2f:T428,### Community support and engagement In addition to providing inspiration and reusable code, the Observable Community provides invaluable support while you learn and work. Here are several places to reach out for help, clarification and support: - [Observable Community Forum](https://talk.observablehq.com/) - [Observable Community Slack Workspace](https://join.slack.com/t/observable-community/shared_invite/zt-1icwex7uf-ovIAS0PcuJ~ZgBToSyUs8w) To stay up-to-date on new features, community highlights, and events, we also recommend: - Signing-up to receive the monthly [Observable Newsletter](https://observablehq.com/@observablehq/community-newsletter-signup) - Subscribing to the [Observable Blog](https://observablehq.com/@observablehq/blog-subscribe) - Bookmarking the [Observable Release Notes](https://observablehq.com/@observablehq/release-notes) - Following Observable on [Twitter](https://twitter.com/observablehq), [Mastodon](https://mastodon.social/@observablehq@vis.social), and [LinkedIn](https://www.linkedin.com/company/observable/mycompany/)30:T443,## JavaScript for data analysis At Observable, we believe that JavaScript is the future of data analysis. Our co-founder, Mike Bostock, wrote in [Towards Data Science](https://towardsdatascience.com/javascript-for-data-analysis-2e8e7dbf63a7): > _JavaScript is the richest medium we’ve ever had for communication, but thanks to the open nature of the web it’s also something more: a medium amenable to inspection and tinkering, for learning and collaboration._ > While JavaScript lacks some of the extensive data analysis and data science libraries you see in R, Python, or Julia, it has an overabundance in portability and convenience. This notebook you're reading is running in a browser, on your laptop, tablet or phone. You can see the code, edit the code, run the code from any of those devices. There is no set-up required, there is no requirements file to install. It simply _works_. As so many of our workflows move to the web, the ones that don't become more inconvenient. What we need are better tools in JavaScript for data analysis, and that's where Observable comes in. 31:T668,### Data analysis and visualization JavaScript has been a common language for data visualization for many years. While [D3](https://d3js.org/) has become the de facto framework for bespoke data visualization, used extensively by newsgroups and custom visualization applications, there are many great visualization frameworks built in JavaScript, such as [VegaLite](https://vega.github.io/vega-lite/), [Highcharts](https://www.highcharts.com/), and others. If you said "I believe JavaScript is the best language for data visualization," no one would bat an eye. At Observable, we believe that **data visualization _is_ data analysis**. Charts let us explore and understand patterns in data using visual encodings, rather than through mathematical models. They can reveal or clarify insights and questions that may otherwise be hidden within model assumptions and numerical outputs. And, visuals can be a more approachable and compelling way to communicate insights with stakeholders who are less familiar with interpreting model estimates. With tools to aggregate and summarize raw data directly in visualizations (for example, see [Plot group](https://observablehq.com/@observablehq/plot-group) for grouped transformations right in Observable Plot), Observable makes it straightforward to view patterns in raw **and** transformed data without the need for any intermediate steps. Combined with SQL cells and JavaScript libraries for data wrangling and analysis (which are easily loaded into notebooks using [require](https://observablehq.com/@observablehq/require)), Observable has the tools you need for many data analysis 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2d:{"title":"Learning Observable: Observable overview","cells":[{"id":0,"value":"# Learning Observable: Observable overview","pinned":false,"hidden":false,"mode":"md"},{"id":420,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":31,"value":"Observable streamlines the path from data to insights for individuals and teams. In Observable notebooks, users can quickly access their data, then combine text, analyses and outputs all in one place. Low-code features allow for fast data access, exploration, analysis and visualization. And, Observable is built for collaboration and sharing, so that more people can to explore, work with, and contribute to discussions around data.","pinned":false,"hidden":false,"mode":"md"},{"id":295,"value":"## The Notebook\n\nWhat you are reading now — this page or document — is an Observable notebook. Observable notebooks are __interactive, editable documents defined by code__. ","pinned":false,"hidden":false,"mode":"md"},{"id":45,"value":"All content in notebooks is made in cells. Within cells, you can author formatted text (in markdown) and code (JavaScript, SQL, HTML) to view right alongside customized data tables and visualizations. Then, quickly share your work with teammates and stakeholders to get everyone literally on the same page. \n","pinned":false,"hidden":false,"mode":"md"},{"id":282,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":279,"value":"A notebook is both a final product for presentation, and a blank canvas for data analysis, exploration, and creative tinkering. With zero software installation or environment management required, the barriers to get up-and-running in an Observable notebook are low for coders and non-coders alike. ","pinned":false,"hidden":false,"mode":"md"},{"id":211,"value":"---\n\n## Upload data, visualize and add interactivity in minutes\n\nAt Observable, we aim to help everyone — regardless of their previous experience with data, writing code, or building visualizations — get from data to insights with the least possible friction. In Observable notebooks, a wealth of features and code snippets for low-code data access, analysis and visualization exist at-your-fingertips.","pinned":false,"hidden":false,"mode":"md"},{"id":237,"value":"#### Upload data\n\nIn Observable, you can quickly attach local files, spreadsheets, connect to [APIs](https://observablehq.com/@observablehq/working-with-apis-remote-files?collection=@observablehq/working-with-data), and for Enterprise and Pro users, connect to [databases](https://observablehq.com/@observablehq/databases) or [cloud files](https://observablehq.com/@observablehq/cloud-files). Here is an example of uploading a CSV to an Observable notebook. ","pinned":false,"hidden":false,"mode":"md"},{"id":476,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":61,"value":"#### Visualize data with Plot\n\nThe [Observable Plot](https://observablehq.com/@observablehq/plot) library lets you quickly build and customize data visualizations. Code snippets are provided in the [cell menu](https://observablehq.com/@observablehq/adding-cells?collection=@observablehq/notebook-fundamentals) as a starting point for many common chart types to get you up-and-running quickly with your own visualizations by substituting your data and variables.","pinned":false,"hidden":false,"mode":"md"},{"id":447,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":343,"value":"#### Add interactivity\n\n[Observable Inputs](https://observablehq.com/@observablehq/inputs) are lightweight interface components (including buttons, sliders, dropdowns, tables, and text inputs) that help you explore data and build interactive displays. You can find them in the cell menu.\n\nOnce you've added an Input to your notebook, link the Input value to one or more elements of a chart to add interactivity. Since your Observable notebook is _on_ the web and in the language _of_ the web, your interactive chart is immediately shareable with collaborators.","pinned":false,"hidden":false,"mode":"md"},{"id":449,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":65,"value":"\n## Made for collaboration\nAt Observable, we believe that collaboration is key to doing responsible, innovative work with data. That's why we support several ways to collaborate with others in notebooks, whether it's co-editing a visualization or adding comments to an analysis. Here are a few ways that Observable is built with collaboration in mind.","pinned":false,"hidden":false,"mode":"md"},{"id":94,"value":"#### Multiplayer editing\nYou can invite others to join and edit notebooks with you. When another user is in the same notebook you're working in, you'll see their avatar at the top of the screen. You can click on their avatar to automatically follow them around the notebook.","pinned":false,"hidden":false,"mode":"md"},{"id":95,"value":"

