From dc3c7746051cc486a8182369a7d43d208efb1b36 Mon Sep 17 00:00:00 2001 From: Kwangchun Lee Date: Wed, 29 May 2024 12:17:06 +0900 Subject: [PATCH] add billboard chart --- .../execute-results/html.json | 4 +- .../figure-revealjs/unnamed-chunk-16-1.png | Bin 102939 -> 103684 bytes .../figure-revealjs/unnamed-chunk-17-1.png | Bin 98092 -> 98572 bytes chatgpt_viz_202406.qmd | 5 - docs/chatgpt_viz_202406.html | 327 ++++++++++-------- .../figure-revealjs/unnamed-chunk-16-1.png | Bin 102939 -> 103684 bytes .../figure-revealjs/unnamed-chunk-17-1.png | Bin 98092 -> 98572 bytes docs/img/billboard_gt.png | Bin 0 -> 492478 bytes docs/search.json | 7 + docs/sitemap.xml | 2 +- img/billboard_gt.png | Bin 0 -> 492478 bytes slideshow/202406-viz/data-viz-journalism.qmd | 34 ++ 12 files changed, 232 insertions(+), 147 deletions(-) create mode 100644 docs/img/billboard_gt.png create mode 100644 img/billboard_gt.png diff --git a/_freeze/chatgpt_viz_202406/execute-results/html.json b/_freeze/chatgpt_viz_202406/execute-results/html.json index a713bb3..cf059f4 100644 --- a/_freeze/chatgpt_viz_202406/execute-results/html.json +++ b/_freeze/chatgpt_viz_202406/execute-results/html.json @@ -1,8 +1,8 @@ { - "hash": "ef5f23e1ad8c681ee7671c20805c1140", + "hash": "e52bdcb2979cdd4fd2f9517cd970dd85", "result": { "engine": "knitr", - "markdown": "---\ntitle: \"챗GPT 데이터 시각화\"\nsubtitle: \"데이터 시각화 어디까지 보고 오셨어요?\"\nauthor: \"이광춘\"\ninstitute: \"한국 R 사용자회\"\ndate: 2024-06-25\nformat: \n insper-revealjs:\n self-contained: false\n footer: |\n 한국 R 사용자회 [chatGPT](https://r2bit.com/chatGPT/). theme [insper](https://github.com/padsInsper/quarto-insper-theme) 소스코드 [GitHub](https://github.com/padsInsper/quarto-insper-theme).\ndate-format: long\nlang: ko\nfilters:\n - lightbox\nlightbox: auto\nbibliography: bibliography.bib\ncsl: apa-single-spaced.csl \neditor_options: \n chunk_output_type: console\ninclude-in-header:\n - text: |\n \n---\n\n\n## 목차\n\n1. 데이터 시각화 [@Lee2018Visualization]\n\n2. 데이터 시각화 + 저널리즘\n\n3. 데이터 시각화 + 저널리즘 + 챗GPT\n\n4. 질의응답!\n\n\n\n# {background-image=\"img/meetup_logo.jpg\"}\n\n::: r-fit-text\n\n2023년 챗GPT 데이터 사이언스\n



\n:::\n\n## 서울 R 미트업 (2023년) {.smaller}\n\n::: columns\n::: column\n::: r-stack\n\n![](img/seoul-r-meetup-september.jpg){.fragment width=\"320\"}\n\n::: fragment\n![](img/seoul-r-meetup-august.jpg){.fragment width=\"320\"}\n:::\n\n\n::: fragment\n![](img/seoul-r-meetup-july.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoulr-r-meetup-june.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoul-r-meetup-202305.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoul-r-meetup-AsiaR.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoul-r-meetup-202304.jpg){.fragment width=\"320\"}\n:::\n\n\n:::\n:::\n\n::: column\n## 참여와 연대\n\n- **서울R미트업 meetup.com**: [link](https://www.meetup.com/seoul-r-meetup)\n - **23년 4월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/292232899/)\n - **23년 5월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/292966674/)\n - **23년 6월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/293485362/)\n - **23년 7월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/293929603/)\n - **23년 8월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/294651161/)\n - **23년 9월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/295338359/)\n- 세계 R 미트업 현황 (Global R Meetup Dashboard): [link](https://r-community.org/usergroups/)\n- 한국 R 사용자회 (Korea R User Group): [link](https://r2bit.com/)\n- 한국 R 컨퍼런스 (Korea R Conference): [link](https://use-r.kr/)\n- 유튜브 채널 (Youtube Channel): [link](https://www.youtube.com/channel/UCW-epmIvjBEhhVXw_F0Nqbw)\n- 페이스북 그룹 (Facebook Group): [link](https://www.facebook.com/groups/tidyverse)\n:::\n:::\n\n\n\n# {background-image=\"img/meetup_logo.jpg\"}\n\n::: r-fit-text\n\n2024년 인공지능 데이터 사이언스\n



\n:::\n\n## 서울 R 미트업 {.smaller}\n\n::: columns\n::: column\n::: r-stack\n\n![](img/meetup/20240430_poster.png){.fragment width=\"320\"}\n\n::: fragment\n![](img/meetup/20240430_poster.png){.fragment width=\"320\"}\n:::\n\n\n\n:::\n:::\n\n::: column\n## 참여와 연대\n\n- **서울R미트업 meetup.com**: [link](https://www.meetup.com/seoul-r-meetup)\n - **23년 4월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/300281000/)\n - **23년 5월 서울 R 미트업**: [link]()\n - **23년 6월 서울 R 미트업**: [link]()\n - **23년 7월 서울 R 미트업**: [link]()\n - **23년 8월 서울 R 미트업**: [link]()\n - **23년 9월 서울 R 미트업**: [link]()\n- Resources for General Help with R - Regional R communities [link](https://contributor.r-project.org/r-help)\n- 세계 R 미트업 현황 (Global R Meetup Dashboard): [link](https://r-community.org/usergroups/)\n- 한국 R 사용자회 (Korea R User Group): [link](https://r2bit.com/)\n- 한국 R 컨퍼런스 (Korea R Conference): [link](https://use-r.kr/)\n- 유튜브 채널 (Youtube Channel): [link](https://www.youtube.com/channel/UCW-epmIvjBEhhVXw_F0Nqbw)\n- 페이스북 그룹 (Facebook Group): [link](https://www.facebook.com/groups/tidyverse)\n:::\n:::\n\n\n\n# 데이터 시각화\n\n## 정적 그래프 {.smaller}\n\n
\n\n::: {.cell .custom3070 output-location='column-fragment'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(plotly)\nlibrary(gapminder)\nlibrary(crosstalk)\nlibrary(leaflet)\nlibrary(flipbookr)\n\ngapminder %>% \n ggplot(aes(x=year, \n y=lifeExp, \n group=country)) + \n geom_line()\n```\n\n::: {.cell-output-display}\n![](chatgpt_viz_202406_files/figure-revealjs/fig-static-graph-1.png){#fig-static-graph width=672}\n:::\n:::\n\n\n## 인터랙티브 그래프 {.smaller}\n\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\np <- gapminder %>% \n ggplot(aes(x=year, \n y=lifeExp, \n group=country)) + \n geom_line()\n\nggplotly(p)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 인터랙티브 그래프 - 툴팁(Tooltip) 기능 {.smaller}\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\np <- gapminder %>% \n ggplot(aes(\n x = year, \n y = lifeExp, \n group = country, \n text = paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_line()\n\nggplotly(p, tooltip = \"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n\n## 강조(Highlight) 기능 {.smaller}\n\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\ngm_highlight <- highlight_key(gapminder, \n ~country)\n\nlife_g <- gm_highlight %>% \n ggplot(aes(\n x=year, \n y=lifeExp, \n group=country, \n text=paste0(\"대륙: \", continent, \"\\n\",\n \"국가: \", country))) + \n geom_line()\n\nlife_gg <- ggplotly(life_g, tooltip = \"text\")\nhighlight(life_gg, on = \"plotly_click\", \n selectize = TRUE, \n dynamic = TRUE, \n persistent = TRUE)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 연결뷰(Linked View) 기능 {.smaller}\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\ngapminder_cjk <- gapminder %>% \n filter(country %in% c(\"China\", \"Japan\", \n \"Korea, Rep.\"))\n\ngapminder_sd <- SharedData$new(gapminder_cjk, \n ~country)\n\nlife_g <- gapminder_sd %>% \n ggplot(aes(\n x = year, \n y = lifeExp, \n group = country,\n text = paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_line() +\n geom_point() +\n facet_wrap(~country)\n\nggplotly(life_g, tooltip = \"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n\n## 삼국지 {.smaller}\n\n::: {.cell}\n\n:::\n\n\n::: {.cell output-location='slide' class='output3'}\n\n```{.r .cell-code}\nlibrary(crosstalk); library(DT)\n### 1. 공유 데이터\ngeneral_sd_df <- general_df %>% select(삼국, 무장, 무력, 지력, 통솔, 생년)\nsam_sd <- SharedData$new(general_sd_df)\n\n### 2. 제어\nsam_ctrl <- filter_checkbox(\"삼국\", \"위촉오\", sam_sd, ~삼국, inline = TRUE)\nyear_ctrl <- filter_slider(\"생년\", \"출생년도\", sam_sd, ~생년, width = \"50%\")\n\n### 3. 표\nsam_tbl <- sam_sd |> \n datatable( extensions=\"Scroller\", style=\"bootstrap\", class=\"compact\", width=\"100%\",\n options=list(deferRender=TRUE, scrollY=300, scroller=TRUE))\n\n### 4. 시각화\nforce_g <- ggplot(sam_sd, aes(x=무력, y=통솔, color=삼국,\n text = paste('이름 :', 무장, \"\\n\",\n '무력:', 무력, \"\\n\",\n '지력:', 지력, \"\\n\",\n '통솔:', 통솔, \"\\n\"))) +\n geom_point() +\n theme(legend.position = \"none\") +\n labs(x=\"무력\", y=\"통솔\") +\n scale_color_manual(values = c(\"red\", \"green\", \"blue\"))\n\nforce_gg <- ggplotly(force_g, tooltip = \"text\")\n\n### 5. 인터랙티브 시각화\nbscols(widths = c(2, 5, 5),\n list(year_ctrl, sam_ctrl),\n sam_tbl, force_gg)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
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\n```\n\n:::\n:::\n\n## 애니메이션 {.smaller}\n\n::: {.cell .custom3070 output-location='column-fragment'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(gapminder)\nlibrary(plotly)\n\nlife_g <- gapminder %>% \n ggplot(aes(\n x = gdpPercap, \n y = lifeExp, \n group = country, color=country,\n text=paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_point(alpha = 0.2) +\n geom_point() +\n facet_wrap(~continent, ncol = 2) +\n scale_x_sqrt() +\n theme(legend.position = \"none\")\n\nggplotly(life_g, tooltip=\"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 애니메이션 {.smaller}\n\n`frame= 매개변수`만 넣으면 됨.\n\n::: {.cell .custom3070 output-location='column-fragment'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(gapminder)\nlibrary(plotly)\n\nlife_g <- gapminder %>% \n ggplot(aes(\n x = gdpPercap, \n y = lifeExp, \n group = country, color=country,\n text=paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_point(alpha = 0.2) +\n geom_point(aes(frame = year), color=\"red\") +\n facet_wrap(~continent, ncol = 2) +\n scale_x_sqrt() +\n theme(legend.position = \"none\")\n\nggplotly(life_g, tooltip=\"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 애니메이션 - 2017년 버전\n\n::: panel-tabset\n### 정적 그래프\n\n![](img/party-approval-static.png){fig-align=\"center\"}\n\n### Small Multiple\n\n![](img/party-approval-static-facet.png){fig-align=\"center\"}\n\n### 애니메이션\n\n![](img/party_approval_2017.gif){fig-align=\"center\"}\n:::\n\n::: aside\n[정적 그래프에서 부드러운 동영상 그래프까지](https://statkclee.github.io/viz/viz-animations.html)\n:::\n\n\n## `crosstalk` \n\n::: {.cell .output3 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(crosstalk); library(plotly); library(leaflet); library(palmerpenguins)\npenguins <- na.omit(penguins) # Remove missing data for simplicity\n\npenguins$longitude <- rnorm(nrow(penguins), mean = -64, sd = 0.1)\npenguins$latitude <- rnorm(nrow(penguins), mean = -64, sd = 0.1)\n\n# Create a shared data object\nsd_penguins <- SharedData$new(penguins)\n\n# Plot with plotly\npenguin_plot <- plot_ly(sd_penguins, x = ~bill_length_mm, y = ~flipper_length_mm, \n color = ~species, \n text = ~paste(\"Body Mass:\", body_mass_g), \n type = 'scatter', mode = 'markers') %>% \n add_markers() %>% highlight(\"plotly_selected\")\n\n# Map with leaflet\npenguin_map <- leaflet(sd_penguins) %>% addTiles() %>% \n addCircles(lng = ~longitude, lat = ~latitude, \n weight = 1, radius = 40, popup = ~species)\n\n# Combine both using crosstalk\nbscols(widths = c(6, 6), penguin_plot, penguin_map)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
