2b:null 2c:["$","title",null,{"children":"Advanced Data Viz Course | Ssen Kim | Observable"}] 31:T6b2,## Slides: Why visualize, (un)common chart types, Grammar of Graphics [These slides](https://docs.google.com/presentation/d/1XblTzWpLv_N6NwzJ7ITF2YmReYmG2kD7v9P58yf1rt4/edit?usp=sharing) cover the following topics: - Why visualize data?
_The purpose of visualization is insight, not pictures(Card, Mackinlay, Shneiderman, Readings in information Visualization,1999)_. - Common and uncommon chart types, their pros and cons
_**Common Chart **Line chart, bar charts, scatterplots, pie charts,_
🌱PROS:Familiar, most people will understand them|Easy to make in a variety of different tools | Work across many differenet datasets, not usually sensitive to the content |
🌱CONS:Boring and forgettable(especially in presentations | Not specific to the data or task | Easy to create based on superficial understanding of the data
_**UnCommon Chart **Sankey diagrams, connected scatterplots, power diagrams,..._
🌱PROS:Can be more specific to the data and/or task than common charts | Attention-catching and memorable |Design process can be part of deep data exploration(설계 프로세스는 심층 데이터 탐색의 일부가 될 수 있습니다.)
🌱CONS:Unfamiliar, audience might not be able to understand | More difficult to make(often need special tools)&Special tool이 필요할 수도, special 작업방법이 필요할수도 있다 | Often specific to data and only work kfor specific datasets - _The Grammar of Graphics_ by Leland Wilkinson, as well as grammars for graphics/charts in general32:[{"id":"af55e9c0cb745b133ce357d9f7d355ea32ffa275149ca29cca15dbc35112f20b13230e5b877358097e896700d2ecb14d529bff9b64e5b9bc04d290cf42c88a22","href":"https://static.observableusercontent.com/files/af55e9c0cb745b133ce357d9f7d355ea32ffa275149ca29cca15dbc35112f20b13230e5b877358097e896700d2ecb14d529bff9b64e5b9bc04d290cf42c88a22","name":"image.png","type":"image/png","lastModified":1686804650367.315,"size":169874},{"id":"af55e9c0cb745b133ce357d9f7d355ea32ffa275149ca29cca15dbc35112f20b13230e5b877358097e896700d2ecb14d529bff9b64e5b9bc04d290cf42c88a22","href":"https://static.observableusercontent.com/files/af55e9c0cb745b133ce357d9f7d355ea32ffa275149ca29cca15dbc35112f20b13230e5b877358097e896700d2ecb14d529bff9b64e5b9bc04d290cf42c88a22","name":"image@1.png","type":"image/png","lastModified":1686804666862.586,"size":169874},{"id":"76d1c7ab1322945ff09e749fb3c37e4bbe2a8e34522808aeeedbb2d82cf96c92778d0e71612fc6c19b0b7baf0dee02a95e3b5ab398f145d066e136ba22bb9c95","href":"https://static.observableusercontent.com/files/76d1c7ab1322945ff09e749fb3c37e4bbe2a8e34522808aeeedbb2d82cf96c92778d0e71612fc6c19b0b7baf0dee02a95e3b5ab398f145d066e136ba22bb9c95","name":"STUDIOSAENA_LOGO.png","type":"image/png","lastModified":1688461451467.815,"size":9867},{"id":"298d7a1276b5217972dd2141c54b6a499af936ae7d4005c7cb48fbc91ab871f343c6153175ac44d9ed8c6a679bc547fd42142e3377a65815c3f546e2f09d1f8a","href":"https://static.observableusercontent.com/files/298d7a1276b5217972dd2141c54b6a499af936ae7d4005c7cb48fbc91ab871f343c6153175ac44d9ed8c6a679bc547fd42142e3377a65815c3f546e2f09d1f8a","name":"image@2.png","type":"image/png","lastModified":1688462714999.851,"size":120323},{"id":"298d7a1276b5217972dd2141c54b6a499af936ae7d4005c7cb48fbc91ab871f343c6153175ac44d9ed8c6a679bc547fd42142e3377a65815c3f546e2f09d1f8a","href":"https://static.observableusercontent.com/files/298d7a1276b5217972dd2141c54b6a499af936ae7d4005c7cb48fbc91ab871f343c6153175ac44d9ed8c6a679bc547fd42142e3377a65815c3f546e2f09d1f8a","name":"image@3.png","type":"image/png","lastModified":1688462721295.617,"size":120323},{"id":"1721fcea06ac2465a320d0e6b35aa9b928ed5e3e32df17205e789370d8ba5832a5c8bd125add846de92e784a565613b8fc79eaf470345cb7f56b5f5267ac3ad5","href":"https://static.observableusercontent.com/files/1721fcea06ac2465a320d0e6b35aa9b928ed5e3e32df17205e789370d8ba5832a5c8bd125add846de92e784a565613b8fc79eaf470345cb7f56b5f5267ac3ad5","name":"2307_SeriesReport-20230704054321_c1186f@2.