td-smoothing
OfficialSmooth signals, reduce noise.
Authorteradata-labs
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the challenge of noisy or irregular time series data by applying advanced signal smoothing and noise reduction techniques, ensuring cleaner data for analysis and modeling.
Core Features & Use Cases
- Signal Smoothing: Applies various smoothing algorithms to reduce high-frequency noise.
- Noise Reduction: Filters out unwanted variations to reveal underlying trends.
- Data Regularization: Prepares data for downstream analysis by making it more consistent.
- Use Case: Analyze IoT sensor data from thousands of devices to smooth out erratic readings and identify genuine patterns in equipment performance.
Quick Start
Analyze time series table: my_database.sensor_data with timestamp column and value columns.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: td-smoothing Download link: https://github.com/teradata-labs/claude-cookbooks/archive/main.zip#td-smoothing Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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