- Papers and Scripts
- SAS script importing Excel dataset for regression analysis
- Dashboard for Wild Concessions - Projections
- Python script processing data using Pandas
- SAS script importing and inspecting dataset for analysis
- Powering NHL Strategies with Data Analytics
- Python script processing data using Pandas
- Extract and Identify Errors
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Presentation on ETL and salary model building for hockey analytics
- Jupyter Notebook for data transformation and ETL
- Regression & Correlation in NHL Team Salaries
- Python script processing data using Pandas
- Document detailing data preparation challenges in SAS
- Python script processing data using Pandas
- Extract from NHL API - play types
- Model for Player Analysis
- Output from NHL API
- Calculate NHL percentages mapped to rink
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Output from NHL API
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Document related to decision support systems
- Extract from NHL API - teams
- Extract from NHL API - schedule
- Python script interacting with an API
- Document discussing Tableau and data visualization techniques
- Python script interacting with an API
- Python script interacting with an API
- Python script interacting with an API
- Python script interacting with an API
- Python script interacting with an API
- Python script processing data using Pandas
- Python script interacting with an API
- Manageing the NHL Salary Cap
- Analysis of Goal Scoring NHL New View
- Dictionary
- Jupyter Notebook for data transformation and ETL
- Python script processing data using Pandas
- Python script processing data using Pandas
- Mismatch name output using fuzzy logic
- Python script filtering and analyzing YTD revenue data
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Jupyter Notebook for data transformation and ETL
- Python script processing data using Pandas
- Python script processing data using Pandas
- Jupyter Notebook for data transformation and ETL
- Python script processing data using Pandas
- Python script processing data using Pandas
- Analysis of Goal Scoring NHL
- Python script processing data using Pandas
- Python script processing data using Pandas
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- Python script processing data using Pandas
- SQL script performing bulk data insert
- Python script processing data using Pandas
- Spreadsheet containing bad data for data cleaning and preprocessing
- Jupyter Notebook for data transformation and ETL
- Python script processing data using Pandas
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Final paper summarizing Tableau project and ETL process
- Jupyter Notebook for data transformation and ETL
- Jupyter Notebook for data transformation and ETL
- Python script processing data using Pandas
