This repository contains a Jupyter Notebook that delves into the analysis of crime data in Los Angeles. The notebook titled "Analyzing Crime in LA" provides a comprehensive examination of crime statistics using publicly available data from the Los Angeles Police Department. Notebook Overview

Dataset Used: The analysis is based on a dataset available here, which includes detailed crime data from LA.
Data Exploration: The notebook starts with an exploration of the dataset, focusing on understanding the structure, content, and distribution of the data.
Data Cleaning and Preparation: The notebook demonstrates data cleaning and preparation techniques, ensuring the data is ready for analysis.
Statistical Analysis: Various statistical methods are applied to draw insights from the data, including trends and patterns in crime occurrences.
Visualizations: The notebook includes various visualizations to aid in the interpretation of the data and to present findings in an accessible format.

Link to Data

Since the data files are very large in size, you can download it from "https://app.datacamp.com/workspace/w/79085988-ab3c-46d9-aa8a-56487b1463a2/edit"

Objectives

To provide a data-driven understanding of crime trends in Los Angeles.
To showcase data cleaning, preparation, and analysis techniques using Python.
To demonstrate the use of statistical methods and data visualization in real-world data analysis.

Technologies Used

Python
Jupyter Notebooks
Libraries: Pandas, NumPy, Matplotlib, Seaborn, etc.

How to Run

Instructions for cloning the repository and running the notebook on your local machine.