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\n```\n\n:::\n:::\n\n## 지도 - `BitSpatial`\n\n::: {.cell .custom3070 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(tidyverse);library(sf);library(bitSpatial);library(ggiraph)\n\nstart_gg <- bitSpatial::admi |> \n ggplot(aes(geometry = geometry)) +\n geom_sf(\n data = bitSpatial::mega,\n aes(fill = mega_nm), color = 'black', linewidth = 0.5\n ) +\n geom_sf(fill = NA, color = 'black', linewidth = 0.1)\n\n# 인터랙티브 지도\nmap_gg <- bitSpatial::admi |> \n ggplot(aes(geometry = geometry)) +\n geom_sf(\n data = bitSpatial::mega,\n aes(fill = mega_nm), color = 'black', linewidth = 0.5 ) +\n geom_sf(fill = NA, color = 'black', linewidth = 0.1 ) +\n geom_sf_interactive(fill = NA, \n aes(data_id = cty_cd, tooltip = glue::glue('{mega_nm}
{cty_nm}')),\n linewidth = 0.1\n ) +\n theme_void() +\n theme(legend.position = 'none') +\n scale_fill_manual(\n values = c(\"#A0CBE8FF\", \"#F28E2BFF\", \"#FFBE7DFF\", \"#59A14FFF\", \"#8CD17DFF\", \"#B6992DFF\", \"#F1CE63FF\", \"#499894FF\", \"#86BCB6FF\", \"#E15759FF\", \"#FF9D9AFF\", \"#79706EFF\", \"#BAB0ACFF\", \"#D37295FF\", \"#B07AA1FF\", \"#D4A6C8FF\", \"#9D7660FF\") ) \n\ngirafe(ggobj = map_gg,\n options = list(opts_hover(\n css = girafe_css(css = '', area = 'stroke: black; fill: black;'))))\n```\n\n::: {#fig-bitSpatial .cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 로고 + 막대그래프\n\n\n::: {.cell .custom3070 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\n\ndat <- tribble( ~neo_bank, ~market_cap_bn, ~logo_url,\n \"Nubank\", 45, \"https://upload.wikimedia.org/wikipedia/commons/f/f7/Nubank_logo_2021.svg\",\n \"Revolut\", 33, \"https://upload.wikimedia.org/wikipedia/commons/d/d6/Revolut.svg\",\n \"Chime\", 25, \"https://upload.wikimedia.org/wikipedia/commons/f/f6/Chime_company_logo.svg\",\n \"WeBank\", 21, \"https://upload.wikimedia.org/wikipedia/en/e/eb/WeBank_Logo.svg\",\n \"Kakaobank\", 19, \"https://upload.wikimedia.org/wikipedia/commons/4/48/KakaoBank_logo.svg\",\n \"Robinhood\", 10, \"https://upload.wikimedia.org/wikipedia/commons/d/da/Robinhood_%28company%29_logo.svg\",\n \"SoFi\", 10, \"https://upload.wikimedia.org/wikipedia/commons/1/16/SoFi_logo.svg\",\n \"Tinkoff\", 9, \"https://upload.wikimedia.org/wikipedia/commons/1/19/Tinkoff_logo_2024.svg\",\n \"N26\", 9, \"https://upload.wikimedia.org/wikipedia/commons/b/bf/N26_logo_2019.svg\",\n \"K Bank\", 7, \"https://upload.wikimedia.org/wikipedia/commons/2/26/Kbank_logo.svg\"\n) \n\nmap(dat$logo_url, magick::image_read_svg) |>\n walk2(\n dat$neo_bank,\n \\(x, y) magick::image_write(x, path = paste0(\"img/logos/\", y, \".png\"))\n )\n\ndat |> \n mutate(neo_bank = fct_reorder(neo_bank, market_cap_bn)) |>\n ggplot(aes(x = market_cap_bn, y = neo_bank)) +\n geom_col() +\n scale_y_discrete(\n labels = \\(x) glue::glue(\"\")\n ) +\n theme_minimal(base_size = 12, base_family = 'Source Sans Pro') +\n labs(\n title = 'Top 10 neobanks worldwide by market capitalization 2022',\n y = element_blank()) +\n theme(axis.text.y = ggtext::element_markdown())\n```\n\n::: {.cell-output-display}\n![카카오뱅크와 K뱅크](chatgpt_viz_202406_files/figure-revealjs/fig-image-logo-1.png){#fig-image-logo width=672}\n:::\n:::\n\n::: aside\n\n출처: \n\n:::\n\n\n## 인터랙티브 그래프\n\n::: {.cell .custom3070 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(tidyverse); library(palmerpenguins); library(ggiraph); library(patchwork)\ncolor_palette <- thematic::okabe_ito(3)\n\nscatter_gg <- penguins |> drop_na() |>\n ggplot(aes(x = flipper_length_mm, y = body_mass_g, color = species, data_id = species)) +\n geom_point_interactive(size = 1) +\n labs(title = \"펭귄의 지느러미 길이와 몸무게\",\n x = \"지느러미 길이 (mm)\", y = \"몸무게 (g)\", color = \"종\") +\n theme_minimal(base_size = 5) +\n theme(legend.position = \"top\") +\n scale_color_manual(values = color_palette) +\n scale_y_continuous(labels = scales::comma) \n\nboxplot_gg <- penguins |> drop_na() |> \n ggplot(aes(x = species, y = body_mass_g, fill = species, data_id = species)) +\n geom_boxplot_interactive() + \n geom_jitter_interactive(aes(col = species)) +\n labs(title = \"펭귄 종별 몸무게\",\n x = \"펭귄 종명\", y = \"몸무게 (g)\", color = \"종\") +\n theme_minimal(base_size = 12) +\n theme(legend.position = \"none\") +\n scale_fill_manual(values = color_palette) +\n scale_color_manual(values = color_palette) +\n scale_y_continuous(labels = scales::comma) +\n coord_flip()\n\ngirafe(\n ggobj = boxplot_gg + plot_spacer() + scatter_gg + plot_layout(widths = c(0.45, 0.1, 0.45)),\n options = list(\n opts_hover(css = ''), opts_hover_inv(css = \"opacity:0.1;\"), \n opts_sizing(rescale = FALSE)\n ))\n```\n\n::: {#fig-interactive-ggiraph .cell-output-display}\n\n```{=html}\n
\n\n```\n\n\n산점도와 상자그림\n:::\n:::\n\n\n# 데이터 시각화 + 저널리즘\n\n## 문 대통령 해외순방 {.smaller}\n\n::: panel-tabset\n### 뉴스 기사\n\n![](img/omn_viz.png){fig-align=\"center\" width=\"495\"}\n\n### 위키 데이터\n\n::: {.cell output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(rvest)\n\nmoon_html <- read_html(\"https://ko.wikipedia.org/wiki/문재인의_대통령_순방_목록\")\n\nmoon_raw <- moon_html |> \n html_elements(\"table\") |> \n html_table()\n\nmoon_h3 <- moon_html |> \n html_elements(\"h3\") |> \n html_text()\n\nnames(moon_raw) <- moon_h3[1:6]\n\nmoon_tbl <- moon_h3 |> \n enframe() |> \n mutate(연도 = str_remove(value, \"년\\\\[편집\\\\]\")) |> \n filter(str_detect(연도, \"\\\\d{4}\")) |> \n mutate(data = moon_raw[c(1:5)]) |> \n unnest(data) |> \n select(연도, 나라, 장소, 일자, 세부내용=`세부 내용`) |>\n separate(일자, into = c(\"출국\", \"도착\"), sep = \"~\") |> \n mutate(도착 = ifelse(is.na(도착), 출국, 도착)) |> \n mutate(출국일 = str_glue(\"{연도}-{출국}\"),\n 도착일 = str_glue(\"{연도}-{도착}\")) |> \n mutate(출국일 = parse_date(출국일, \"%Y-%m월 %d일\"),\n 도착일 = parse_date(도착일, \"%Y-%m월 %d일\")) |> \n select(출국일, 도착일, 국가 = 나라, 장소) |> \n mutate(기간 = (출국일 %--% 도착일) / ddays(1) +1)\n\nmoon_tbl |> slice(1:5) |> gt::gt()\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n \n \n
출국일도착일국가장소기간
2017-06-282017-07-03미국워싱턴 D.C.6
2017-07-052017-07-08독일베를린, 함부르크4
2017-09-062017-09-07러시아블라디보스토크2
2017-09-192017-09-21미국뉴욕3
2017-11-082017-11-10인도네시아자카르타3
\n
