Welcome to Norton's Data World
- View the data visualization report of group project at (https://app.luminpdf.com/viewer/5ecc6da18124240012ae0885)
- Tableau Dashboard for Philadelphia House Price Data Visualization
- Language: Python
- Data Pipeline and Automation: Apache Airflow
- Data Cleaning: Pandas
- Data Storage: MySQL
- Data Transformation (Join Table): Apache Spark (SQL) - Cluster @ Databricks
- Data Visualization: Jupyter Notebook: Matplotlib -> (heatmap), seaborn -> (pairplot, boxplot), plotly -> (3D plot), Tableau Public-> dashboard
- Language: Python
- Apache Airflow
- Pandas
- Matplotlib
- MySQL / PostgreSQL
- Jupyter Notebook Report
- AWS (S3, EC2, RDS)
- Language: R
- NoSQL Database: MongoDB
- Visualization Tools: ggplot2, plotly -> (3D plot)
- In this project (LEGO dataset), I applied both R-Studio and jupyter notebook to import and export data from MongoDB, then used ggplot2 and plotly to demonstrate the analytical reslut with data visualization, respectively.
- Language: Python
- Class
- Unit Testing
- Object Oriented Programming
- Terminal
- In this project, I applied unit-test tool to verify the classes and modules in the Black Jack Application.
In this repo, Apache Kafka is used for tracking the route of the designed buslines. When we run the three different busdata producers python files, you will see three different moving spots in the map.
Environment & tools:
- Python 3.70 (pykafka, flask, JSON)
- Apache Kafka
- Javascript (Leaflet.JS)
- html
Thank you for visiting. More projects are coming