Update README.md

README.md

@@ -1,7 +1,48 @@
+# 2025 Homicide Trend Analysis
+
+![License](https://img.shields.io/badge/license-BSD--3--Clause--Clear-blue )
+![Python](https://img.shields.io/badge/python-3.8+-blue.svg )
+![Platform](https://img.shields.io/badge/platform-linux%20%7C%20macos%20%7C%20windows-lightgrey )
+
+📊 This project provides Python-based data visualization examples for analyzing homicide trends over time.
+
+Source: [HeyJackass.com](https://heyjackass.com )
+
+---
+
+## 📊 Overview
+
+This repository includes Python scripts to visualize homicide data using:
+- Bar graphs
+- Pie charts
+- DataFrames from `pandas`
+
+All visualizations are based on real-world data spanning from **2015 to 2024**.
+
 ---
-license: bsd-3-clause-clear
+
+## 📈 Sample Data
+
+| Year | Homicides |
+|------|-----------|
+| 2024 | 219       |
+| 2023 | 257       |
+| 2022 | 261       |
+| 2021 | 276       |
+| 2020 | 254       |
+| 2019 | 211       |
+| 2018 | 211       |
+| 2017 | 257       |
+| 2016 | 262       |
+| 2015 | 174       |
+
 ---
-Source: [Source: HeyJackass.com](https:///heyjackass.com)
+
+## 📊 Visualization Examples
+
+### 1. Bar Graph: Homicides Per Year
+
+```python
 import matplotlib.pyplot as plt
 import pandas as pd
 
@@ -25,63 +66,34 @@ plt.tight_layout()
 
 # Show the plot
 plt.show()
-
-# Python3 Examples for Bar/Pie Chart
-### 📊 Python Code to Create a Pie Chart Based on Year Distribution
-
-``python
-
+```
+### 2. Pie Chart: Distribution of Incidents by Year
+```python
 from datasets import load_dataset
 import matplotlib.pyplot as plt
 
 # Load the dataset
 ds = load_dataset("ajsbsd/hj")
 
-# Assuming the dataset is in the 'train' split and contains a 'Year' column
+# Count year occurrences
 year_counts = {}
-
-# Count occurrences per year
 for entry in ds['train']:
     year = entry.get('Year', None)
     if year is not None:
         year_counts[year] = year_counts.get(year, 0) + 1
 
-# Sort by year for consistent ordering
+# Sort years
 sorted_years = sorted(year_counts.items())
-
 years, counts = zip(*sorted_years)
 
 # Plot pie chart
 plt.figure(figsize=(8, 8))
 plt.pie(counts, labels=years, autopct='%1.1f%%', startangle=140)
 plt.title('Distribution of Incidents by Year')
-plt.axis('equal')  # Equal aspect ratio ensures the pie is circular
+plt.axis('equal')
 plt.show()
+```
 
-### 📊 Python Code to Create a Bar Graph of Homicides Per Year
-
-import matplotlib.pyplot as plt
-import pandas as pd
-
-# Data from your CSV
-data = {
-    'Year': [2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015],
-    'Homicides': [219, 257, 261, 276, 254, 211, 211, 257, 262, 174]
-}
-
-# Convert to DataFrame
-df = pd.DataFrame(data)
-
-# Plot bar graph
-plt.figure(figsize=(10, 6))
-plt.bar(df['Year'].astype(str), df['Homicides'], color='skyblue')
-plt.title('Homicides Per Year')
-plt.xlabel('Year')
-plt.ylabel('Number of Homicides')
-plt.xticks(rotation=45)
-plt.tight_layout()
-
-# Show the plot
-plt.show()
+BSD-3-Clause-Clear License
 
-```
+See LICENSE file for full text.