Welcome to the Interactive Data Visualization with Bokeh project! This project showcases a collection of interactive visualizations created using the Bokeh library, which is known for its ability to produce high-quality, interactive plots and dashboards in Python.
This repository contains various examples and tutorials on how to leverage Bokeh to create interactive data visualizations. Bokeh is a powerful library for building visually appealing and interactive plots that are well-suited for data exploration and presentation.
- 📈 Line Plots: Create line charts to visualize data trends over time.
- 🔵 Scatter Plots: Plot data points to reveal relationships and distributions.
- 🔶 Hexbin Plots: Visualize density of data points using hexagonal bins.
- 🖼️ Image & Image RGBA Plots: Generate grayscale and color images from data matrices.
- 🔍 Interactive Charts: Add interactivity to charts with tools such as hover and zoom.
- 📊 Bokeh Datasets: Work with built-in datasets to create insightful visualizations.
- Bokeh: A Python library for creating interactive plots and dashboards.
- NumPy: A library for numerical computations and data manipulation.
To use the code in this repository, you need to install the required libraries. You can do this using pip:
pip install bokeh numpy You can clone this repository to your local machine using the following command:
git clone https://github.com/yyigitturan/Interactive-Data-Visualization-With-Bokeh.gitAfter cloning the repository and installing the required libraries, you can explore the various examples and tutorials provided in the project. Each example demonstrates a different aspect of Bokeh's capabilities for creating interactive visualizations.