Posted on No Comments on Monday – December 4, 2023.

Monday – December 4, 2023.

So, for the final project, I have decided to work on this dataset: https://data.boston.gov/dataset/crime-incident-reports-august-2015-to-date-source-new-system

These are the steps for analysis, I will be following for our analysis:

  1. Variety of Crimes in Different Areas:
    1. Group the data by street and analyze the count of unique types of crimes on each street.
    2. Visualize the results using bar charts or other appropriate plots.
  2. Most Common Crime Types, Time, and Day on Specific Streets:
    1. Filter the data for each street and analyze the most common crime types, days, and hours.
    2. Use bar charts, pie charts, or heatmaps for visualization.
  3. Rise in Certain Crimes in Specific Areas:
    1. Perform a temporal analysis to identify trends in specific types of crimes over time.
    2. Use line charts or other time series visualizations.
  4. Common Crimes Rising Over Time:
    1. Analyze the overall trend of common crimes over the entire dataset.
    2. Consider creating a time series plot to visualize the changes.
  5. Common Neighborhoods with Crime:
    1. Group the data by neighborhood to identify areas with higher crime rates.
    2. Visualize the results using maps or bar charts.
  6. Time Analysis:
    1. Analyze the data based on time factors such as month, day of the week, and hour.
    2. Identify patterns and trends over time using appropriate visualizations.
  7. Map Chart Visualization:
    1. Utilize the latitude and longitude information to create a map chart.
    2. Color-code or size-code data points based on the frequency of crimes in each location.
  8. Correlation Analysis:
    1. Use statistical methods to identify correlations between different variables (e.g., time, day, month) and types of crimes.
    2. Visualize correlations using correlation matrices or scatter plots.
  9. Shooting Data Analysis:
    1. Analyze shooting data separately, identifying patterns, and correlations with other variables.
    2. Visualize shooting incidents on a map and explore temporal patterns.
  10. Predictive Models:
    1. Depending on the nature of your dataset, you can build predictive models to forecast future crime incidents or classify incidents into different categories.
    2. Common algorithms include decision trees, random forests, or neural networks.