A Plotly-based visualization library for road accident data analysis.
Project description
🚗 RoadIntel – Road Accident Data Visualization Library
RoadIntel is a Python library built on Plotly Express for interactive visualization of road accident datasets.
It helps researchers, analysts, and students uncover meaningful patterns in road safety data through clean, reusable visualization functions.
📦 Installation
pip install roadintel
🧠 Features
- Create rich, interactive charts using Plotly Express
- Analyze accident data by state, vehicle type, road condition, and more
- Automatically generate human-readable insights
- Optimized for dark-themed dashboards
- Modular and ready for integration in Dash or Jupyter apps
📊 Example Usage
import pandas as pd
from roadintel import charts
# Load dataset
df = pd.read_csv('road_accidents.csv')
# Example 1: Create India Map
fig = charts.create_india_map_chart(df, geojson_data, 'plotly_dark')
fig.show()
# Example 2: Accident Trend
charts.create_monthly_trend_chart(df, 'plotly_dark').show()
📈 Available Charts
| Function | Description |
|---|---|
create_india_map_chart |
Choropleth map of state-wise accidents |
create_monthly_trend_chart |
Monthly accident trend (line chart) |
create_state_bar_chart |
Top 10 states by accident count |
create_severity_donut_chart |
Accident severity donut chart |
create_road_type_chart |
Severity comparison across road types |
create_vehicle_bar_chart |
Top 5 vehicle types involved |
create_alcohol_pie_chart |
Alcohol involvement in accidents |
create_weather_light_chart |
Weather & lighting impact |
create_age_casualty_bar_chart |
Casualties by driver age group |
calculating_insights |
Generates 5 textual insights from dataset |
🧾 License
Licensed under the MIT License.
👨💻 Author
Anubhav Shukla
M.Sc. Data Science | Central University of Haryana
📧 Email: anubhavshukla870@gmail.com
🌐 GitHub: https://github.com/mr-robot369
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