This is a Python-based implementation of a Bubble Chart visualization. It uses matplotlib
, pandas
, and numpy
to generate a bubble chart based on the number of talks by country and year.
- Dynamic Bubble Chart: Visualizes the number of talks per country and year.
In this demo, the chart shows example data with randomly assigned years, countries, and talk counts.
Before running the script, make sure you have the following software and packages installed:
To install Python, download the latest version from the official Python website. If you're unsure whether you already have Python installed, you can check by running the following command in your terminal:
python --version
- Git You'll also need Git installed to clone the repository. You can verify if Git is installed by running:
git --version
- Required Python packages:
matplotlib
numpy
pandas
Install these packages using the following command:
pip install matplotlib numpy pandas
Alternatively, you can install all dependencies at once using the requirements.txt
file (if it's included in the repository):
pip install -r requirements.txt
The requirements.txt
file contains the following lines:
matplotlib
numpy
pandas
-
Open Terminal: On Windows, open the terminal by searching for CMD or PowerShell in the Start menu.
-
Clone the repository:
git clone https://github.com/Omid2831/ChartBubbleGraph.git
- Navigate into the project directory:
cd ChartBubbleGraph
- Run the Python script to generate the bubble chart:
python bubblechart.py
🚀 download the file and open it:
bubblechart.exe
Enjoy! 🎉 If you need further assistance or have other questions, please ask! 😊
📂 ChartBubbleGraph ├── bubblechart.py # Main Python script for generating the bubble chart ├── 📂 img │ └── BubbleGraph_Chart.png # Screenshot of the bubble chart ├── requirements.txt # List of required libraries ├── README.md # Documentation file for the project ├── bubblechart.zip # This is the run application IRL └── demo_video.mp4 # Demo video showing the chart generation process
I just wanted to let you know that this project is open for further collaboration. If you have ideas on improving the visualization, adding new features, or any suggestions, feel free to fork the repository or submit a pull request. Let’s make this project even better together! 🚀