DataBytes-Organisation/Intelligent-IoT-Data-Management
May 2025 – May 2025
1 Month active
Languages Used
Python
Technical Skills
Correlation AnalysisData AnalysisJupyter NotebookMatplotlibNumPyPandas
Jainy13
PROFILE
Jainy13
Developed a Sensor Data Correlation Analysis Notebook for the DataBytes-Organisation/Intelligent-IoT-Data-Management repository, enabling analysts to examine inter-sensor relationships in industrial IoT datasets. The solution was implemented in Python using Jupyter Notebook, leveraging Pandas and Seaborn for data loading, preprocessing, and visualization. It featured time-series plots and a pairplot to reveal correlations across multiple sensors, along with a lag-detection function to identify maximum correlation between specific sensor pairs. Comprehensive documentation accompanied the notebook, supporting reproducibility and ease of use. The work focused on delivering actionable analytics for IIoT operations, with an emphasis on clarity and extensibility in both code and documentation.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
348
Activity Months1
Your Network
12 peopleShared Repositories
12
Work History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for DataBytes-Organisation/Intelligent-IoT-Data-Management: Delivered a Sensor Data Correlation Analysis Notebook enabling analysts to explore inter-sensor relationships through data loading, preprocessing, time-series visualizations, a pairplot of sensor correlations, and a lag-detection feature to identify maximum correlation between s1 and s2. Documentation and notebook were added, supporting cross-sensor insights and actionable analytics for IIoT operations.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for DataBytes-Organisation/Intelligent-IoT-Data-Management: Delivered a Sensor Data Correlation Analysis Notebook enabling analysts to explore inter-sensor relationships through data loading, preprocessing, time-series visualizations, a pairplot of sensor correlations, and a lag-detection feature to identify maximum correlation between s1 and s2. Documentation and notebook were added, supporting cross-sensor insights and actionable analytics for IIoT operations.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Correlation AnalysisData AnalysisJupyter NotebookMatplotlibNumPyPandasSeaborn
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline