Welcome to the Brazil Traffic Data repository. This repository is a valuable resource for anyone interested in analyzing and understanding traffic patterns in various regions of Brazil. Whether you're a data scientist, researcher, or enthusiast, this dataset provides a rich source of information for your projects and analysis.
- Introduction
- Data Sources
- Data Description
- Data Fields
- Usage
- How to Get Started
- Contributing
- License
- Contact Me
Traffic data plays a vital role in urban planning, transportation management, and safety assessment. This repository aims to provide a comprehensive collection of traffic data from different parts of Brazil. The dataset is suitable for a wide range of applications, including data analysis, research, and decision-making.
The dataset in this repository has been sourced from various reliable providers, which may include government agencies, transportation authorities, and open data platforms. Please check the specific data source for more information on the origin and update frequency of the data.
The dataset encompasses a broad range of traffic-related information, including traffic congestion, accidents, vehicle counts, road conditions, and more. The data is organized in a structured format for ease of use and analysis.
The dataset includes the following key fields:
- Immobilized bus
- Broken Truck
- Vehicle excess
- Accident victim
- Running over
- Fire vehicles
- Occurrence involving freight
- Incident involving dangerous freight
- Lack of electricity
- Fire
- Point of flooding
- Manifestations
- Defect in the network of trolleybuses
- Tree on the road
- Semaphore off
- Intermittent Semaphore
- Slowness in traffic (%)
For a more detailed description of each field, please refer to the data source or documentation.
Feel free to use this dataset for a variety of purposes, such as data analysis, visualization, machine learning, research, and more. You can clone or download the repository and access the data in various formats, depending on your preferences.
If you use this dataset in your work, please consider citing the appropriate data sources or providing a citation as needed based on your usage.
- Clone the Repository: Start by cloning this repository to your local machine using the following command:
1. Clone the Repository:
git clone https://github.com/Mujtaba-12390/brazil-traffic-cause-data.git
2. Install Dependencies: Ensure you have Jupyter Notebook installed. If not, you can install it using:
pip install jupyter
3. Launch Jupyter Notebook:
jupyter notebook
4. New way to kick-start How to kick-start a data science project
Old way 🥴
- import libraries you'll need
- dealing with import-related errors
- search the correct import statement on Google
(repeat the cycle, depending on the project's complexity)
New way 🤓
- pip install pyforest
PyForet gives you an unfair advantage to jumpstart any data science projects With just one line of code, you can import the 40 most commonly used Python libraries Libraries are loaded on-demand, consuming memory space only when a specific function or method is invoked This saves you time and ensures that your code doesn't slow down due to unnecessary imports I can't believe I wasted so much time hunting down imports statements!
5. Install all Python libraries: You must install Python and its libraries. If not, you can install it using:
pip install pyforest
6. Explore the Analysis: Dive into the analysis by opening the Brazil Traffic Data Visualization.ipynb file in your preferred Python environment.
We welcome contributions from the community. If you have additional data sources, updates, or improvements to the dataset, please open an issue or submit a pull request. Your contributions and collaboration are highly valued.
This dataset is provided under an open-source license (if applicable). Please review the specific license details in the dataset folder for more information on usage and distribution.
If you have questions, or suggestions, or want to discuss this project further, please feel free to reach out. I welcome collaboration and feedback.
- Email: Email Address
- GitHub: GitHub Profile
- LinkedIn: My LinkedIn Profile
- Medium Articles: Medium Profile I look forward to connecting with you and exploring the fascinating world of data together.
Thank you for using the Brazil Traffic Data repository. We hope this dataset proves to be a valuable resource for your projects and analysis. If you have any questions or suggestions, please don't hesitate to get in touch.