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Analyzing Crime Trends: Merging and Exploring Bedfordshire and Essex Police Data
This dataset includes police data from Bedfordshire and Essex, spanning 2019 to June 30th, 2022.
Overview
The dataset consists of police data from the Bedfordshire and Essex police forces, covering a period from 2019 to June 30th, 2022. The data provides a detailed monthly overview of reported crimes and incidents within these regions. This README file provides a summary of the dataset, including column descriptions and key points to consider during analysis.
Click this link to directly access the report: Analyzing Crime Trends
Directory Structure
This directory contains the following files:
bedfordshire_data.csv: Crime data from Bedfordshire police force.essex_data.csv: Crime data from Essex police force.README.md: This README file.scripts/: Directory for scripts used to analyze the data.
Bedfordshire Data Set Column Descriptions
Unnamed: 0: An index or identifier for each row in the dataset.Crime ID: Unique identifier for each reported crime.Report Date: The date when the crime was reported.Location: Description or address of the crime location.Latitude: The latitude coordinates of the crime location.Longitude: The longitude coordinates of the crime location.LSOA code: Code representing the Lower Layer Super Output Area of the crime location.LSOA name: Name of the Lower Layer Super Output Area of the crime location.Crime Type: The type or category of the crime reported.Last Outcome Category: The last known outcome or status of the reported crime.Context: Additional contextual information related to the crime, if available.
Note: The columns Crime ID, Last Outcome Category, and Context may have missing values, which should be considered during analysis.
Essex Data Set Column Descriptions
Unnamed: 0: An index or identifier for each row in the dataset.Crime ID: Unique identifier for each reported crime.Month: The month in which the crime was reported.Reported by: The organization or authority responsible for reporting the crime.Falls within: The jurisdiction or area within which the crime falls.Longitude: The longitude coordinates of the crime location.Latitude: The latitude coordinates of the crime location.Location: Description or address of the crime location.LSOA code: Code representing the Lower Layer Super Output Area of the crime location.LSOA name: Name of the Lower Layer Super Output Area of the crime location.Crime type: The type or category of the crime reported.Last outcome category: The last known outcome or status of the reported crime.Context: Additional contextual information related to the crime, if available.
Note: Some columns, such as Crime ID, Longitude, Latitude, LSOA code, LSOA name, Last outcome category, and Context, may have missing values, which should be considered during analysis.
How to Use This Data
Exploring the Data
- Load the datasets into a data analysis environment like R or Python.
- Merge the datasets if necessary to perform comparative analysis between the two regions.
- Clean the data by handling missing values and standardizing column names for consistency.
Analyzing Trends
- Analyze crime trends over time to identify any patterns or significant changes.
- Compare the crime types and outcomes between Bedfordshire and Essex.
- Examine the geographical distribution of crimes using the latitude and longitude coordinates.
Visualizations
- Create visualizations such as line charts, bar charts, and maps to illustrate crime trends and distributions.
- Use tools like ggplot2 in R or Matplotlib in Python for visualization.
Reporting
- Summarize findings in reports or presentations.
- Highlight key insights and recommendations based on the analysis.
Source
The dataset used in this project can be found at the following link: Analyzing Crime Trends: Merging and Exploring Bedfordshire and Essex Police Data
Report for this project can be found at the following link: Analyzing Crime Trends: Merging and Exploring Bedfordshire and Essex Police Data
