컴퓨터 언어 하나쯤은 잘 사용하면 좋습니다. 대학교에 들어가면 C 언어 또는 Python을 주로 배우게 될 것입니다. 그 때 피하지 말고 즐기시길. 아래 언어들은 데이터과학쪽이나 논문 쓸 때 활용하면 좋습니다. Quarto 오픈소스 샘플을 가져왔습니다.
Hello, Quarto
Combine Jupyter notebooks with flexible options to produce production quality output in a wide variety of formats. Author using traditional notebook UIs or with a plain text markdown representation of notebooks.
Quarto is a multi-language, next generation version of R Markdown from Posit, with many new new features and capabilities. Like R Markdown, Quarto uses knitr to execute R code, and is therefore able to render most existing Rmd files without modification.
---
title: "ggplot2 demo"
author: "Norah Jones"
date: "5/22/2021"
format:
html:
fig-width: 8
fig-height: 4
code-fold: true
---
## Air Quality
@fig-airquality further explores the impact of temperature on ozone level.
```{r}
#| label: fig-airquality
#| fig-cap: "Temperature and ozone level."
#| warning: false
library(ggplot2)
ggplot(airquality, aes(Temp, Ozone)) +
geom_point() +
geom_smooth(method = "loess")
```
Combine markdown and Julia code to create dynamic documents that are fully reproducible. Quarto executes Julia code via the IJulia Jupyter kernel, enabling you to author in plain text (as shown below) or render existing Jupyter notebooks.
---
title: "Plots Demo"
author: "Norah Jones"
date: "5/22/2021"
format:
html:
code-fold: true
jupyter: julia-1.8
---
## Parametric Plots
Plot function pair (x(u), y(u)).
See @fig-parametric for an example.
```{julia}
#| label: fig-parametric
#| fig-cap: "Parametric Plots"
using Plots
plot(sin,
x->sin(2x),
0,
2π,
leg=false,
fill=(0,:lavender))
```
Quarto includes native support for Observable JS, a set of JavaScript enhancements created by Mike Bostock (the author of D3). Observable JS uses a reactive execution model, and is especially well suited for interactive data exploration and analysis.
---
title: "observable plot"
author: "Norah Jones"
format:
html:
code-fold: true
---
## Seattle Precipitation by Day (2012 to 2016)
```{ojs}
data = FileAttachment("seattle-weather.csv")
.csv({typed: true})
Plot.plot({
width: 800, height: 500, padding: 0,
color: { scheme: "blues", type: "sqrt"},
y: { tickFormat: i => "JFMAMJJASOND"[i] },
marks: [
Plot.cell(data, Plot.group({fill: "mean"}, {
x: d => new Date(d.date).getDate(),
y: d => new Date(d.date).getMonth(),
fill: "precipitation",
inset: 0.5
}))
]
})
```
References
Footnotes
입시수학, 공업수학, 미적분, 일반 문제풀이,…↩︎