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1688464106742.612,"size":10673}] 2f:{"id":"9110db45dfc2b4de","slug":null,"title":"Advanced Data Viz Course","thumbnail":"49e3b8e7b5c25c76853ac31b4ed41e895e2facb91573182f4e68e995d0ccb899","access_level":"public","create_time":"$D2023-06-15T04:34:05.286Z","update_time":"$D2023-08-23T05:45:14.541Z","view_time":null,"first_public_time":"$D2023-06-15T04:34:05.286Z","has_unpublished_edits":null,"fork":{"id":"983c728f7c45926e","slug":"lesson-1-introduction-grammars","title":"Lesson 1: Introduction, Grammars","owner":{"id":"f35c755083683fe5","login":"observablehq","name":"Observable"}},"stars":0,"starred":false,"owner":{"type":"team","id":"ca32d02dd4fd9da1","login":"ssen0117","name":"Ssen Kim","avatar_url":"https://avatars-next.observableusercontent.com/acfa6bf30847029913fca8c84b4fea2653ded376d0d91ef7944bb954a0c4fbef","tier":"starter_2024"},"version":331,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"388e6ba669af2a7d","login":"ssen0117","name":"Ssen Kim","avatar_url":"https://avatars-next.observableusercontent.com/acfa6bf30847029913fca8c84b4fea2653ded376d0d91ef7944bb954a0c4fbef","tier":null}],"members":[{"type":"individual","id":"388e6ba669af2a7d","login":"ssen0117","name":"Ssen Kim","avatar_url":"https://avatars-next.observableusercontent.com/acfa6bf30847029913fca8c84b4fea2653ded376d0d91ef7944bb954a0c4fbef","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Advanced Data Viz Course","cells":[{"id":294,"value":"# Advanced Data Viz Course","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":0,"value":"_SSEN's_\n# Lesson 1: Introduction, Grammars","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"In the first lesson of this course, we'll go over a few logistics, talk about some theory, and look at the scatterplot matrix (and the variant, the faceted scatterplot). In the theory part, we'll talk about why we even visualize data, the pros and cons of common and uncommon chart types, and grammar-based approaches to data visualization.\n\nPlease take a look at the [materials pointers notebook](https://observablehq.com/@observablehq/advanced-course-materials-and-pointers?collection=@observablehq/advanced-data-vis-course) for links to the Observable Slack community, as well as some prerequisites (especially if you're not familiar with Observable).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":194,"value":"[자료 원본_Observable](https://observablehq.com/collection/@observablehq/advanced-data-vis-course)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":93,"value":"참고
http://book.visualisingdata.com/chapter/0","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":98,"value":"image1 = FileAttachment(\"image@1.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":12,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":107,"value":"[2회 수업 여기서 부터](https://www.youtube.com/live/-1jqnWJBwuc?feature=share&t=1815)","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":48,"value":"## Uncommon chart examples\n\nI briefly covered these examples, many of which we'll back to later in the course:\n\n- [The Connected Scatterplot](https://observablehq.com/@d3/connected-scatterplot/2)\n- [Sankey Diagram](https://observablehq.com/@d3/sankey)\n- [Parallel Sets](https://observablehq.com/@d3/parallel-sets)\n- [Treemap](https://observablehq.com/@d3/treemap)\n- [Scatterplot Matrix](https://observablehq.com/@d3/brushable-scatterplot-matrix) (brushable!)\n- [\"Swoopy Line Chart\"](https://observablehq.com/@mbostock/inequality-in-american-cities) (as opposed to [the animated scatterplot](https://observablehq.com/@mbostock/inequality-in-american-cities/2))\n- [Ridgeline Plot/Joy Plot](https://eagereyes.org/wp-content/uploads/2017/07/joy-plot.jpg)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":16,"value":"## Scatterplot in Observable Plot\n\nI ran out of time to show the full scatterplot matrix and faceted scatterplot examples, but we built a simple scatterplot in [Observable Plot](https://observablehq.com/plot/). Here is the data, which describes three populations of penguins. For an explanation of what the culmen is, [see Allison Horst's beautiful illustration](https://twitter.com/allison_horst/status/1270046411002753025/photo/1).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":26,"value":"data = penguins","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":56,"value":"data","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":60,"value":"The chart below maps the culmen depth and length data columns to the x and y dimensions of the scatterplot, respectively. The `marks` array contains a single entry in this case, a dot mark created by calling the `Plot.dot` function.\n\nI'll cover the scatterplot matrix next time, since I was going to talk about parallel coordinates too (and these two techniques are actually closely related). I will talk about facets in a later lesson.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":57,"value":"Plot.plot({\n marks: [\n Plot.dot(penguins, {\n x: \"culmen_length_mm\",\n y: \"culmen_depth_mm\",\n fill: \"species\",\n r: \"body_mass_g\",\n tip: true\n })\n ],\n color: {\n legend: true\n }\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"## Limits of Grammars\n\n- Even simple charts require relatively complex computations\n- Some require recursion and/or optimization \n일부는 최적화가 필요\n- Difficult to capture interactivity 상호작용을 포착하기 어려움\n- Trade-off between flexibility and expressiveness유연성과 표현력 차이 절충점\n
