R Program to Python Conversion
Budget: $10 – $30 USD
Convert R Algorithm to Python
I have a specialized R script that implements an advanced event detection algorithm for time-series data analysis. The code is fully functional and includes comprehensive debugging capabilities. I need this converted to Python while preserving all functionality and logic.
Project Scope:
Convert R event detection algorithm to Python
Maintain all original algorithm parameters and thresholds
Preserve the detailed event detection logic and state management
Keep the comprehensive debugging and logging functionality
Ensure CSV input/output compatibility
Technical Requirements:
Use pandas for data handling and CSV operations
Implement equivalent debugging output and logging
Maintain the same parameter structure and defaults
Preserve all conditional logic and edge case handling
Include comprehensive error handling and validation
Generate equivalent debug logs and summary statistics
Deliverables:
Complete Python script with identical algorithm behavior
Detailed documentation explaining the algorithm steps
Debug logging functionality matching the R version
Test validation showing equivalent results on sample data
Requirements.txt for all dependencies
Usage examples and parameter tuning guide
Ideal Candidate:
Strong experience in both R and Python data analysis
Understanding of signal processing and event detection algorithms
Experience with time-series analysis and anomaly detection
Familiarity with scientific computing libraries (pandas, numpy)
Attention to detail for preserving complex algorithm logic
The original R code includes extensive debugging output and handles various edge cases. Looking for a faithful Python conversion that maintains the algorithm's precision and reliability while leveraging Python's data science ecosystem.
I have a specialized R script that implements an advanced event detection algorithm for time-series data analysis. The code is fully functional and includes comprehensive debugging capabilities. I need this converted to Python while preserving all functionality and logic.
Project Scope:
Convert R event detection algorithm to Python
Maintain all original algorithm parameters and thresholds
Preserve the detailed event detection logic and state management
Keep the comprehensive debugging and logging functionality
Ensure CSV input/output compatibility
Technical Requirements:
Use pandas for data handling and CSV operations
Implement equivalent debugging output and logging
Maintain the same parameter structure and defaults
Preserve all conditional logic and edge case handling
Include comprehensive error handling and validation
Generate equivalent debug logs and summary statistics
Deliverables:
Complete Python script with identical algorithm behavior
Detailed documentation explaining the algorithm steps
Debug logging functionality matching the R version
Test validation showing equivalent results on sample data
Requirements.txt for all dependencies
Usage examples and parameter tuning guide
Ideal Candidate:
Strong experience in both R and Python data analysis
Understanding of signal processing and event detection algorithms
Experience with time-series analysis and anomaly detection
Familiarity with scientific computing libraries (pandas, numpy)
Attention to detail for preserving complex algorithm logic
The original R code includes extensive debugging output and handles various edge cases. Looking for a faithful Python conversion that maintains the algorithm's precision and reliability while leveraging Python's data science ecosystem.