\n```\n\n:::\n:::\n\n### 표\n\n::: {.cell output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\nlibrary(countrycode)\nlibrary(gt)\nlibrary(gtExtras)\n\ncountry_codes <- data.frame(\n \"국가\" = c(\"노르웨이\", \"뉴질랜드\", \"덴마크\", \"독일\", \"라오스\", \"러시아\", \"말레이시아\", \"미국\", \"미얀마\", \"바티칸 시국\", \"베트남\", \"벨기에\", \"브루나이\", \"사우디아라비아\", \"스웨덴\", \"스페인\", \"싱가포르\", \"아랍에미리트\", \"아르헨티나\", \"영국\", \"오스트레일리아\", \"오스트리아\", \"우즈베키스탄\", \"이집트\", \"이탈리아\", \"인도\", \"인도네시아\", \"일본\", \"조선민주주의인민공화국\", \"중화인민공화국\", \"체코\", \"카자흐스탄\", \"캄보디아\", \"태국\", \"투르크메니스탄\", \"파푸아뉴기니\", \"프랑스\", \"핀란드\", \"필리핀\", \"헝가리\"),\n \"영문_국가명\" = c(\"Norway\", \"New Zealand\", \"Denmark\", \"Germany\", \"Laos\", \"Russia\", \"Malaysia\", \"United States\", \"Myanmar\", \"Vatican City\", \"Vietnam\", \"Belgium\", \"Brunei\", \"Saudi Arabia\", \"Sweden\", \"Spain\", \"Singapore\", \"United Arab Emirates\", \"Argentina\", \"United Kingdom\", \"Australia\", \"Austria\", \"Uzbekistan\", \"Egypt\", \"Italy\", \"India\", \"Indonesia\", \"Japan\", \"North Korea\", \"China\", \"Czech Republic\", \"Kazakhstan\", \"Cambodia\", \"Thailand\", \"Turkmenistan\", \"Papua New Guinea\", \"France\", \"Finland\", \"Philippines\", \"Hungary\"),\n \"iso2c\" = c(\"NO\", \"NZ\", \"DK\", \"DE\", \"LA\", \"RU\", \"MY\", \"US\", \"MM\", \"VA\", \"VN\", \"BE\", \"BN\", \"SA\", \"SE\", \"ES\", \"SG\", \"AE\", \"AR\", \"GB\", \"AU\", \"AT\", \"UZ\", \"EG\", \"IT\", \"IN\", \"ID\", \"JP\", \"KP\", \"CN\", \"CZ\", \"KZ\", \"KH\", \"TH\", \"TM\", \"PG\", \"FR\", \"FI\", \"PH\", \"HU\")\n)\n\nmoon_tbl |> \n group_by(국가) |> \n summarise(방문수 = n(),\n 연도 = str_c(str_glue(\"{lubridate::year(출국일)}\"), collapse = \",\")) |> \n left_join(country_codes, by = \"국가\") |> \n mutate(대륙 = countrycode(iso2c, \"iso2c\", \"continent\")) |>\n arrange(desc(방문수)) |>\n select(-영문_국가명) |> \n select(iso2c, everything()) |> \n filter(대륙 %in% c(\"Americas\", \"Oceania\")) |> \n gt(groupname_col = \"대륙\") |> \n fmt_flag(columns = iso2c) |> \n cols_label(\n iso2c = \"\"\n ) |> \n cols_align(\"center\") |> \n tab_header(\n title = md(\"문재인 대통령 해외 순방\"),\n subtitle = md(\"2017년 5월 10일 ~ 2021년 5월 9일\")\n ) |>\ntab_footnote(\n footnote = md(\"데이터 출처: [위키백과](https://ko.wikipedia.org/wiki/문재인의_대통령_순방_목록)\")\n) |> \n gt_theme_538() |> \n ## 표 전체 합계 -------------------------------------\n grand_summary_rows(\n columns = 방문수,\n fns = list(label = \"\", fn = \"sum\"),\n fmt = ~ fmt_integer(.),\n side = \"bottom\"\n )\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\n \n \n \n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n \n \n \n \n \n \n
문재인 대통령 해외 순방
2017년 5월 10일 ~ 2021년 5월 9일
국가방문수연도
Americas
United States미국82017,2017,2018,2018,2019,2019,2021,2021
Argentina아르헨티나12018
Oceania
New Zealand뉴질랜드12018
Australia오스트레일리아12021
Papua New Guinea파푸아뉴기니12018
12
데이터 출처: 위키백과
\n
\n```\n\n:::\n:::\n\n### 지도\n\n::: {.cell .custom7030 output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\nlibrary(viridis); library(sf); sf_use_s2(FALSE)\n\nmoon_tour <- moon_tbl |> group_by(국가) |> \n summarise(방문수 = n(),\n 연도 = str_c(str_glue(\"{lubridate::year(출국일)}\"), collapse = \",\")) |> \n left_join(country_codes, by = \"국가\")\n\nworld_map <- rnaturalearth::ne_countries(scale = 50, returnclass = \"sf\")\ncountry_centroid <- inner_join(st_centroid(world_map), moon_tour, \n by = c(\"iso_a2\" = \"iso2c\"))\n\ncountry_centroid <- bind_cols(country_centroid,\n st_coordinates(country_centroid) |> \n as_tibble() |> set_names(c(\"lon\", \"lat\")))\n\nmoon_map <- left_join(world_map, moon_tour, by = c(\"iso_a2\" = \"iso2c\"))\n\nmoon_map |> \n filter(continent != \"Antarctica\") |> \n mutate(방문수 = factor(방문수, levels = c(1, 2, 8),\n labels = c(\"1회\", \"2회\", \"8회\"))) |>\n ggplot() +\n geom_sf(aes(fill = 방문수)) +\n scale_fill_manual(values = c(\"gray50\", \"skyblue\", \"blue\"), \n na.value = \"transparent\",\n breaks = c(\"1회\", \"2회\", \"8회\", NA),\n labels = c(\"1회\", \"2회\", \"8회\", \"방문 없음\")) +\n labs(title = \"문재인 대통령 해외순방\") +\n theme_void(base_family = \"NanumGothic\") +\n theme(legend.position = \"bottom\") +\n ggrepel::geom_text_repel(\n data = country_centroid |> select(국가, lon, lat) |> st_drop_geometry(),\n aes(label = 국가, x = lon, y = lat), size = 3, segment.size = 0.2)\n```\n\n::: {.cell-output-display}\n![](chatgpt_viz_202406_files/figure-revealjs/unnamed-chunk-16-1.png){width=672}\n:::\n:::\n\n### 태평양 중심지도\n\n::: {.cell .custom7030 output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\noffset <- 180 - 150\n\npolygon <- st_polygon(x = list(rbind(\n c(-0.0001 - offset, 90), c(0 - offset, 90),\n c(0 - offset, -90), c(-0.0001 - offset, -90),\n c(-0.0001 - offset, 90) ))) %>%\n st_sfc() %>% st_set_crs(4326)\n\nworld_pacific <- world_map |> \n st_difference(polygon) |> st_transform(crs = \"+proj=eqc +x_0=0 +y_0=0 +lat_0=0 +lon_0=150\")\n\nmoon_pacific_map <- left_join(world_pacific, moon_tour, by = c(\"iso_a2\" = \"iso2c\"))\n\npacific_centroid <- inner_join(st_centroid(moon_pacific_map), moon_tour, by = c(\"iso_a2\" = \"iso2c\"))\n\npacific_country_centroid <- bind_cols(pacific_centroid,\n st_coordinates(pacific_centroid) |> as_tibble() |> set_names(c(\"lon\", \"lat\")))\n\n\nmoon_pacific_map |> \n mutate(방문수 = factor(방문수, levels = c(1, 2, 8), labels = c(\"1회\", \"2회\", \"8회\"))) |>\n ggplot() +\n geom_sf(aes(fill = 방문수)) +\n scale_fill_manual(values = c(\"gray50\", \"skyblue\", \"blue\"), \n na.value = \"transparent\",\n breaks = c(\"1회\", \"2회\", \"8회\", NA),\n labels = c(\"1회\", \"2회\", \"8회\", \"방문 없음\")) +\n theme_void(base_family = \"NanumGothic\") +\n theme(legend.position = \"bottom\") +\n ggrepel::geom_text_repel(\n data = pacific_country_centroid |> select(국가.x, lon, lat) |> st_drop_geometry(),\n aes(label = 국가.x, x = lon, y = lat), size = 3, segment.size = 0.2)\n```\n\n::: {.cell-output-display}\n![](chatgpt_viz_202406_files/figure-revealjs/unnamed-chunk-17-1.png){width=672}\n:::\n:::\n:::\n\n\n# 데이터 시각화 + 저널리즘 +
챗GPT\n\n## OpenAI Advanced Data Analysis {.smaller}\n\n
\n\n> Open AI Code Interpreter → Advanced Data Analysis → 챗GPT4\n\n
\n\n![](img/km_code_interpreter.png)\n\n::: aside\n[생성AI 광명시 데이터 분석\n사례](https://r2bit.com/map_challenge/km_BitGPT.html)\n:::\n\n## RStudio Copilot\n\n> `Tools -> Global Options -> Copilot -> Enable Github Copilot`\n\n![](img/rstudio_copilot.jpg)\n\n## 웹앱(Shiny App) 개발 사례\n\n![](img/shiny_app_ci.gif)\n\n## 광명시 보좌관\n\n![](img/km_ai.gif){fig-align=\"center\" width=\"728\"}\n\n- [소스코드](https://github.com/bit2r/BitStat2)\n\n## RTutor & PandasAI\n\n![](img/rtutor_pandasai.png){fig-align=\"center\" width=\"450\"}\n\n::: aside\n- [챗GPT 데이터 과학](https://r2bit.com/gpt-ds/)\n:::\n\n\n\n\n# 참고문헌\n\n::: {#refs}\n:::\n\n\n \n \n\n", + "markdown": "---\ntitle: \"챗GPT 데이터 시각화\"\nsubtitle: \"데이터 시각화 어디까지 보고 오셨어요?\"\nauthor: \"이광춘\"\ninstitute: \"한국 R 사용자회\"\ndate: 2024-06-25\nformat: \n insper-revealjs:\n self-contained: false\n footer: |\n 한국 R 사용자회 [chatGPT](https://r2bit.com/chatGPT/). theme [insper](https://github.com/padsInsper/quarto-insper-theme) 소스코드 [GitHub](https://github.com/padsInsper/quarto-insper-theme).\ndate-format: long\nlang: ko\nfilters:\n - lightbox\nlightbox: auto\nbibliography: bibliography.bib\ncsl: apa-single-spaced.csl \neditor_options: \n chunk_output_type: console\ninclude-in-header:\n - text: |\n \n---\n\n\n## 목차\n\n1. 데이터 시각화 [@Lee2018Visualization]\n\n2. 데이터 시각화 + 저널리즘\n\n3. 데이터 시각화 + 저널리즘 + 챗GPT\n\n4. 질의응답!\n\n\n\n# {background-image=\"img/meetup_logo.jpg\"}\n\n::: r-fit-text\n\n2023년 챗GPT 데이터 사이언스\n



