Traffic Speed Dataset

Welcome to the Traffic Speed Dataset repository! This repository contains the necessary resources to complete a development exercise. Please read the following information to understand the purpose and structure of this repository.

Exercise Overview

The exercise focuses on applying your development skills to analyse and manipulate data related to traffic flow observations and sensor data. You will be working with two CSV files: traffic_speed.csv and sensors.csv.

Traffic Flow Observations

The traffic_speed.csv file contains observations of traffic flow, capturing various attributes such as ID, geographical coordinates, length, and speed. These observations serve as a dataset for analysis and manipulation.

Sensor Data

The sensors.csv file provides sensor-specific information, including unique identifiers and associated names. This data complements the traffic flow observations and may be used in the exercise to enhance the analysis.

Exercise Requirements

To complete the exercise, applicants are expected to demonstrate their proficiency in handling data, performing calculations or transformations, and deriving meaningful insights from the provided datasets. Further instructions and guidelines for the exercise will be provided separately to the applicants.

Repository Structure

The repository is organized as follows:

├── traffic_speed.csv             # Dataset containing traffic flow observations
├── sensors.csv                   # Dataset containing sensor-specific information
└── README.md                     # Repository overview and instructions (this file)
└── LICENSE.md                    # Repository open-source LICENSE (MIT)

Getting Started

1. Clone this repository to your local development environment.
2. Become familiar with the structure and content of the CSV files.
3. Read the exercise instructions provided separately.
4. Develop your solution, utilizing the datasets as necessary.
5. Submit your completed exercise as instructed.

Notes

• This repository only contains the datasets, the LICENSE and the README files. The exercise instructions will be shared separately.
• Feel free to explore the datasets and leverage the recommended programming languages and tools (and others you find suitable) for the exercise.