Analyzing EV charging patterns using a dataset from Kaggle, providing insights through an interactive web application built with Flask.
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This project analyzes electric vehicle (EV) charging patterns using a dataset from Kaggle. The goal is to uncover trends and patterns in EV charging behaviors, such as time of day, station usage, and user segmentation, and provide insights through an interactive web application built with Flask.
A. Leaderboard Model Kendaraan Terbaik
This feature provides a leaderboard showcasing the most efficient EV models based on factors such as charging patterns, energy consumption, and more. Users can identify the most efficient models tailored to their needs.
B. Statistik Penggunaan dan Pengisian
Displays detailed usage and charging data for each vehicle model, helping users understand the performance of EV models under various conditions and charging behaviors.
C. Visualisasi Interaktif
The results are presented in tables and interactive graphs, allowing users to easily view insights and trends in EV charging behavior.
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- Python 3.x
- pip
pip install flask
pip install kagglehub
pip install pandas
pip install matplotlib
pip install seaborn
pip install scikit-learn