\n:::\n\n## 서울 R 미트업 (2023년) {.smaller}\n\n::: columns\n::: column\n::: r-stack\n\n![](img/seoul-r-meetup-september.jpg){.fragment width=\"320\"}\n\n::: fragment\n![](img/seoul-r-meetup-august.jpg){.fragment width=\"320\"}\n:::\n\n\n::: fragment\n![](img/seoul-r-meetup-july.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoulr-r-meetup-june.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoul-r-meetup-202305.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoul-r-meetup-AsiaR.jpg){.fragment width=\"320\"}\n:::\n\n::: fragment\n![](img/seoul-r-meetup-202304.jpg){.fragment width=\"320\"}\n:::\n\n\n:::\n:::\n\n::: column\n## 참여와 연대\n\n- **서울R미트업 meetup.com**: [link](https://www.meetup.com/seoul-r-meetup)\n - **23년 4월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/292232899/)\n - **23년 5월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/292966674/)\n - **23년 6월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/293485362/)\n - **23년 7월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/293929603/)\n - **23년 8월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/294651161/)\n - **23년 9월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/295338359/)\n- 세계 R 미트업 현황 (Global R Meetup Dashboard): [link](https://r-community.org/usergroups/)\n- 한국 R 사용자회 (Korea R User Group): [link](https://r2bit.com/)\n- 한국 R 컨퍼런스 (Korea R Conference): [link](https://use-r.kr/)\n- 유튜브 채널 (Youtube Channel): [link](https://www.youtube.com/channel/UCW-epmIvjBEhhVXw_F0Nqbw)\n- 페이스북 그룹 (Facebook Group): [link](https://www.facebook.com/groups/tidyverse)\n:::\n:::\n\n\n\n# {background-image=\"img/meetup_logo.jpg\"}\n\n::: r-fit-text\n\n2024년 인공지능 데이터 사이언스\n



