kernel. You can also request this connection data by running the %connect_info magic. This will print the same ID information as well as the content of the JSON data structure it contains. You can then, for keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples. Code cells A code cell allows you to edit and write new code, with full syntax highlighting are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also: Rich Output example

for getting the information necessary to connect to the kernel. You can also request this connection data by running the %connect_info magic [http://ipython.org/ipython- doc/dev/interactive/tutorial.html#magics-explained] html#magics-explained]. This will print the same ID information as well as the content of the JSON data structure it contains. You can then, for example, manually start a Qt console connected to the same keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples [http://nbviewer.jupyter.org/github/jupyter/notebook/tree/master/docs/source/examples/Notebook/]

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic [https://ipython.readthedocs.io/en/stable/interactive/tutorial keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples [http://nbviewer.jupyter.org/github/jupyter/notebook/tree/master/docs/source/examples/Notebook/] are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also Rich Output [https://nbviewer

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic [https://ipython.readthedocs.io/en/stable/interactive/tutorial keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples [http://nbviewer.jupyter.org/github/jupyter/notebook/tree/master/docs/source/examples/Notebook/] are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also Rich Output [https://nbviewer

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic, which will print the same ID information along with other details keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples. 1.4.1 Code cells A code cell allows you to edit and write new code, with full syntax are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also: Rich Output example

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic, which will print the same ID information along with other details keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples. 1.4.1 Code cells A code cell allows you to edit and write new code, with full syntax are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also: Rich Output example

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic, which will print the same ID information along with other details keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples. 1.4.1 Code cells A code cell allows you to edit and write new code, with full syntax are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also: Rich Output example

use Jupyter in a web browser, some people are understandably concerned about using it with sensitive data. However, if you followed the standard install instructions, Jupyter is actually running on your own http://localhost: or http://127.0.0.1:, it’s your computer acting as the server. Jupyter doesn’t send your data anywhere else—and as it’s open source, other people can check that we’re being honest about this. might run the server for you, for instance. If you want to work with sensitive data in those cases, talk to your IT or data protection staff about it. We aim to ensure that other pages in your browser

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic [https://ipython.readthedocs.io/en/stable/interactive/tutorial keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples [http://nbviewer.jupyter.org/github/jupyter/notebook/tree/master/docs/source/examples/Notebook/] are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also Rich Output [https://nbviewer

to connect to the kernel. If the notebook uses the IPython kernel, you can also see this connection data by running the %connect_info magic, which will print the same ID information along with other details keyboard shortcuts. For more information on the different things you can do in a notebook, see the collection of examples. 1.4.1 Code cells A code cell allows you to edit and write new code, with full syntax are also possible, including matplotlib figures and HTML tables (as used, for example, in the pandas data analysis package). This is known as IPython’s rich display capability. See also: Rich Output example