amirjahantab / Dash_Data_Visualization

The CSV Data Visualization Tool is a web-based application built using Dash and Plotly.

CSV Data Visualization Tool

Overview

The CSV Data Visualization Tool is a web-based application built using Dash and Plotly. It allows users to upload a CSV file, preview the data, and generate various types of charts for analysis. The application provides an intuitive interface for selecting chart parameters such as the X and Y axes, color encoding, and chart type.

Features

• CSV File Upload: Users can upload a CSV file for visualization.
• Data Table Preview: Displays the first 5 rows of the uploaded dataset.
• Dynamic Axis Selection: Users can choose columns for the X and Y axes.
• Color Encoding: Allows users to apply color differentiation based on a selected column.
• Multiple Chart Types:
  • Scatter Plot
  • Line Chart
  • Bar Chart
  • Histogram (with bin selection)
  • Box Plot
  • Violin Plot
  • Heatmap
  • Sunburst Chart
• Interactive Graphs: Generated plots are interactive and dynamically update based on user inputs.

How to Use

1. Upload a CSV File

   • Click on the Upload CSV button.
   • Select a CSV file from your computer.

2. Preview Data

   • The first 5 rows of the dataset will be displayed in a table.

3. Select Plot Parameters

   • Choose a column for the X-axis.
   • Select one or more columns for the Y-axis.
   • Optionally, choose a Color encoding.
   • Pick a Chart Type from the dropdown menu.

4. Generate Chart

   • Click the Generate Chart button to visualize the data.
   • If using a histogram, specify the number of bins.

Installation & Running the Application

Prerequisites

Ensure you have Python installed along with the required libraries:

pip install dash plotly pandas

Running the Application

Save the script as app.py and execute it using:

python app.py

The application will start a local server, and you can access it in your browser at http://127.0.0.1:8050/.

File Processing & Data Handling

• The application reads the uploaded CSV file using Pandas.
• The first 5 rows are displayed in a Dash DataTable.
• Axis and color dropdown options are dynamically populated based on the dataset.
• Charts are generated using Plotly Express, making them interactive and responsive.

Customization

You can modify the application to add:

• Additional chart types.
• More customization options (e.g., themes, styling).
• Advanced filtering and transformation capabilities.

Conclusion

This tool is a powerful and flexible way to quickly visualize CSV datasets. It is particularly useful for data analysis, exploratory data visualization, and presentation of insights.