom output filename, detection of non-normal distributions, and equipment monitoring recommendations.

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