dataset-onboarding-graph-preprocess

Convert raw phone network data files into structured graph tables.

Updated Jun 2, 2026

Search Tags:#data conversion #graph data #data preprocessing #field mapping #phone network

Ready to run

npx skills add https://github.com/bettercallfan/deerflow --skill dataset-onboarding-graph-preprocess

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dataset-onboarding-graph-preprocess
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/phone-network-analysis/dataset-onboarding-graph-preprocess
Command: npx skills add https://github.com/bettercallfan/deerflow --skill dataset-onboarding-graph-preprocess

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, python, and includes scripts (resource) components.

What problem does it solve?

This Skill preprocesses phone network data by converting raw data files into structured, usable graph format for advanced analysis.

Core Features & Use Cases

Data Conversion: Converts CSV, Excel, JSON, or Parquet files into structured user nodes, call edges, and device edges.
Field Mapping & Data Quality: Automatically identifies and maps fields, checks data quality, and generates diagnostic reports.
Use Case: Ideal for preparing data for further analysis in the phone network domain, including risk assessment and anomaly detection.

Quick Start

Run the following command to preprocess the uploaded phone network data: dataset-onboarding-graph-preprocess --input-dir /path/to/data --dataset-name [dataset_name]

Frequently Asked Questions about dataset-onboarding-graph-preprocess

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I preprocess raw phone network data into a graph format?▼

Preprocess raw phone network data into a structured graph format by converting input files into structured user nodes, call edges, and device edges. The tool automatically handles field mapping, performs data quality checks, and generates diagnostic reports for downstream analysis.

Can I convert CSV and Excel files for phone network graph data preprocessing?▼

Yes, you can convert CSV, Excel, JSON, and Parquet files for phone network graph data preprocessing. The tool reads these raw input formats and transforms them into structured graph tables for advanced analysis.

What is the best way to map fields and check data quality for phone network data?▼

The best way to map fields and check data quality for phone network data is using an automated preprocessing tool. This Skill automatically identifies and maps fields, validates data quality, and outputs diagnostic reports for structured graph tables.

Does phone network graph preprocessing require Python and pandas?▼

Yes, phone network graph preprocessing requires Python and pandas. These dependencies are necessary to execute the data conversion, field mapping, and quality checks for generating structured graph tables.

Why do I need to preprocess phone network data for risk assessment?▼

Preprocessing phone network data for risk assessment converts raw files into structured user nodes, call edges, and device edges. This structured graph format is required to perform advanced anomaly detection and risk analysis.