This project is an analysis of the crimes in NYPD over various factors. The data has been sourced from this Kaggle dataset and the corresponding Kaggle notebook has been also linked.
The dataset has not been cleaned before hand. It has been originally sourced from data.gov. It provides a list of Hate Crimes conducted by people in NYPD. It comprises of 13 features. Some of them are:
- Full Complaint ID: Provides a unique complaint ID
- Complaint Year Number: Year of complaint
- Month Number: Month of complaint
- Record Create Date: Date of record creation
- Complaint Precinct Code: Code of complaint precinct code
NYPD hate crime data analysis delves into uncovering trends in the data, both in terms of temporal patterns, like changes over time, and geospatial distribution, identifying areas with higher concentrations of hate crimes. Examining the details of the data, including offense types, associated law codes, bias motivations behind the crimes, and arrest trends, provides a deeper understanding of the nature of these incidents and how law enforcement responds.
Author: Manjit Baishya
Start Date: 06/03/2024
Project Status: Completed
End Date: 08/08/2024
Last Update: 08/03/2024
This project is dedicated to determine the key points responsible for crimes in NYPD. Analysis has been done through various measures - including categorical, temporal and spatial points. It has been accompanied with visualizations wherever necessary.
In this step, we import all required libraries for the analysis and also the source file itself.
In this step, we clean the data of any null values.
In this step, we make our data ready foir analysis - extracting only required features, creating new features from existing ones, fixing date-time formats, renaming columns and so on.
Here, we perform all sorts of temporal, categoriccal and geospatial analysis on the given data.
Here, we use Matplotlib and Seaborn to visualize our data.
Some conclusions drawn from the analysis on each instance.