{"metadata":{"image":[],"title":"","description":""},"api":{"url":"","auth":"required","settings":"","params":[],"results":{"codes":[]}},"next":{"description":"","pages":[]},"title":"JupyterLab quick reference","type":"basic","slug":"editor-quick-reference","excerpt":"","body":"JupyterLab is one of the two available editors in Data Studio, where the actual code editing and execution takes place. This document provides a brief description of the JupyterLab environment and its commonly used commands.\n\n## The interface\n\nWhen you open JupyterLab, you see the **Launcher** screen that allows you to select one of the available options:\n[block:image]\n{\n \"images\": [\n {\n \"image\": [\n \"https://files.readme.io/cc6bcba-jupyterlab-quick-reference-1.png\",\n \"jupyterlab-quick-reference-1.png\",\n 659,\n 592,\n \"#f4f4f4\"\n ]\n }\n ]\n}\n[/block]\n\nChoose one of the options in the **Notebook** section, depending on the programming language you want to use. Available programming languages and their versions might differ depending on the selected [environment setup](doc:about-libraries-in-a-data-cruncher-analysis).\n\nThe editor screen showing a notebook and a terminal console open at the same time will look like this:\n[block:image]\n{\n \"images\": [\n {\n \"image\": [\n \"https://files.readme.io/2fd0c06-jupyterlab-quick-reference-2.png\",\n \"jupyterlab-quick-reference-2.png\",\n 1440,\n 682,\n \"#f0eee9\"\n ]\n }\n ]\n}\n[/block]\n\nThe main elements of the JupyterLab editor are:\n1. **Notebook** - The document that contains the code and outputs of an interactive analysis, as well as additional markdown or raw text that accompanies the code, but is not meant for execution.\n2. **Cell** - A single section of a notebook where you can enter code, markdown or raw text.\n3. **Toolbar** - Allows you to quickly perform the most common actions within a notebook, by clicking on an icon.\n4. **Left-hand panel** containing tabs that allow you to access some (or all) of the following functionalities:\n * View and manage files that are created or added (uploaded or downloaded) within the analysis itself, including the Jupyter notebooks (`.ipynb` files). \n * Manage kernel sessions that are currently running. One kernel session corresponds to one open notebook.\n * View and use additional commands in the editor. To execute a command, click it in the list.\n * Add notebook tags and metadata.\n * Manage active tabs.\n5. **Terminal console** - This is a JupyterLab Terminal extension equivalent to a Linux shell.\n6. **Code Console** - Enables you to run code interactively in a kernel.\n7. **Back button** - Allows you to navigate back from the editor to the analysis details page.\n8. **Analysis control and help options**:\n * **Stop** - Allows you to stop the analysis directly from the editor.\n * **Help** - Displays a dropdown containing a link to Data Studio documentation and the link to the feedback form through which you can contact our Support Team.\n\nFor more details about the visual interface, see the [official JupyterLab documentation](https://jupyterlab.readthedocs.io/en/stable/user/interface.html).\n\n## Commonly used text commands\n\nBesides execution of Python, R or Julia code, you can also run the following types of commands directly in your notebook:\n\n* **Magic commands** - a set of predefined functions that you can call with a command line style syntax. Magic commands can begin with a single `%` symbol, in which case they take the rest of the line as an argument. If you prefix a magic command with a double `%` symbol (`%%`), it will take the rest of the cell as its argument. Learn more about [magic commands](http://ipython.readthedocs.io/en/stable/interactive/magics.html) or type `%magic` in a blank cell and execute it.\n* **Linux shell commands** - You can also run any system shell command by prefixing it with an exclamation mark (`!`), for example `!ls`. You can even combine shell commands with the rest of the code in your notebook, for example:\n[block:code]\n{\n \"codes\": [\n {\n \"code\": \"myfiles = !ls\",\n \"language\": \"python\"\n }\n ]\n}\n[/block]\n This line of code will assign the list of files returned by the `ls` command to the `myfiles` variable.\n\nFind out more about functionalities related to [text commands](http://ipython.readthedocs.io/en/stable/interactive/tutorial.html).","updates":[],"order":2,"isReference":false,"hidden":false,"sync_unique":"","link_url":"","link_external":false,"_id":"58f5d56702c293230028f0a1","parentDoc":null,"project":"55faf11ba62ba1170021a9a7","createdAt":"2017-04-18T08:59:19.555Z","category":{"sync":{"isSync":false,"url":""},"pages":[],"title":"DATA STUDIO","slug":"data-cruncher","order":42,"from_sync":false,"reference":false,"_id":"58f5d52d7891630f00fe4e77","project":"55faf11ba62ba1170021a9a7","version":"55faf11ba62ba1170021a9aa","__v":1,"createdAt":"2017-04-18T08:58:21.978Z"},"githubsync":"","__v":0,"user":"5767bc73bb15f40e00a28777","version":{"version":"1.0","version_clean":"1.0.0","codename":"","is_stable":true,"is_beta":true,"is_hidden":false,"is_deprecated":false,"categories":["55faf11ca62ba1170021a9ab","55faf8f4d0e22017005b8272","55faf91aa62ba1170021a9b5","55faf929a8a7770d00c2c0bd","55faf932a8a7770d00c2c0bf","55faf94b17b9d00d00969f47","55faf958d0e22017005b8274","55faf95fa8a7770d00c2c0c0","55faf96917b9d00d00969f48","55faf970a8a7770d00c2c0c1","55faf98c825d5f19001fa3a6","55faf99aa62ba1170021a9b8","55faf99fa62ba1170021a9b9","55faf9aa17b9d00d00969f49","55faf9b6a8a7770d00c2c0c3","55faf9bda62ba1170021a9ba","5604570090ee490d00440551","5637e8b2fbe1c50d008cb078","5649bb624fa1460d00780add","5671974d1b6b730d008b4823","5671979d60c8e70d006c9760","568e8eef70ca1f0d0035808e","56d0a2081ecc471500f1795e","56d4a0adde40c70b00823ea3","56d96b03dd90610b00270849","56fbb83d8f21c817002af880","573c811bee2b3b2200422be1","576bc92afb62dd20001cda85","5771811e27a5c20e00030dcd","5785191af3a10c0e009b75b0","57bdf84d5d48411900cd8dc0","57ff5c5dc135231700aed806","5804caf792398f0f00e77521","58458b4fba4f1c0f009692bb","586d3c287c6b5b2300c05055","58ef66d88646742f009a0216","58f5d52d7891630f00fe4e77","59a555bccdbd85001bfb1442","5a2a81f688574d001e9934f5","5b080c8d7833b20003ddbb6f","5c222bed4bc358002f21459a","5c22412594a2a5005cc9e919","5c41ae1c33592700190a291e","5c8a525e2ba7b2003f9b153c","5cbf14d58c79c700ef2b502e","5db6f03a6e187c006f667fa4","5f894c7d3b0894006477ca01","6176d5bf8f59c6001038c2f7"],"_id":"55faf11ba62ba1170021a9aa","releaseDate":"2015-09-17T16:58:03.490Z","createdAt":"2015-09-17T16:58:03.490Z","project":"55faf11ba62ba1170021a9a7","__v":48}}