Refer to this blog article Five tips to get you started with Jupyter notebooks to get further understanding on patterns to follow while using Jupyter notebooks. Accessing Help > Keyboard shortcuts from a running notebook will bring up a help dialog as shown below.Īmong the shortcuts, ctrl + shift + P or cmd + shift + P on a mac is particularly useful as it brings up a command palette into which you can type what you wish to do and execute it. As you get used to this new interface, you can enhance your productivity by learning a few keyboard shortcuts. You can get a tour of the notebook interface from the Help -> User Interface Tour menu. In the screenshot above, note the icons of currently running notebooks are green in color. To do so, from the Notebook Dashboard page, click on the 'New' button and select a Python kernel of choice as shown in the image below.Īlternately, you can create new notebooks from the 'File' menu of a running notebook. In addition to running the sample notebooks, you can create new notebooks for your projects. Jupyter Notebooks, interactive documents that comprise code, rich-text, and visualizations, are widely used and loved by data scientists and machine learning practitioners. When a cell is executing the cell number turns to an asterisk (*) and the circle next to the kernal name (Python 3 in the gif above) turns solid. The animation below shows these steps in action. Alternately, you can run a cell using the keyboard shortcut shift + enter. You can run each cell by selecting it and clicking on the 'run cell' button. This opens the notebook in a new tab or window. In the Jupyter Notebook, you can navigate the folder structure and click on a sample notebook. The page you see in this image is called the Notebook Dashboard. The command starts Jupyter Notebook and opens it in your default web browser as shown below. In the example above, the samples have been downloaded and extracted into c:\code directory. If you are running a sample notebook for the API, you need to 'cd' into the directory where you downloaded the samples. For more information on the benefits of using environments and how to create and manage them, refer to this official documentation page. If you installed the ArcGIS API for Python in a conda environment other than root (which is the default), you need to activate that environment before starting the Jupyter Notebook. Below is a screen shot of how it would appear if you were running the command from Windows command prompt. Similarly if you are running a Mac or Linux OS, this could be your terminal. If you are running a Windows OS, this could be your command prompt or PowerShell window. Once conda and the ArcGIS API for Python is installed, you can start the Jupyter Notebook environment by typing the following command in your terminal. Starting the Jupyter Notebook environment Refer to the official Jupyter documentation and this quick start guide for further details. This section provides a quick introduction to the Jupyter Notebook environment where you can run Python code in an interactive manner and visualize the output as maps and charts.
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