data-analyst
shubhamsaboo/awesome-llm-apps
SQL, pandas, and statistical analysis expertise for data exploration and insights.
What is data-analyst?
Expert data analyst skill providing SQL query writing, pandas data manipulation, and statistical analysis capabilities. Use when analyzing datasets, writing database queries, performing statistical tests, or exploring data patterns.
- Write complex SQL queries with JOINs, subqueries, CTEs, window functions, and aggregations
- Manipulate and transform datasets using pandas with grouping, filtering, pivoting, and time series analysis
- Perform descriptive statistics, hypothesis testing, and correlation analysis
- Clean and prepare data, handle missing values, and identify data patterns
- Optimize database queries and provide performance considerations
- Interpret statistical findings and provide actionable insights
How to install data-analyst
npx skills add https://github.com/shubhamsaboo/awesome-llm-apps --skill data-analystHow to use data-analyst
- 1.Describe your data analysis task or provide sample data structure
- 2.Request SQL queries, pandas code, or statistical analysis as needed
- 3.Review provided code with comments and example results
- 4.Apply the code to your dataset and iterate based on findings
- 5.Use performance considerations and interpretations to refine your analysis
Use cases
- Extract and analyze customer behavior data using SQL and pandas to identify trends
- Perform hypothesis testing on A/B test results to determine statistical significance
- Clean messy datasets and create data transformations for downstream analysis
- Analyze time series data to forecast trends or detect anomalies
- Optimize slow database queries affecting reporting pipelines
- Data analysts and scientists
- Business intelligence professionals
- SQL and Python developers working with data
- Researchers performing statistical analysis
- Anyone exploring or analyzing datasets
data-analyst FAQ
The skill provides SQL expertise applicable to standard relational databases. Specific database syntax (PostgreSQL, MySQL, SQL Server, etc.) can be adapted based on your system.
Yes, the skill includes data cleaning and preparation expertise using pandas, including handling missing data, removing duplicates, and transforming formats.
The skill covers basic predictive modeling and statistical analysis. For advanced machine learning, additional specialized skills may be needed.
The skill provides query optimization techniques and performance considerations for both SQL and pandas to handle larger datasets efficiently.
Full instructions (SKILL.md)
Source of truth, from shubhamsaboo/awesome-llm-apps.
name: data-analyst description: | SQL, pandas, and statistical analysis expertise for data exploration and insights. Use when: analyzing data, writing SQL queries, using pandas, performing statistical analysis, or when user mentions data analysis, SQL, pandas, statistics, or needs help exploring datasets. license: MIT metadata: author: awesome-llm-apps version: "1.0.0"
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
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