\n:::\n\n## 서울 R 미트업 {.smaller}\n\n::: columns\n::: column\n::: r-stack\n\n![](img/meetup/20240430_poster.png){.fragment width=\"320\"}\n\n::: fragment\n![](img/meetup/20240430_poster.png){.fragment width=\"320\"}\n:::\n\n\n\n:::\n:::\n\n::: column\n## 참여와 연대\n\n- **서울R미트업 meetup.com**: [link](https://www.meetup.com/seoul-r-meetup)\n - **23년 4월 서울 R 미트업**: [link](https://www.meetup.com/seoul-r-meetup/events/300281000/)\n - **23년 5월 서울 R 미트업**: [link]()\n - **23년 6월 서울 R 미트업**: [link]()\n - **23년 7월 서울 R 미트업**: [link]()\n - **23년 8월 서울 R 미트업**: [link]()\n - **23년 9월 서울 R 미트업**: [link]()\n- Resources for General Help with R - Regional R communities [link](https://contributor.r-project.org/r-help)\n- 세계 R 미트업 현황 (Global R Meetup Dashboard): [link](https://r-community.org/usergroups/)\n- 한국 R 사용자회 (Korea R User Group): [link](https://r2bit.com/)\n- 한국 R 컨퍼런스 (Korea R Conference): [link](https://use-r.kr/)\n- 유튜브 채널 (Youtube Channel): [link](https://www.youtube.com/channel/UCW-epmIvjBEhhVXw_F0Nqbw)\n- 페이스북 그룹 (Facebook Group): [link](https://www.facebook.com/groups/tidyverse)\n:::\n:::\n\n\n\n# 데이터 시각화\n\n## 정적 그래프 {.smaller}\n\n
\n\n::: {.cell .custom3070 output-location='column-fragment'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(plotly)\nlibrary(gapminder)\nlibrary(crosstalk)\nlibrary(leaflet)\nlibrary(flipbookr)\n\ngapminder %>% \n ggplot(aes(x=year, \n y=lifeExp, \n group=country)) + \n geom_line()\n```\n\n::: {.cell-output-display}\n![](chatgpt_viz_202406_files/figure-revealjs/fig-static-graph-1.png){#fig-static-graph width=672}\n:::\n:::\n\n\n## 인터랙티브 그래프 {.smaller}\n\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\np <- gapminder %>% \n ggplot(aes(x=year, \n y=lifeExp, \n group=country)) + \n geom_line()\n\nggplotly(p)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 인터랙티브 그래프 - 툴팁(Tooltip) 기능 {.smaller}\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\np <- gapminder %>% \n ggplot(aes(\n x = year, \n y = lifeExp, \n group = country, \n text = paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_line()\n\nggplotly(p, tooltip = \"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n\n## 강조(Highlight) 기능 {.smaller}\n\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\ngm_highlight <- highlight_key(gapminder, \n ~country)\n\nlife_g <- gm_highlight %>% \n ggplot(aes(\n x=year, \n y=lifeExp, \n group=country, \n text=paste0(\"대륙: \", continent, \"\\n\",\n \"국가: \", country))) + \n geom_line()\n\nlife_gg <- ggplotly(life_g, tooltip = \"text\")\nhighlight(life_gg, on = \"plotly_click\", \n selectize = TRUE, \n dynamic = TRUE, \n persistent = TRUE)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 연결뷰(Linked View) 기능 {.smaller}\n\n::: {.cell .custom3070 output-location='column-fragment' class='output'}\n\n```{.r .cell-code}\ngapminder_cjk <- gapminder %>% \n filter(country %in% c(\"China\", \"Japan\", \n \"Korea, Rep.\"))\n\ngapminder_sd <- SharedData$new(gapminder_cjk, \n ~country)\n\nlife_g <- gapminder_sd %>% \n ggplot(aes(\n x = year, \n y = lifeExp, \n group = country,\n text = paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_line() +\n geom_point() +\n facet_wrap(~country)\n\nggplotly(life_g, tooltip = \"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n\n## 삼국지 {.smaller}\n\n::: {.cell}\n\n:::\n\n\n::: {.cell output-location='slide' class='output3'}\n\n```{.r .cell-code}\nlibrary(crosstalk); library(DT)\n### 1. 공유 데이터\ngeneral_sd_df <- general_df %>% select(삼국, 무장, 무력, 지력, 통솔, 생년)\nsam_sd <- SharedData$new(general_sd_df)\n\n### 2. 제어\nsam_ctrl <- filter_checkbox(\"삼국\", \"위촉오\", sam_sd, ~삼국, inline = TRUE)\nyear_ctrl <- filter_slider(\"생년\", \"출생년도\", sam_sd, ~생년, width = \"50%\")\n\n### 3. 표\nsam_tbl <- sam_sd |> \n datatable( extensions=\"Scroller\", style=\"bootstrap\", class=\"compact\", width=\"100%\",\n options=list(deferRender=TRUE, scrollY=300, scroller=TRUE))\n\n### 4. 시각화\nforce_g <- ggplot(sam_sd, aes(x=무력, y=통솔, color=삼국,\n text = paste('이름 :', 무장, \"\\n\",\n '무력:', 무력, \"\\n\",\n '지력:', 지력, \"\\n\",\n '통솔:', 통솔, \"\\n\"))) +\n geom_point() +\n theme(legend.position = \"none\") +\n labs(x=\"무력\", y=\"통솔\") +\n scale_color_manual(values = c(\"red\", \"green\", \"blue\"))\n\nforce_gg <- ggplotly(force_g, tooltip = \"text\")\n\n### 5. 인터랙티브 시각화\nbscols(widths = c(2, 5, 5),\n list(year_ctrl, sam_ctrl),\n sam_tbl, force_gg)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
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\n```\n\n:::\n:::\n\n## 애니메이션 {.smaller}\n\n::: {.cell .custom3070 output-location='column-fragment'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(gapminder)\nlibrary(plotly)\n\nlife_g <- gapminder %>% \n ggplot(aes(\n x = gdpPercap, \n y = lifeExp, \n group = country, color=country,\n text=paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_point(alpha = 0.2) +\n geom_point() +\n facet_wrap(~continent, ncol = 2) +\n scale_x_sqrt() +\n theme(legend.position = \"none\")\n\nggplotly(life_g, tooltip=\"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 애니메이션 {.smaller}\n\n`frame= 매개변수`만 넣으면 됨.\n\n::: {.cell .custom3070 output-location='column-fragment'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(gapminder)\nlibrary(plotly)\n\nlife_g <- gapminder %>% \n ggplot(aes(\n x = gdpPercap, \n y = lifeExp, \n group = country, color=country,\n text=paste0(\"대륙: \", continent, \"\\n\", \n \"국가: \", country))) + \n geom_point(alpha = 0.2) +\n geom_point(aes(frame = year), color=\"red\") +\n facet_wrap(~continent, ncol = 2) +\n scale_x_sqrt() +\n theme(legend.position = \"none\")\n\nggplotly(life_g, tooltip=\"text\")\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 애니메이션 - 2017년 버전\n\n::: panel-tabset\n### 정적 그래프\n\n![](img/party-approval-static.png){fig-align=\"center\"}\n\n### Small Multiple\n\n![](img/party-approval-static-facet.png){fig-align=\"center\"}\n\n### 애니메이션\n\n![](img/party_approval_2017.gif){fig-align=\"center\"}\n:::\n\n::: aside\n[정적 그래프에서 부드러운 동영상 그래프까지](https://statkclee.github.io/viz/viz-animations.html)\n:::\n\n\n## `crosstalk` \n\n::: {.cell .output3 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(crosstalk); library(plotly); library(leaflet); library(palmerpenguins)\npenguins <- na.omit(penguins) # Remove missing data for simplicity\n\npenguins$longitude <- rnorm(nrow(penguins), mean = -64, sd = 0.1)\npenguins$latitude <- rnorm(nrow(penguins), mean = -64, sd = 0.1)\n\n# Create a shared data object\nsd_penguins <- SharedData$new(penguins)\n\n# Plot with plotly\npenguin_plot <- plot_ly(sd_penguins, x = ~bill_length_mm, y = ~flipper_length_mm, \n color = ~species, \n text = ~paste(\"Body Mass:\", body_mass_g), \n type = 'scatter', mode = 'markers') %>% \n add_markers() %>% highlight(\"plotly_selected\")\n\n# Map with leaflet\npenguin_map <- leaflet(sd_penguins) %>% addTiles() %>% \n addCircles(lng = ~longitude, lat = ~latitude, \n weight = 1, radius = 40, popup = ~species)\n\n# Combine both using crosstalk\nbscols(widths = c(6, 6), penguin_plot, penguin_map)\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