\n","pinned":false,"hidden":false,"mode":"html"},{"id":103,"value":"#### Explore, comment and discuss — right in the notebook\n\nCollaborators and stakeholders don't require edit access to contribute to work in an Observable notebook. Anyone with view access can interact with notebooks using [inputs](https://observablehq.com/d/a6eb5a18f8943489?collection=@observablehq/enterprise-training-curriculum#cell-22), and can give feedback and participate in discussions using [comments](https://observablehq.com/@observablehq/comments). Comments get sent to the original editor so they can respond and resolve. ","pinned":false,"hidden":false,"mode":"md"},{"id":107,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":98,"value":"#### Version history\nWhether working solo or with collaborators in a notebook, it is useful to have a record of changes made. The [History](https://observablehq.com/@observablehq/history) pane (accessed by clicking the clock icon in the right margin) shows what changes were made to your notebook. You also have the option to revert back to an earlier version by choosing to \"Restore\" a version that you select. \n\nAutomated version history in Observable means that everyone working in the notebook can safely make edits and investigate changes.","pinned":false,"hidden":false,"mode":"md"},{"id":99,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":407,"value":"## The Observable Community\n\nThe community of Observable creators, learners, readers, and ambassadors is vast. Two major benefits of joining the [Observable community](https://observablehq.com/community) are: (1) access to a universe of published notebooks and examples that you can look to for inspiration and to reuse in your own work, and (2) direct support from community members when you have questions or need help.","pinned":false,"hidden":false,"mode":"md"},{"id":8,"value":"### Community contributions for inspiration and reuse \n\nThe Observable community is home to thousands of visualization and data analysis examples. Our [explore](https://observablehq.com/explore) page is your portal to our top content, rated by community likes and curated by the Observable team. Examples you find can be reused for your own analysis, either by importing the code itself or forking the notebook to your own workspace. \n","pinned":false,"hidden":false,"mode":"md"},{"id":9,"value":"When visualization are written as functions, it's easy to reuse for other datasets. The [D3 Charts](https://observablehq.com/collection/@d3/charts) collection features dozens of visualizations written as functions for the exact purpose of being reused.","pinned":false,"hidden":false,"mode":"md"},{"id":10,"value":"

\n","pinned":false,"hidden":false,"mode":"html"},{"id":11,"value":"The video above shows an example of an [import](https://observablehq.com/@observablehq/import?collection=@observablehq/notebook-fundamentals). Observable lets you quickly reuse content by importing named cells from other notebooks. Most often you'll import code and functions for reuse, but imports are versatile — you can also import charts, inputs, tables, or text from any named cell. This works with community notebooks, as well as private notebooks within a team.","pinned":false,"hidden":false,"mode":"md"},{"id":12,"value":"

\n","pinned":false,"hidden":false,"mode":"html"},{"id":14,"value":"With content from thousands of community-contributed Observable notebooks available for reuse, how can you focus your search to find what you need? Check out our guide for [searching on Observable](https://observablehq.com/@observablehq/searching-on-observable) and visit a couple of our favorite links:\n- Community examples\n - [Trending notebooks](https://observablehq.com/trending)\n - [Most liked (all time) notebooks](https://observablehq.com/top)\n- Visualization examples from the Observable team\n - [Plot examples](https://observablehq.com/collection/@observablehq/plot-examples)\n - [D3 charts](https://observablehq.com/collection/@d3/charts)\n - [Maps](https://observablehq.com/collection/@observablehq/maps)","pinned":false,"hidden":false,"mode":"md"},{"id":411,"value":"$2f","pinned":false,"hidden":false,"mode":"md"},{"id":142,"value":"$30","pinned":false,"hidden":false,"mode":"md"},{"id":197,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":527,"value":"newUsersCourseSmOverview1 = FileAttachment(\"new-users-course-sm-overview@1.png\").image({width: 200})","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}