zealptl / cs-460

CS 460

NYC Crime Analysis and Prediction

Group Members

• Greg Kimatov
• Zeal Patel
• Mehedi Shohag

Repository Structure

• data
  • NYC_crime.csv: Raw data from Kaggle. Uploaded to google drive. Find here
  • NYC_data_clean.csv: The cleaned crime data. Uploaded to google drive. Find here
  • NYC_unemployment.csv: The cleaned NYC unemployment data. Uploaded to google drive. Find here
  • gdp.csv: The cleaned year over year NYC gdp data. Uploaded to google drive. Find here
  • data_dictionary.csv: The data dictionary for cleaned dataset.
• code
  • Data_cleaning.py: Cleans NYC_crime.csv
  • 460_Data_Visualization.ipynb: Includes descriptive graphs and charts
  • 460_Model.ipynb: Includes 3 linear regression models

Contributions After Preliminary Analysis

• Greg Kimatov:
  • Model: Effect of annual GDP percent change in NYC on crime
  • Blog Post Sections: "Introduction", "Supplementary datasets", "Predicting the future crime rate based on annual GDP percent change in NYC", "Final Conclusions"
• Mehedi Shohag:
  • Model: Effect of unemployment in NYC on crime
  • Blog Post: "Number of offense type in NYC by borough", "Predicting the future crime rate based on unemployment", "Future Work"
• Zeal Patel:
  • Model: Year vs Arrests in NYC per 100k people (crime rate)
  • Blog Post: "Primary Dataset", "Visualizing the data", "Predicting the future yearly crime rae"
  • Presentation slides