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\n```\n\n:::\n:::\n\n## 지도 - `BitSpatial`\n\n::: {.cell .custom3070 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(tidyverse);library(sf);library(bitSpatial);library(ggiraph)\n\nstart_gg <- bitSpatial::admi |> \n ggplot(aes(geometry = geometry)) +\n geom_sf(\n data = bitSpatial::mega,\n aes(fill = mega_nm), color = 'black', linewidth = 0.5\n ) +\n geom_sf(fill = NA, color = 'black', linewidth = 0.1)\n\n# 인터랙티브 지도\nmap_gg <- bitSpatial::admi |> \n ggplot(aes(geometry = geometry)) +\n geom_sf(\n data = bitSpatial::mega,\n aes(fill = mega_nm), color = 'black', linewidth = 0.5 ) +\n geom_sf(fill = NA, color = 'black', linewidth = 0.1 ) +\n geom_sf_interactive(fill = NA, \n aes(data_id = cty_cd, tooltip = glue::glue('{mega_nm}
{cty_nm}')),\n linewidth = 0.1\n ) +\n theme_void() +\n theme(legend.position = 'none') +\n scale_fill_manual(\n values = c(\"#A0CBE8FF\", \"#F28E2BFF\", \"#FFBE7DFF\", \"#59A14FFF\", \"#8CD17DFF\", \"#B6992DFF\", \"#F1CE63FF\", \"#499894FF\", \"#86BCB6FF\", \"#E15759FF\", \"#FF9D9AFF\", \"#79706EFF\", \"#BAB0ACFF\", \"#D37295FF\", \"#B07AA1FF\", \"#D4A6C8FF\", \"#9D7660FF\") ) \n\ngirafe(ggobj = map_gg,\n options = list(opts_hover(\n css = girafe_css(css = '', area = 'stroke: black; fill: black;'))))\n```\n\n::: {#fig-bitSpatial .cell-output-display}\n\n```{=html}\n
\n\n```\n\n:::\n:::\n\n## 로고 + 막대그래프\n\n\n::: {.cell .custom3070 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\n\ndat <- tribble( ~neo_bank, ~market_cap_bn, ~logo_url,\n \"Nubank\", 45, \"https://upload.wikimedia.org/wikipedia/commons/f/f7/Nubank_logo_2021.svg\",\n \"Revolut\", 33, \"https://upload.wikimedia.org/wikipedia/commons/d/d6/Revolut.svg\",\n \"Chime\", 25, \"https://upload.wikimedia.org/wikipedia/commons/f/f6/Chime_company_logo.svg\",\n \"WeBank\", 21, \"https://upload.wikimedia.org/wikipedia/en/e/eb/WeBank_Logo.svg\",\n \"Kakaobank\", 19, \"https://upload.wikimedia.org/wikipedia/commons/4/48/KakaoBank_logo.svg\",\n \"Robinhood\", 10, \"https://upload.wikimedia.org/wikipedia/commons/d/da/Robinhood_%28company%29_logo.svg\",\n \"SoFi\", 10, \"https://upload.wikimedia.org/wikipedia/commons/1/16/SoFi_logo.svg\",\n \"Tinkoff\", 9, \"https://upload.wikimedia.org/wikipedia/commons/1/19/Tinkoff_logo_2024.svg\",\n \"N26\", 9, \"https://upload.wikimedia.org/wikipedia/commons/b/bf/N26_logo_2019.svg\",\n \"K Bank\", 7, \"https://upload.wikimedia.org/wikipedia/commons/2/26/Kbank_logo.svg\"\n) \n\nmap(dat$logo_url, magick::image_read_svg) |>\n walk2(\n dat$neo_bank,\n \\(x, y) magick::image_write(x, path = paste0(\"img/logos/\", y, \".png\"))\n )\n\ndat |> \n mutate(neo_bank = fct_reorder(neo_bank, market_cap_bn)) |>\n ggplot(aes(x = market_cap_bn, y = neo_bank)) +\n geom_col() +\n scale_y_discrete(\n labels = \\(x) glue::glue(\"\")\n ) +\n theme_minimal(base_size = 12, base_family = 'Source Sans Pro') +\n labs(\n title = 'Top 10 neobanks worldwide by market capitalization 2022',\n y = element_blank()) +\n theme(axis.text.y = ggtext::element_markdown())\n```\n\n::: {.cell-output-display}\n![카카오뱅크와 K뱅크](chatgpt_viz_202406_files/figure-revealjs/fig-image-logo-1.png){#fig-image-logo width=672}\n:::\n:::\n\n::: aside\n\n출처: \n\n:::\n\n\n## 인터랙티브 그래프\n\n::: {.cell .custom3070 output-location='slide'}\n\n```{.r .cell-code}\nlibrary(tidyverse); library(palmerpenguins); library(ggiraph); library(patchwork)\ncolor_palette <- thematic::okabe_ito(3)\n\nscatter_gg <- penguins |> drop_na() |>\n ggplot(aes(x = flipper_length_mm, y = body_mass_g, color = species, data_id = species)) +\n geom_point_interactive(size = 1) +\n labs(title = \"펭귄의 지느러미 길이와 몸무게\",\n x = \"지느러미 길이 (mm)\", y = \"몸무게 (g)\", color = \"종\") +\n theme_minimal(base_size = 5) +\n theme(legend.position = \"top\") +\n scale_color_manual(values = color_palette) +\n scale_y_continuous(labels = scales::comma) \n\nboxplot_gg <- penguins |> drop_na() |> \n ggplot(aes(x = species, y = body_mass_g, fill = species, data_id = species)) +\n geom_boxplot_interactive() + \n geom_jitter_interactive(aes(col = species)) +\n labs(title = \"펭귄 종별 몸무게\",\n x = \"펭귄 종명\", y = \"몸무게 (g)\", color = \"종\") +\n theme_minimal(base_size = 12) +\n theme(legend.position = \"none\") +\n scale_fill_manual(values = color_palette) +\n scale_color_manual(values = color_palette) +\n scale_y_continuous(labels = scales::comma) +\n coord_flip()\n\ngirafe(\n ggobj = boxplot_gg + plot_spacer() + scatter_gg + plot_layout(widths = c(0.45, 0.1, 0.45)),\n options = list(\n opts_hover(css = ''), opts_hover_inv(css = \"opacity:0.1;\"), \n opts_sizing(rescale = FALSE)\n ))\n```\n\n::: {#fig-interactive-ggiraph .cell-output-display}\n\n```{=html}\n
\n\n```\n\n\n산점도와 상자그림\n:::\n:::\n\n\n# 데이터 시각화 + 저널리즘\n\n## 문 대통령 해외순방 {.smaller}\n\n::: panel-tabset\n### 뉴스 기사\n\n![](img/omn_viz.png){fig-align=\"center\" width=\"495\"}\n\n### 위키 데이터\n\n::: {.cell output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\nlibrary(tidyverse)\nlibrary(rvest)\n\nmoon_html <- read_html(\"https://ko.wikipedia.org/wiki/문재인의_대통령_순방_목록\")\n\nmoon_raw <- moon_html |> \n html_elements(\"table\") |> \n html_table()\n\nmoon_h3 <- moon_html |> \n html_elements(\"h3\") |> \n html_text()\n\nnames(moon_raw) <- moon_h3[1:6]\n\nmoon_tbl <- moon_h3 |> \n enframe() |> \n mutate(연도 = str_remove(value, \"년\\\\[편집\\\\]\")) |> \n filter(str_detect(연도, \"\\\\d{4}\")) |> \n mutate(data = moon_raw[c(1:5)]) |> \n unnest(data) |> \n select(연도, 나라, 장소, 일자, 세부내용=`세부 내용`) |>\n separate(일자, into = c(\"출국\", \"도착\"), sep = \"~\") |> \n mutate(도착 = ifelse(is.na(도착), 출국, 도착)) |> \n mutate(출국일 = str_glue(\"{연도}-{출국}\"),\n 도착일 = str_glue(\"{연도}-{도착}\")) |> \n mutate(출국일 = parse_date(출국일, \"%Y-%m월 %d일\"),\n 도착일 = parse_date(도착일, \"%Y-%m월 %d일\")) |> \n select(출국일, 도착일, 국가 = 나라, 장소) |> \n mutate(기간 = (출국일 %--% 도착일) / ddays(1) +1)\n\nmoon_tbl |> slice(1:5) |> gt::gt()\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n \n \n
출국일도착일국가장소기간
2017-06-282017-07-03미국워싱턴 D.C.6
2017-07-052017-07-08독일베를린, 함부르크4
2017-09-062017-09-07러시아블라디보스토크2
2017-09-192017-09-21미국뉴욕3
2017-11-082017-11-10인도네시아자카르타3
\n
\n```\n\n:::\n:::\n\n### 표\n\n::: {.cell output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\nlibrary(countrycode)\nlibrary(gt)\nlibrary(gtExtras)\n\ncountry_codes <- data.frame(\n \"국가\" = c(\"노르웨이\", \"뉴질랜드\", \"덴마크\", \"독일\", \"라오스\", \"러시아\", \"말레이시아\", \"미국\", \"미얀마\", \"바티칸 시국\", \"베트남\", \"벨기에\", \"브루나이\", \"사우디아라비아\", \"스웨덴\", \"스페인\", \"싱가포르\", \"아랍에미리트\", \"아르헨티나\", \"영국\", \"오스트레일리아\", \"오스트리아\", \"우즈베키스탄\", \"이집트\", \"이탈리아\", \"인도\", \"인도네시아\", \"일본\", \"조선민주주의인민공화국\", \"중화인민공화국\", \"체코\", \"카자흐스탄\", \"캄보디아\", \"태국\", \"투르크메니스탄\", \"파푸아뉴기니\", \"프랑스\", \"핀란드\", \"필리핀\", \"헝가리\"),\n \"영문_국가명\" = c(\"Norway\", \"New Zealand\", \"Denmark\", \"Germany\", \"Laos\", \"Russia\", \"Malaysia\", \"United States\", \"Myanmar\", \"Vatican City\", \"Vietnam\", \"Belgium\", \"Brunei\", \"Saudi Arabia\", \"Sweden\", \"Spain\", \"Singapore\", \"United Arab Emirates\", \"Argentina\", \"United Kingdom\", \"Australia\", \"Austria\", \"Uzbekistan\", \"Egypt\", \"Italy\", \"India\", \"Indonesia\", \"Japan\", \"North Korea\", \"China\", \"Czech Republic\", \"Kazakhstan\", \"Cambodia\", \"Thailand\", \"Turkmenistan\", \"Papua New Guinea\", \"France\", \"Finland\", \"Philippines\", \"Hungary\"),\n \"iso2c\" = c(\"NO\", \"NZ\", \"DK\", \"DE\", \"LA\", \"RU\", \"MY\", \"US\", \"MM\", \"VA\", \"VN\", \"BE\", \"BN\", \"SA\", \"SE\", \"ES\", \"SG\", \"AE\", \"AR\", \"GB\", \"AU\", \"AT\", \"UZ\", \"EG\", \"IT\", \"IN\", \"ID\", \"JP\", \"KP\", \"CN\", \"CZ\", \"KZ\", \"KH\", \"TH\", \"TM\", \"PG\", \"FR\", \"FI\", \"PH\", \"HU\")\n)\n\nmoon_tbl |> \n group_by(국가) |> \n summarise(방문수 = n(),\n 연도 = str_c(str_glue(\"{lubridate::year(출국일)}\"), collapse = \",\")) |> \n left_join(country_codes, by = \"국가\") |> \n mutate(대륙 = countrycode(iso2c, \"iso2c\", \"continent\")) |>\n arrange(desc(방문수)) |>\n select(-영문_국가명) |> \n select(iso2c, everything()) |> \n filter(대륙 %in% c(\"Americas\", \"Oceania\")) |> \n gt(groupname_col = \"대륙\") |> \n fmt_flag(columns = iso2c) |> \n cols_label(\n iso2c = \"\"\n ) |> \n cols_align(\"center\") |> \n tab_header(\n title = md(\"문재인 대통령 해외 순방\"),\n subtitle = md(\"2017년 5월 10일 ~ 2021년 5월 9일\")\n ) |>\ntab_footnote(\n footnote = md(\"데이터 출처: [위키백과](https://ko.wikipedia.org/wiki/문재인의_대통령_순방_목록)\")\n) |> \n gt_theme_538() |> \n ## 표 전체 합계 -------------------------------------\n grand_summary_rows(\n columns = 방문수,\n fns = list(label = \"\", fn = \"sum\"),\n fmt = ~ fmt_integer(.),\n side = \"bottom\"\n )\n```\n\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\n \n \n \n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n \n \n \n \n \n \n
