Data Analyst

v1.0.0

SQL, pandas, and statistical analysis expertise for data exploration and insights. Use when: analyzing data, writing SQL queries, using pandas, performing st...

0· 18·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for 2072932870wh-ui/data-analyst-new.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Data Analyst" (2072932870wh-ui/data-analyst-new) from ClawHub.
Skill page: https://clawhub.ai/2072932870wh-ui/data-analyst-new
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Canonical install target

openclaw skills install 2072932870wh-ui/data-analyst-new

ClawHub CLI

Package manager switcher

npx clawhub@latest install data-analyst-new
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
The name/description (SQL, pandas, statistics) matches the SKILL.md instructions. No unrelated binaries, credentials, or config paths are requested; everything requested is consistent with a pure analysis assistant.
Instruction Scope
SKILL.md contains only guidance about producing SQL queries, pandas code, and statistical interpretation. It does not instruct the agent to read system files, environment variables, or transmit data to external endpoints. It is high-level and scoped to producing analysis artifacts.
Install Mechanism
No install spec or code files are present; this is instruction-only and does not write code to disk or download external packages, representing the lowest install risk.
Credentials
The skill declares no required environment variables, credentials, or config paths. There is no disproportionate request for secrets or unrelated access.
Persistence & Privilege
always is false and the skill is user-invocable (normal). The skill does not request permanent presence or modify other skills or system-wide settings.
Assessment
This skill is a safe, instruction-only helper that will produce SQL and pandas code and statistical explanations but cannot execute anything or access your files by itself. Before running any generated code against your systems: (1) review queries and code for correctness and safety (e.g., DELETE/UPDATE statements, expensive joins), (2) do not paste sensitive credentials or full datasets into the chat — redact personal data or use representative/sanitized samples, (3) validate performance considerations on a test database to avoid heavy operations, and (4) treat code suggestions as starting points and test them in a controlled environment.

Like a lobster shell, security has layers — review code before you run it.

latestvk97etz72y0y7cnra95cw2j3d0s85fyx6
18downloads
0stars
1versions
Updated 3h ago
v1.0.0
MIT-0

Data Analyst

You are an expert data analyst with expertise in SQL, Python (pandas), and statistical analysis.

When to Apply

Use this skill when:

  • Writing SQL queries for data extraction
  • Analyzing datasets with pandas
  • Performing statistical analysis
  • Creating data transformations
  • Identifying data patterns and insights
  • Data cleaning and preparation

Core Competencies

SQL

  • Complex queries with JOINs, subqueries, CTEs
  • Window functions and aggregations
  • Query optimization
  • Database design understanding

pandas

  • Data manipulation and transformation
  • Grouping, filtering, pivoting
  • Time series analysis
  • Handling missing data

Statistics

  • Descriptive statistics
  • Hypothesis testing
  • Correlation analysis
  • Basic predictive modeling

Output Format

Provide SQL queries and pandas code with:

  • Clear comments
  • Example results
  • Performance considerations
  • Interpretation of findings

Created for data analysis and SQL/pandas workflows

Comments

Loading comments...