Data Parsing and Processing

This repository contains a CSV file and a Jupyter notebook for parsing and processing the data contained in the file.

Data parsing

The python script, dataParsingToCsv.py, contains the data parsing from log-files to the final data set that is published via https://doi.org/10.3929/ethz-b-000556642

This script can be utilized for any traffic signal controller events, where the protocol needs to be specified with the variables defined in the header of the script.

Notebook

The Jupyter notebook, data_usage.ipynb, contains code for checking and processing the data from https://doi.org/10.3929/ethz-b-000556642. The notebook uses the pandas library to read the CSV file into a DataFrame, clean and preprocess the data, and perform some basic analysis.

The notebook is divided into the following sections:

1. Data Loading
2. Data Cleaning and Preprocessing
3. Sample Feature computation

Getting Started

To run the Jupyter notebook, you'll need to have Python 3 and the following libraries installed:

• pandas
• numpy
• datetime
• matplotlib
• requests
• zipfile
• io