![Jupyter Tutorial](/jupyter/images/jupyter-mini-logo.jpg)
- Jupyter Tutorial
- Jupyter - Home
- IPython
- IPython - Introduction
- IPython - Installation
- IPython - Getting Started
- Running & Editing Python Script
- IPython - History Command
- IPython - System Commands
- IPython - Command Line Options
- Dynamic Object Introspection
- IPython - IO Caching
- Setting IPython as Default Python Environment
- Importing Python Shell Code
- IPython - Embedding IPython
- IPython - Magic Commands
- Jupyter
- Project Jupyter - Overview
- Jupyter Notebook - Introduction
- Working With Jupyter Online
- Installation and Getting Started
- Jupyter Notebook - Dashboard
- Jupyter Notebook - User Interface
- Jupyter Notebook - Types of Cells
- Jupyter Notebook - Editing
- Jupyter Notebook - Markdown Cells
- Cell Magic Functions
- Jupyter Notebook - Plotting
- Converting Notebooks
- Jupyter Notebook - IPyWidgets
- QtConsole
- QtConsole - Getting Started
- QtConsole - Multiline Editing
- QtConsole - Inline Graphics
- QtConsole - Save to Html
- QtConsole - Multiple Consoles
- Connecting to Jupyter Notebook
- Using github and nbviewer
- JupyterLab
- JupyterLab - Overview
- Installation & Getting Started
- JupyterLab - Interface
- JupyterLab - Installing R Kernel
- Jupyter Resources
- Jupyter - Quick Guide
- Jupyter - Useful Resources
- Jupyter - Discussion
Jupyter Notebook - Plotting
IPython kernel of Jupyter notebook is able to display plots of code in input cells. It works seamlessly with matplotlib library. The inline option with the %matplotlib magic function renders the plot out cell even if show() function of plot object is not called. The show() function causes the figure to be displayed below in[] cell without out[] with number.
![Matplotlib Library](/jupyter/images/matplotlib_library.jpg)
Now, add plt.show() at the end and run the cell again to see the difference.
Note that the %matplotlib notebook magic renders interactive plot.
Just below the figure, you can find a tool bar to switch views, pan, zoom and download options.
![Matplotlib Library Toolbar](/jupyter/images/matplotlib_library_toolbar.jpg)
Importantly, if you modify the data underneath the plot, the display changes dynamically without drawing another plot.
In the above example, change the data sets of x and y in the cell below and plot the figure again, the figure above will get dynamically refreshed.
![Modify Data Underneath](/jupyter/images/modifying_data_underneath.jpg)
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