문재인 대통령 해외 순방
2017년 5월 10일 ~ 2021년 5월 9일
국가방문수연도
Americas
United States미국82017,2017,2018,2018,2019,2019,2021,2021
Argentina아르헨티나12018
Oceania
New Zealand뉴질랜드12018
Australia오스트레일리아12021
Papua New Guinea파푸아뉴기니12018
12
데이터 출처: 위키백과
\n
\n```\n\n:::\n:::\n\n### 지도\n\n::: {.cell .custom7030 output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\nlibrary(viridis); library(sf); sf_use_s2(FALSE)\n\nmoon_tour <- moon_tbl |> group_by(국가) |> \n summarise(방문수 = n(),\n 연도 = str_c(str_glue(\"{lubridate::year(출국일)}\"), collapse = \",\")) |> \n left_join(country_codes, by = \"국가\")\n\nworld_map <- rnaturalearth::ne_countries(scale = 50, returnclass = \"sf\")\ncountry_centroid <- inner_join(st_centroid(world_map), moon_tour, \n by = c(\"iso_a2\" = \"iso2c\"))\n\ncountry_centroid <- bind_cols(country_centroid,\n st_coordinates(country_centroid) |> \n as_tibble() |> set_names(c(\"lon\", \"lat\")))\n\nmoon_map <- left_join(world_map, moon_tour, by = c(\"iso_a2\" = \"iso2c\"))\n\nmoon_map |> \n filter(continent != \"Antarctica\") |> \n mutate(방문수 = factor(방문수, levels = c(1, 2, 8),\n labels = c(\"1회\", \"2회\", \"8회\"))) |>\n ggplot() +\n geom_sf(aes(fill = 방문수)) +\n scale_fill_manual(values = c(\"gray50\", \"skyblue\", \"blue\"), \n na.value = \"transparent\",\n breaks = c(\"1회\", \"2회\", \"8회\", NA),\n labels = c(\"1회\", \"2회\", \"8회\", \"방문 없음\")) +\n labs(title = \"문재인 대통령 해외순방\") +\n theme_void(base_family = \"NanumGothic\") +\n theme(legend.position = \"bottom\") +\n ggrepel::geom_text_repel(\n data = country_centroid |> select(국가, lon, lat) |> st_drop_geometry(),\n aes(label = 국가, x = lon, y = lat), size = 3, segment.size = 0.2)\n```\n\n::: {.cell-output-display}\n![](chatgpt_viz_202406_files/figure-revealjs/unnamed-chunk-16-1.png){width=672}\n:::\n:::\n\n### 태평양 중심지도\n\n::: {.cell .custom7030 output-location='column-fragment' class='output-font'}\n\n```{.r .cell-code}\noffset <- 180 - 150\n\npolygon <- st_polygon(x = list(rbind(\n c(-0.0001 - offset, 90), c(0 - offset, 90),\n c(0 - offset, -90), c(-0.0001 - offset, -90),\n c(-0.0001 - offset, 90) ))) %>%\n st_sfc() %>% st_set_crs(4326)\n\nworld_pacific <- world_map |> \n st_difference(polygon) |> st_transform(crs = \"+proj=eqc +x_0=0 +y_0=0 +lat_0=0 +lon_0=150\")\n\nmoon_pacific_map <- left_join(world_pacific, moon_tour, by = c(\"iso_a2\" = \"iso2c\"))\n\npacific_centroid <- inner_join(st_centroid(moon_pacific_map), moon_tour, by = c(\"iso_a2\" = \"iso2c\"))\n\npacific_country_centroid <- bind_cols(pacific_centroid,\n st_coordinates(pacific_centroid) |> as_tibble() |> set_names(c(\"lon\", \"lat\")))\n\n\nmoon_pacific_map |> \n mutate(방문수 = factor(방문수, levels = c(1, 2, 8), labels = c(\"1회\", \"2회\", \"8회\"))) |>\n ggplot() +\n geom_sf(aes(fill = 방문수)) +\n scale_fill_manual(values = c(\"gray50\", \"skyblue\", \"blue\"), \n na.value = \"transparent\",\n breaks = c(\"1회\", \"2회\", \"8회\", NA),\n labels = c(\"1회\", \"2회\", \"8회\", \"방문 없음\")) +\n theme_void(base_family = \"NanumGothic\") +\n theme(legend.position = \"bottom\") +\n ggrepel::geom_text_repel(\n data = pacific_country_centroid |> select(국가.x, lon, lat) |> st_drop_geometry(),\n aes(label = 국가.x, x = lon, y = lat), size = 3, segment.size = 0.2)\n```\n\n::: {.cell-output-display}\n![](chatgpt_viz_202406_files/figure-revealjs/unnamed-chunk-17-1.png){width=672}\n:::\n:::\n:::\n\n## K-POP 빌보드 HOT 100 {.smaller}\n\n::: panel-tabset\n### 작업흐름\n\n```{mermaid}\n%%| fig-align: center\ngraph TD\n A[나무위키
크롤링]\n A --> C[데이터 전처리
데이터프레임]\n C --> E[Billboard API]\n C --> F[데이터 시각화
ggplot + gt]\n F --> G[대시보드
Quarto 문서 작성]\n E --> G\n G --> I[gh-pages 배포]\n```\n\n### 인포그래픽\n\n![](img/billboard_gt.png){fig-align=\"center\" width=\"378\"}\n\n### 대시보드\n\n'\n\n::: aside\n\n- [소스코드](https://github.com/statkclee/billboard)\n\n:::\n\n:::\n\n\n\n# 데이터 시각화 + 저널리즘 +
챗GPT\n\n## OpenAI Advanced Data Analysis {.smaller}\n\n
\n\n> Open AI Code Interpreter → Advanced Data Analysis → 챗GPT4\n\n
\n\n![](img/km_code_interpreter.png)\n\n::: aside\n[생성AI 광명시 데이터 분석\n사례](https://r2bit.com/map_challenge/km_BitGPT.html)\n:::\n\n## RStudio Copilot\n\n> `Tools -> Global Options -> Copilot -> Enable Github Copilot`\n\n![](img/rstudio_copilot.jpg)\n\n## 웹앱(Shiny App) 개발 사례\n\n![](img/shiny_app_ci.gif)\n\n## 광명시 보좌관\n\n![](img/km_ai.gif){fig-align=\"center\" width=\"728\"}\n\n- [소스코드](https://github.com/bit2r/BitStat2)\n\n## RTutor & PandasAI\n\n![](img/rtutor_pandasai.png){fig-align=\"center\" width=\"450\"}\n\n::: aside\n- [챗GPT 데이터 과학](https://r2bit.com/gpt-ds/)\n:::\n\n\n\n\n# 참고문헌\n\n::: {#refs}\n:::\n\n\n \n \n\n", "supporting": [ "chatgpt_viz_202406_files" ], diff --git a/_freeze/chatgpt_viz_202406/figure-revealjs/unnamed-chunk-16-1.png b/_freeze/chatgpt_viz_202406/figure-revealjs/unnamed-chunk-16-1.png index d06ad5ab0cbbe2be2ef5315f724a1ea85fffb14c..991fa859a89092ed40888be622a2beac3d831185 100644 GIT binary patch literal 103684 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a/docs/chatgpt_viz_202406.html +++ b/docs/chatgpt_viz_202406.html @@ -423,6 +423,9 @@ margin-right: 0; } + + + @@ -713,8 +716,8 @@

인터랙티브 그래프

ggplotly(p)
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@@ -735,8 +738,8 @@

인터랙티브 그래프 - 툴팁(Tooltip) 기능

ggplotly(p, tooltip = "text")
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@@ -764,8 +767,8 @@

강조(Highlight) 기능

persistent = TRUE)
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@@ -795,8 +798,8 @@

연결뷰(Linked View) 기능

ggplotly(life_g, tooltip = "text")
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@@ -849,7 +852,7 @@

삼국지

@@ -874,17 +877,17 @@

삼국지

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@@ -913,8 +916,8 @@

애니메이션

ggplotly(life_g, tooltip="text")
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@@ -944,8 +947,8 @@

애니메이션

ggplotly(life_g, tooltip="text")
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@@ -1016,12 +1019,12 @@

crosstalk

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@@ -1065,8 +1068,8 @@

지도 - BitSpatial

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그림 2 @@ -1169,8 +1172,8 @@

인터랙티브 그래프

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그림 4: 산점도와 상자그림 @@ -1238,23 +1241,23 @@

문 대통령 해외순방

-
- @@ -1781,24 +1784,24 @@

문 대통령 해외순방

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+