_Grammars like Observable Plot for fast exploration and variations of common charts 빠른 탐색과 일반적인 차트의 변형이 가능합니다._\n
_More promrammatic approaches like D3 useful for uncommon and bespoke charts
흔하지 않은 맞춤형 차트에 유용한 D3와 같은 보다 상징적인 접근 방식_\n ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":131,"value":"[2회차 시작](https://www.youtube.com/live/gKUBkXo-GBg?feature=share)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":133,"value":"File Attachment 실험 실패?\n${await FileAttachment(\"STUDIOSAENA_LOGO.png\").image({width: 600,height:600})}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":143,"value":"_SSEN's_\n# Lesson 2: Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":147,"value":"### Satterplot Matrix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":149,"value":"Plot.plot({\n marks: [\n Plot.dot(penguins, {\n x: \"culmen_length_mm\",\n y: \"culmen_depth_mm\",\n // fill: \"species\",\n // r: \"body_mass_g\",\n tip: true\n })\n ],\n color: {\n legend: true\n }\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":152,"value":"https://observablehq.com/@observablehq/brushable-scatterplot-matrix-cars\n↓원본","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":157,"value":"![image@3.png](${await FileAttachment(\"image@3.png\").url()})","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":161,"value":"역시 알아듣기는 어려우나 눈치밥으로 하는 중...그나저나 직접 입력하는 방법은 안 나오는 것 같다(원본 자료는 있어서 다행임)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":163,"value":"### Shapes of data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":166,"value":"[미국노동통계국](https://data.bls.gov/cgi-bin/surveymost?bls)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":170,"value":"unemploymentWide = unemploymentBLS.sheet(0, {headers: true})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":175,"value":"unemploymentWide","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":172,"value":"unemploymentBLS = FileAttachment(\"2307_SeriesReport-20230704054321_c1186f@2.xlsx\").xlsx({})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":176,"value":"[230705오늘은 여기부터!](https://www.youtube.com/live/gKUBkXo-GBg?feature=share&t=1969)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":179,"value":"data1 = aq.from(unemploymentWide)\n .fold(aq.not('Year'),{as : ['Month', 'Unemployment']})\n .objects()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":184,"value":"data1","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":185,"value":"## Missing values","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":197,"value":"## Parallel coordinates","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":201,"value":"# Interaction\n## Facets","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":187,"value":"data2 = data","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"data2","database":"$undefined"},{"id":211,"value":"Plot.plot({\n marginRight: 80,\n color: {\n legend: true\n },\n marks: [\n Plot.auto(data2, {x: \"culmen_length_mm\", y: \"culmen_depth_mm\", fx: \"species\", fy: \"island\", color: \"island\"})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":233,"value":"Plot.plot({\n marginRight: 80,\n color: {\n legend: true\n },\n marks: [\n Plot.auto(data2, {x: \"body_mass_g\", fy: \"species\"})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":231,"value":"Plot.plot({\n color: { legend: true },\n marginRight: 80,\n x: {},\n marks: [\n Plot.frame({ strokeOpacity: 0.1 }),\n Plot.dot(data2, {\n fx: \"species\",\n fy: \"island\",\n x: \"culmen_length_mm\",\n y: \"culmen_depth_mm\",\n stroke: \"island\",\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":244,"value":"## Interaction\n### Tooltips","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":247,"value":"Plot.plot({\n marks: [\n Plot.dot(cars, {x: \"power (hp)\", y: \"economy (mpg)\", tip: true,\n title: d => `${d.name} (19${d.year}): ${d[\"power (hp)\"]} HP, ${d[\"economy (mpg)\"]} MPG`})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":249,"value":"[참고_Crossfilter](http://crossfilter.github.io/crossfilter/)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":272,"value":"## [내일은 여기부터](https://www.youtube.com/live/_Z39cYrtsDM?feature=share&t=2140)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":261,"value":"viewof minWeight = Inputs.range(d3.extent(cars, d => d[\"weight (lb)\"]), {label: \"Min Weight\", step: 1, value: d3.min(cars, d => d[\"weight (lb)\"])})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":257,"value":"viewof maxWeight = Inputs.range(d3.extent(cars, d => d[\"weight (lb)\"]), {label: \"Max Weight\", step: 1, value: d3.max(cars, d => d[\"weight (lb)\"])})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":255,"value":"viewof pinCarAxes = Inputs.toggle({label: \"Pin Axes\", value: true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":253,"value":"viewof mode = Inputs.select([\"Filter\", \"Highlight\"], {label: \"Mode\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":251,"value":"Plot.plot({\n marks: [\n Plot.dot((mode === \"Filter\" ? carsFiltered:cars), {x: \"power (hp)\", y: \"economy (mpg)\", title: \"name\",\n fill: d=>(mode ===\"Filter\" ? \"black\" : \n (d[\"weight (lb)\"] >= minWeight && d[\"weight (lb)\"] <=maxWeight ?\n \"steelblue\" : \"lightgray\"))}) \n ],\n x:{\n domain: (pinCarAxes || mode ===\"Highlight\") ? [40,240] : undefined\n },\n y: {\n domain: (pinCarAxes || mode === \"Highlight\") ? [8,48] : undefined\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":282,"value":"carsFiltered = cars.filter(d => d[\"weight (lb)\"] >= minWeight && d[\"weight (lb)\"] <= maxWeight)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":301,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":299,"value":"## Lesson 4: Presentation, Uncertainty, ISOTYPE","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":303,"value":"[MOSAIC-데이터 시각화 프레임 워크](https://uwdata.github.io/mosaic/what-is-mosaic/)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":309,"value":"### Presentation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":306,"value":"- repetitive use of the same kinds of charts, need for more variety(같은 종류의 차트를 반복적으로 사용, 더 많은 다양성 필요)\n\n - _some people are half asleep_(어떤 사람들은 반쯤 잠 들어있다=그래프를 잘 모른다?)\n - _I hate bar charts, [they're] very 2001_\n - use lollipop charts to _break up an otherwise boring series of charts_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":313,"value":"- meetings are usually recurring 회의는 일반적으로 반복적으로 진행됩니다.\n - don't treat every meeting as independent of the others 모든 미팅을 다른 미팅과 독립적인 것으로 취급하지 마세요.\n - build on what was discussed last time (with reminders for those who don't remember) 지난번에 논의한 내용을 기반으로 구축합니다(기억이 나지 않는 분들을 위한 알림 포함).\n - show what's different (for those who do remember) 무엇이 다른지 보여주세요(기억하는 사람들을 위해).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":318,"value":"- meetings have different functions\n - get peers up to speed on data, collect questions, work together on analysis(\"jam session\")\n - present to superiors who want to be able to ask questions, usually on an ongoing basis(\"semi-improvised performances\")\n - present to a large audience that knows little about the topic, but makes important decisions(\"recital\")\n \n- 회의에는 다양한 기능이 있습니다.\n - 동료들에게 데이터에 대한 정보를 제공하고, 질문을 수집하고, 분석을 위해 함께 작업(\"잼 세션\")\n - 일반적으로 지속적으로 질문할 수 있기를 원하는 상사에게 프레젠테이션(\"반즉흥 공연\")\n - 주제에 대해 거의 알지 못하지만 중요한 결정을 내리는 많은 청중에게 발표(\"발표회\")","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":320,"value":"- tool support\n - disconnect between analysis and presentation tools\n - causes issues with charts being out of date, needing to remake all of them to make sure they're consistent, etc.\n\n- 도구 지원\n - 분석 도구와 프레젠테이션 도구 간의 단절\n - 차트가 오래되어 일관성을 유지하기 위해 모든 차트를 다시 만들어야 하는 등의 문제를 일으킵니다.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":323,"value":"[다음은 여기부터. 4.5구간](https://www.youtube.com/live/Wb6xKQRtWig?feature=share&t=1924)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":328,"value":"Plot.plot({\n color: {\n legend: true\n },\n marks: [\n Plot.auto(data, {x: \"species\", color: \"island\"})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"}],"files":"$W32","stdlib":"1","titling":"auto"}} 30:"$2f:body"