{"id":297602,"date":"2018-08-20T11:22:40","date_gmt":"2018-08-20T18:22:40","guid":{"rendered":"http:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=297602"},"modified":"2021-08-03T00:40:36","modified_gmt":"2021-08-03T07:40:36","slug":"python-workflows-jupyterlab","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/api-python\/mapping\/python-workflows-jupyterlab","title":{"rendered":"Optimize Your Python Workflows Using JupyterLab"},"author":8282,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,22941,37511],"tags":[164102,210202,24341,26521,220392],"industry":[],"product":[36841,36601],"class_list":["post-297602","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-mapping","category-sharing-collaboration","tag-jupyter-notebook","tag-jupyterlab","tag-python","tag-visualization","tag-whats-new-september-2018","product-api-python","product-developers"],"acf":{"short_description":"The ArcGIS API for Python's seamless integration with JupyterLab allows you to work with spatial data in a modern, easy-to-use IDE.","flexible_content":[{"acf_fc_layout":"content","content":"

You may know that the ArcGIS API for Python<\/a> provides simple and efficient tools for performing GIS analysis, visualizing your spatial data<\/a>, and administrating your web GIS\u2014but did you also know that the ArcGIS API for Python integrates smoothly with the larger open-source Python ecosystem? These non-Esri software packages are free to use, and many can provide customization options and new features that enhance your Python development experience. There are many software packages worth exploring\u2014but perhaps the most useful of these software offerings is Project Jupyter<\/a>.<\/p>\n

Jupyter’s flagship software offering is the Jupyter Notebook. Jupyter Notebooks are web documents that let you\u00a0run Python code in an interactive manner, annotate your code with maps\/charts\/text\/equations, and share your results with others seamlessly. Using Python in Jupyter Notebooks has become the preferred workflow for data scientists and GIS analysts in many use cases: data cleaning and transformation, statistical modeling, data visualization, machine learning, and more.<\/p>\n

The ArcGIS API for Python is designed to work extremely well with the Jupyter Notebook format. Historically, this was done by running the jupyter notebook<\/code> command to launch the ‘Classic Notebook’ server. While we will continue to support this Classic Notebook experience, v1.5.0 of the Python API also supports the JupyterLab experience. JupyterLab interacts with the same Jupyter Notebook format<\/strong>, but offers a robust file explorer, a more intuitive user interface, support for interacting with other file types, etc. This makes JupyterLab more of an IDE<\/a> when compared to the Classic Notebook server.<\/p>\n

In this blog post, we will walk through some of the benefits of using JupyterLab in your development and data science workflows. The below gif shows what this workflow might look like: data is read in from a local csv file, Python code is run in the Jupyter Notebook that transforms that csv data, and the result is visualized on a map.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":297922,"id":297922,"title":"JupyterLab Workflow","filename":"jlab_workflow.gif","filesize":1934297,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/api-python\/mapping\/python-workflows-jupyterlab\/jlab_workflow","alt":"","author":"8282","description":"An example data science workflow in JupyterLab: data is read in from a local csv file, Python code is ran in the Jupyter Notebook that transforms that csv data, and the result is visualized on a map.","caption":"","name":"jlab_workflow","status":"inherit","uploaded_to":297602,"date":"2018-08-13 19:50:10","modified":"2018-08-20 13:08:19","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1611,"height":811,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","thumbnail-width":213,"thumbnail-height":107,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","medium-width":464,"medium-height":234,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","medium_large-width":768,"medium_large-height":387,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","large-width":1611,"large-height":811,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","1536x1536-width":1536,"1536x1536-height":773,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","2048x2048-width":1611,"2048x2048-height":811,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","card_image-width":826,"card_image-height":416,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/jlab_workflow.gif","wide_image-width":1611,"wide_image-height":811}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Installation<\/h2>\n

To start using the ArcGIS API for Python with JupyterLab, follow these installation steps:<\/p>\n

1) Install >=v1.5.0 of the ArcGIS API for Python by following this installation guide<\/a>.<\/p>\n

2) Run the following 2 commands:<\/p>\n

<\/code>jupyter labextension install @jupyter-widgets\/jupyterlab-manager<\/code><\/p>\n

<\/code>jupyter labextension install arcgis-map-ipywidget@1.5.0<\/code><\/code><\/p>\n