// Generates production-ready analysis code in Python, R, SQL. Invoke when user wants reusable code for data analysis, ML, or visualization.
全面的AB测试分析工具，支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果，提供统计显著性检验和深度洞察。
Perform multi-touch attribution analysis using Markov chains, Shapley values, and custom attribution models. Use when you need to analyze marketing channel effectiveness, calculate conversion attribution, optimize marketing budgets, or understand customer journey paths. Supports channel transition analysis, ROI calculation, and marketing optimization insights with Chinese language support.
Analyze text content using both traditional NLP and LLM-enhanced methods. Extract sentiment, topics, keywords, and insights from various content types including social media posts, articles, reviews, and video content. Use when working with text analysis, sentiment detection, topic modeling, or content optimization.
通用的 6 阶段数据分析助手：数据质量→探索性分析→假设生成→可视化→代码生成→综合报告。提供完整的方法论和模板！
自动化数据探索和可视化工具，提供从数据加载到专业报告生成的完整EDA解决方案。支持多种图表类型、智能数据诊断、建模评估和HTML报告生成。适用于医疗、金融、电商等领域的数据分析项目。
Performs exploratory data analysis, statistical analysis, and pattern discovery. Invoke when user wants to analyze data, find patterns, statistical testing, or get deep insights.
| name | code-generator |
| description | Generates production-ready analysis code in Python, R, SQL. Invoke when user wants reusable code for data analysis, ML, or visualization. |
Expert software engineer specializing in generating production-ready data analysis code.
Invoke this skill when user:
用户可以指定代码类型：
适用场景: 数据预处理
生成代码:
适用场景: 统计分析
生成代码:
适用场景: 图表创建
生成代码:
适用场景: 预测建模
生成代码:
根据用户需求生成特定代码
import pandas as pd
import numpy as np
def process_data(df):
"""数据处理函数"""
# 处理逻辑
return processed_df
library(tidyverse)
process_data <- function(df) {
# 处理逻辑
}
.py.R.sql./generated_code/Work with other skills: