The LabEx Jupyter Interface provides an interactive Python environment based on Jupyter Notebook, perfect for data analysis, visualization, and machine learning tasks. Built on Ubuntu 22.04, it offers a familiar notebook-style interface for executing code cells and documenting your work.
The Jupyter environment is particularly useful for:
The Jupyter interface consists of several key components:
Code Cells:
Markdown Cells:
Create new cells:
Run cells:
Change cell type:
Data Analysis Sample
This is a sample data analysis lab that covers 100 exercises using the Pandas.
Working with data in Jupyter:
The output appears directly below the code cell, making it easy to iterate on your analysis.
Machine Learning Sample
This is a sample machine learning lab that compares different classifiers using Scikit-Learn.
Example of machine learning workflow:
How do I install additional Python packages?
You can install additional packages using pip in a code cell:
Remember that installations are temporary and will be reset when your session ends.
What are the essential keyboard shortcuts?
Important Jupyter shortcuts:
Cell Execution
Cell Operations
Cell Types
Other
Press H to view all shortcuts.
Why are educational notebooks different from regular lab content?
Educational notebooks in LabEx are different from regular lab content:
This format allows for a more interactive and self-paced learning experience.