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started","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":316,"value":"

\n \n

Insert new cells of any kind from the add cell menu.

\n\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":151,"value":"With the Add Cell menu open, you can start typing and a search input appears. Press `Return` as soon as you find a match to insert your new cell. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":149,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":175,"value":"This video demonstrates how to add a visualization snippet to your notebook using the Add Cell menu.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":154,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":241,"value":"To learn more, check out our collection on [notebook fundamentals](https://observablehq.com/collection/@observablehq/notebook-fundamentals).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":13,"value":"## Observable Plot\n\nThe [Observable Plot](https://observablehq.com/@observablehq/plot) JavaScript library lets you quickly build and customize data visualizations. As you saw in the previous example, code snippets are provided in the [Add 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","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":213,"value":"Here's an example of a scatterplot with linear regression, created with Observable Plot.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":191,"value":"Plot.plot({\n marks: [\n Plot.dot(penguins, {x: \"culmen_length_mm\", y: \"culmen_depth_mm\", stroke: \"species\"}), // try changing \"stroke\" to \"fill\"\n Plot.linearRegressionY(penguins, {x: \"culmen_length_mm\", y: \"culmen_depth_mm\", stroke: \"species\"})\n ],\n ariaLabel: \"Penguin culmen dimensions\",\n ariaDescription: \"Scatterplot of culmen length by culmen depth for three penguin species. Linear trendlines are added to each, revealing similar positive linear trends between culmen length and depth for chinstrap, gentoo and Adelie penguins.\"\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":83,"value":"We have many examples of Plot visualizations that you can reuse for your own analyses. Our interactive documentation covers all of the core concepts and functions you'll need to become a Plot expert. These links will help you get started:\n\n- [Observable Plot](https://observablehq.com/@observablehq/plot)\n- [Plot Cheatsheets](https://observablehq.com/@observablehq/plot-cheatsheets)\n- [Plot Examples](https://observablehq.com/collection/@observablehq/plot-examples)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":22,"value":"## Observable Inputs\n\n[Observable Inputs](https://observablehq.com/@observablehq/inputs) are lightweight interface components — buttons, sliders, dropdowns, tables, and the like — that help you explore data and build interactive displays. A number of inputs snippets are included in the cell menu. Generally, the process for adding interactivity to a visualization using inputs will take two steps:\n\nFirst, create the input, which will update a value based on user selection. For example, the Input slider below updates a value, stored as `myVal`:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":60,"value":"viewof myVal = Inputs.range([1, 10], {label: \"Amount\", step: 0.1, value: 3})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":63,"value":"myVal","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":65,"value":"Second, add interactivity to your visualization by linking one ore more elements to your Input value. In the Plot code below, dot radius (`r`) is linked to the `myVal` Inputs value.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":75,"value":"Plot.plot({\n marks: [\n Plot.dot(cars, {\n x: \"power (hp)\",\n y: \"economy (mpg)\",\n fill: \"steelblue\",\n opacity: 0.5, \n r: myVal\n })\n ],\n ariaLabel: \"Car horsepower and gas mileage\",\n ariaDescription: \"Scatterplot showing the inverse relationship between car horsepower and gas mileage.\"\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":110,"value":"Check out our [official docs on Observable Inputs](https://observablehq.com/@observablehq/inputs) to learn more. \n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":25,"value":"## Dashboards\n\nNow that you know how to create new cells, data visualizations and inputs, combine your knowledge of Observable to create a dashboard. Below is an example dashboard built with Observable Plot and Observable Inputs. One change you'll notice is that the visualizations are stored as functions, which allows for easier reuse. This is covered more thoroughly in our section on [reusing code](https://observablehq.com/d/71b6812e438d9f14?collection=@observablehq/enterprise-training-curriculum). ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":263,"value":"viewof selectSport = Inputs.select(d3.group(olympians.filter(d => d.weight > 0), d => d.sport), {label: \"Select a sport\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":270,"value":"\n

${weightHistogram(selectSport)}

${medalCountByNationality(selectSport)}

${Inputs.table(selectSport.map(d => ({Name: d.name, 'Date of Birth': d.date_of_birth, Nationality: d.nationality, Sex: d.sex, Height: d.height, Weight: d.weight })))}