quantopian /
qgrid
An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
79/100 healthRecently updatedActive repository
PythonApache-2.0
⑂ 418 forks◯ 181 issuesUpdated 6 days ago
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JupyterDataViz / repository
An interactive Jupyter Notebook project for visualizing mathematical concepts and data through dynamic visualizations
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An interactive Jupyter Notebook project for visualizing mathematical concepts and data through dynamic visualizations.
I developed a program in Jupyter Notebook based on Python language and its modules, such as Numpy,Matplotlib, ipywidget, and Ipython, as some machine learning modules such as sklearn to visualize the process of solution of theories mathematical data from beginners to advanced learners.
Because of the obstruction sciences and learning disorders, and as we know, there are a lot of limitations for women to learn because of gender discrimination, which is common in today's world. Education and learning have turned into a challenge for learners and teachers. So the goal is to make learning mathematics easier for both beginners and advanced learners.
Contributions are welcome! This project is specifically created for the PyCon event, and we encourage you to use it for learning and demonstration purposes. However, please refrain from making any changes to the core codebase during the event. If you have suggestions for improvements or new features, feel free to fork the repository and submit a pull request after the event.
This project is licensed under the MIT License. See the LICENSE file for more details.
For inquiries or issues, please contact:
This project was developed as part of a visualization data in Jupyter Notebook presentation in PyCon, aimed at enhancing understanding of mathematical concepts through visualization data using Jupyter Notebook
The mentioned program is a base step of an online platform that can visualize more mathematics data that is submitted in PyCon US 2025. As the project grows, we plan to include even more advanced features and educational resources. Stay connected with us! You can also check the for more information about our startup.
Selected from shared topics, language and repository description—not editorial ratings.
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All in all, I want to dedicate this program to women and girls who faced problems in education due to gender discrimination and were forbidden from learning and education. We hope that in addition to facilitating learning, it will also be a step toward solving the problem of these struggling girls and women
Special thanks to the PyCon community to create collaborative space for learning and sharing knowledge.
This project is designed to help visualize mathematical problems interactively using Jupyter Notebook. It utilizes several Python libraries to create visualizations for a variety of mathematical problems, making learning easier and more engaging.
This project utilizes the following Python libraries:
Numpy: For numerical operations
Matplotlib: To create static, charts and graphs.
ipywidgets: To enable user inputs and dynamic outputs.
Ipython
scikit-learn (sklearn): For machine learning algorithms and visualizing solutions of problems which has no absolute answers, such as the answers includes imperfect numbers.
this image is one of the outputs of the project that shows the Addition operation on the Horizontal line:
the below image image is another of the outputs of the project that shows the cube root operation in geometric shape:
the below image belongs to the another outputs of the project that shows the square root operation of the imperfect numbers by deep learning algorithms:
To run this project, ensure the following libraries are installed in your environment. You can install them via pip:
pip install numpy matplotlib ipywidgets ipython scikit-learn
## Installation
# To run this project locally, follow these steps:
#1. Clone the repository:
git clone https://github.com/JupyterDataVize/interactive-math-visualization.git
cd interactive-math-visualization
#2. Create and activate a virtual environment (optional but recommended):
python -m venv venv
### On Unix-based systems (Linux/macOS):
source venv/bin/activate
# On Windows:
venv\Scripts\activate
#3. Install the required dependencies:
pip install -r requirements.txt
#4. Start Jupyter Notebook
jupyter notebook
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