DataPilot__Data-Analyst-Agent

🥈Silver

DataPilot is an intelligent data analysis assistant that leverages Generative AI and Python to process datasets, answer business questions, generate insights, and create visual reports, streamlining the data analysis process for businesses.

800Updated 1w ago

Intermediate15 minutes to implementanalytics

Saves ~135 min per use

Quick InstallView Source

claude install ShreshtaSutar/DataPilot__Data-Analyst-Agent

Works with:

ChatGPTGitHub Copilot

Overview

About This Skill

Use Cases

Automating data processing tasks

Generating business insights from large datasets

Creating visual reports for presentations

Answering specific business questions with data

Best For

RevOpsGrowth

Setup & Installation

Quick Install

Terminal

claude install ShreshtaSutar/DataPilot__Data-Analyst-Agent

Alternative Install (Git Clone)

git clone https://github.com/ShreshtaSutar/DataPilot__Data-Analyst-Agent

Requirements

Claude Code or compatible AI agent
Works with: ChatGPT, GitHub Copilot

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I have a dataset about [SPECIFIC BUSINESS AREA] that I need to analyze. The dataset is in [FILE FORMAT] and contains [DESCRIBE DATA]. I need to understand [SPECIFIC BUSINESS QUESTIONS]. Can you help me analyze this data, generate insights, and create a visual report?

Example Output

After analyzing the provided dataset on customer purchasing behavior, I've identified several key insights: 1) Customers who purchase Product A are 3 times more likely to buy Product B within 30 days. 2) The average purchase frequency has increased by 15% in the last quarter, particularly among customers in the 25-34 age demographic. 3) Customers who engage with our email marketing campaigns spend 20% more on average. Based on these insights, I recommend: A) Implementing a targeted email campaign for Product B to customers who recently purchased Product A. B) Developing marketing strategies specifically tailored to the 25-34 age group. C) Analyzing the content of high-performing emails to identify best practices. I've created a visual report with these findings, including charts showing purchase frequency trends and customer segmentation analysis.