Embedded Files
Tags: App Development, Data Visualization
Plotly
Pandas
Streamlit
Python
Jupyter Notebook
● GOAL
● GOAL
Develop a web application for exploring vehicle data and deploy it to a cloud service so that it is accessible to the public.
● OVERVIEW
● OVERVIEW
This project aims to provide users with an interactive dashboard for analyzing vehicle advertisement data. Users can filter the data based on criteria such as year, make/manufacturer, and condition, and visualize the filtered data using histograms and scatter plots.
The project started with the Exploratory Data Analysis (EDA) of the dataset as a crucial step for understanding the data, cleaning and preprocessing it, and identifying relevant patterns and trends.
The development of the app involved creating a Python script that integrates the relevant visualization components and interactivity settings. Upon completion and testing to ensure functionality, the application was deployed on Render, enabling easy access and interaction for end-users.
The dataset used in this project contains vehicle advertisement data in CSV format. The dataset includes information such as price, model, year, condition, type, transmission, and others.
Libraries Used
· Streamlit: For building the web application.
· Pandas: For data manipulation and analysis.
· Plotly Express: For creating interactive data visualizations.
● RESULTS
● RESULTS
A user-friendly and interactive web application where users can update the controls in the sidebar to get relevant information according to their needs. This app presents the following features:
➜ Select and filter data based on year, make/manufacturer, and condition.
➜ Toggle to show only vehicles with automatic transmission.
➜ Visualize the distribution of vehicle prices.
➜ Explore the relationship between days listed and price.
➜ Visualize the trends for fuel, type and color.
The application is accessible at the following URL:
For instructions on how to run locally or to see the code, please visit my GitHub.
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