What are some recommended extensions for data science?

What are some recommended extensions for data science?

There are several great extensions for data science, especially if you're using tools like Jupyter Notebook or VS Code. For Jupyter, I recommend 'JupyterLab', 'nbextensions', and 'Voila'. For VS Code, 'Python', 'Jupyter', and 'Pandas' extensions are very useful.

Can you tell me more about the Jupyter nbextensions?

Sure! Jupyter nbextensions is a collection of community-contributed extensions that enhance the functionality of Jupyter Notebooks. They provide features like code folding, table of contents, and variable inspector, making it easier to manage and navigate your notebooks.

Are there any extensions specifically for data visualization?

Yes, for data visualization, you might want to check out 'Plotly', 'Bokeh', and 'Matplotlib' extensions. They integrate well with Jupyter and allow for interactive and static visualizations.

What about extensions for machine learning?

For machine learning, 'TensorFlow', 'Keras', and 'Scikit-learn' are essential libraries. You can also use 'MLflow' for tracking experiments and 'DVC' for version control of your data and models.