22 lines
93 KiB
JSON
22 lines
93 KiB
JSON
{
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"hash": "1f512aedde0c78d18d7113364c7ce0db",
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"result": {
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"engine": "knitr",
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"markdown": "---\ntitle: \"数据可视化\"\nsubtitle: 《区域水环境污染数据分析实践》<br>Data analysis practice of regional water environment pollution\nauthor: 苏命、王为东<br>中国科学院大学资源与环境学院<br>中国科学院生态环境研究中心\ndate: today\nlang: zh\nformat:\n revealjs:\n theme: dark\n slide-number: true\n chalkboard:\n buttons: true\n preview-links: auto\n lang: zh\n toc: true\n toc-depth: 1\n toc-title: 大纲\n logo: ./_extensions/inst/img/ucaslogo.png\n css: ./_extensions/inst/css/revealjs.css\n pointer:\n key: \"p\"\n color: \"#32cd32\"\n pointerSize: 18\nrevealjs-plugins:\n - pointer\nfilters:\n - d2\nknitr:\n opts_chunk:\n dev: \"svg\"\n retina: 3\nexecute:\n freeze: auto\n cache: true\n echo: true\n fig-width: 5\n fig-height: 6\n---\n\n\n\n\n\n\n## {background-image=\"../../img/concepts/tidyverse-packages-ggplot.png\" background-position=\"center\" background-size=\"100%\"}\n\n\n\n## The ggplot2 Package\n\n<br>\n\n... is an **R package to visualize data** created by Hadley Wickham in 2005\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggplot2\")\nlibrary(ggplot2)\n```\n:::\n\n\n<br>\n\n::: fragment\n... is part of the [`{tidyverse}`](https://www.tidyverse.org/)\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"tidyverse\")\nlibrary(tidyverse)\n```\n:::\n\n:::\n\n# The Grammar of {ggplot2}\n\n\n\n## The Grammar of {ggplot2}\n\n<br>\n<table style='width:100%;font-size:14pt;'>\n <tr>\n <th>Component</th>\n <th>Function</th>\n <th>Explanation</th>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Data</b></td>\n <td><code>ggplot(data)</code> </td>\n <td>*The raw data that you want to visualise.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Aesthetics </b></td>\n <td><code>aes()</code></td>\n <td>*Aesthetic mappings between variables and visual properties.*</td>\n <tr>\n <td><b style='color:#67676;'>Geometries</b></td>\n <td><code>geom_*()</code></td>\n <td>*The geometric shapes representing the data.*</td>\n </tr>\n</table>\n\n\n\n## The Grammar of {ggplot2}\n\n\n<br>\n<table style='width:100%;font-size:14pt;'>\n <tr>\n <th>Component</th>\n <th>Function</th>\n <th>Explanation</th>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Data</b></td>\n <td><code>ggplot(data)</code> </td>\n <td>*The raw data that you want to visualise.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Aesthetics </b></td>\n <td><code>aes()</code></td>\n <td>*Aesthetic mappings between variables and visual properties.*</td>\n <tr>\n <td><b style='color:#67676;'>Geometries</b></td>\n <td><code>geom_*()</code></td>\n <td>*The geometric shapes representing the data.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Statistics</b></td>\n <td><code>stat_*()</code></td>\n <td>*The statistical transformations applied to the data.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Scales</b></td>\n <td><code>scale_*()</code></td>\n <td>*Maps between the data and the aesthetic dimensions.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Coordinate System</b></td>\n <td><code>coord_*()</code></td>\n <td>*Maps data into the plane of the data rectangle.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Facets</b></td>\n <td><code>facet_*()</code></td>\n <td>*The arrangement of the data into a grid of plots.*</td>\n </tr>\n <tr>\n <td><b style='color:#67676;'>Visual Themes</b></td>\n <td><code>theme() / theme_*()</code></td>\n <td>*The overall visual defaults of a plot.*</td>\n </tr>\n</table>\n\n\n\n## The Data\n\n<b style='font-size:2.3rem;'>Bike sharing counts in London, UK, powered by [TfL Open Data](https://tfl.gov.uk/modes/cycling/santander-cycles)</b>\n\n::: incremental\n- covers the years 2015 and 2016\n- incl. weather data acquired from [freemeteo.com](https://freemeteo.com)\n- prepared by Hristo Mavrodiev for [Kaggle](https://www.kaggle.com/hmavrodiev/london-bike-sharing-dataset)\n:::\n\n<br>\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code}\nbikes <- readr::read_csv(\"../../data/ggplot2/london-bikes-custom.csv\",\n ## or: \"https://raw.githubusercontent.com/z3tt/graphic-design-ggplot2/main/data/london-bikes-custom.csv\"\n col_types = \"Dcfffilllddddc\"\n)\n\nbikes$season <- forcats::fct_inorder(bikes$season)\n```\n:::\n\n:::\n\n------------------------------------------------------------------------\n\n\n::: {.cell}\n::: {.cell-output-display}\n`````{=html}\n<table class=\"table lightable-minimal lightable-hover\" style=\"font-size: 20px; margin-left: auto; margin-right: auto; font-family: Spline Sans Mono; \">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Variable </th>\n <th style=\"text-align:left;\"> Description </th>\n <th style=\"text-align:left;\"> Class </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> date </td>\n <td style=\"text-align:left;\"> Date encoded as `YYYY-MM-DD` </td>\n <td style=\"text-align:left;\"> date </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> day_night </td>\n <td style=\"text-align:left;\"> `day` (6:00am–5:59pm) or `night` (6:00pm–5:59am) </td>\n <td style=\"text-align:left;\"> character </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> year </td>\n <td style=\"text-align:left;\"> `2015` or `2016` </td>\n <td style=\"text-align:left;\"> factor </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> month </td>\n <td style=\"text-align:left;\"> `1` (January) to `12` (December) </td>\n <td style=\"text-align:left;\"> factor </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> season </td>\n <td style=\"text-align:left;\"> `winter`, `spring`, `summer`, or `autumn` </td>\n <td style=\"text-align:left;\"> factor </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> count </td>\n <td style=\"text-align:left;\"> Sum of reported bikes rented </td>\n <td style=\"text-align:left;\"> integer </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> is_workday </td>\n <td style=\"text-align:left;\"> `TRUE` being Monday to Friday and no bank holiday </td>\n <td style=\"text-align:left;\"> logical </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> is_weekend </td>\n <td style=\"text-align:left;\"> `TRUE` being Saturday or Sunday </td>\n <td style=\"text-align:left;\"> logical </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> is_holiday </td>\n <td style=\"text-align:left;\"> `TRUE` being a bank holiday in the UK </td>\n <td style=\"text-align:left;\"> logical </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> temp </td>\n <td style=\"text-align:left;\"> Average air temperature (°C) </td>\n <td style=\"text-align:left;\"> double </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> temp_feel </td>\n <td style=\"text-align:left;\"> Average feels like temperature (°C) </td>\n <td style=\"text-align:left;\"> double </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> humidity </td>\n <td style=\"text-align:left;\"> Average air humidity (%) </td>\n <td style=\"text-align:left;\"> double </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> wind_speed </td>\n <td style=\"text-align:left;\"> Average wind speed (km/h) </td>\n <td style=\"text-align:left;\"> double </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> weather_type </td>\n <td style=\"text-align:left;\"> Most common weather type </td>\n <td style=\"text-align:left;\"> character </td>\n </tr>\n</tbody>\n</table>\n\n`````\n:::\n:::\n\n\n## `ggplot2::ggplot()`\n\n\n::: {.cell}\n\n:::\n\n\n{fig-alt=\"The help page of the ggplot() function.\" fig-width=\"175%\"}\n\n## Data\n\n\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code}\nggplot(data = bikes)\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Aesthetic Mapping（视觉映射）：`aes(.)`\n\n<br>\n\n<b class='simple-highlight-grn' style='font-size:2.6rem;'>= link variables to graphical properties</b><br><br>\n\n::: incremental\n- positions (`x`, `y`)\n- colors (`color`, `fill`)\n- shapes (`shape`, `linetype`)\n- size (`size`)\n- transparency (`alpha`)\n- groupings (`group`)\n:::\n\n## Aesthetic Mapping（视觉映射）：`aes(.)`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2|1,2\"}\nggplot(data = bikes) +\n aes(x = temp_feel, y = count)\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## <span style='color:#4758AB;'>aes</span>thetics\n\n`aes()` outside as component\n\n\n::: {.cell}\n\n```{.r .cell-code}\nggplot(data = bikes) +\n aes(x = temp_feel, y = count)\n```\n:::\n\n\n<br>\n\n::: fragment\n`aes()` inside, explicit matching\n\n\n::: {.cell}\n\n```{.r .cell-code}\nggplot(data = bikes, mapping = aes(x = temp_feel, y = count))\n```\n:::\n\n\n<br>\n:::\n\n::: fragment\n`aes()` inside, implicit matching\n\n\n::: {.cell}\n\n```{.r .cell-code}\nggplot(bikes, aes(temp_feel, count))\n```\n:::\n\n\n<br>\n:::\n\n::: fragment\n`aes()` inside, mixed matching\n\n\n::: {.cell}\n\n```{.r .cell-code}\nggplot(bikes, aes(x = temp_feel, y = count))\n```\n:::\n\n:::\n\n# Geometrical Layers \n\n## Geometries（几何图层）：geom_*\n\n<br>\n\n<b class='simple-highlight-grn' style='font-size:2.6rem;'>= interpret aesthetics as graphical representations</b><br><br>\n\n::: incremental\n- points\n- lines\n- polygons\n- text labels\n- ...\n:::\n\n## Geometries（几何图层）：geom_*\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1,2,3,4|5\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Visual Properties of Layers（图层属性）\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5,6,7,8,9,10,11|6,7,8,9,10\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n color = \"#28a87d\",\n alpha = .5,\n shape = \"X\",\n stroke = 1,\n size = 4\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Setting vs Mapping of Visual Properties\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n color = \"#28a87d\",\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n aes(color = season),\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n## Mapping Expressions\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n aes(color = temp_feel > 20),\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Filter Data\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = temp, y = temp_feel)\n ) +\n geom_point(\n aes(color = weather_type == \"clear\",\n size = count),\n shape = 18,\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Filter Data\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(\n bikes %>% filter(!is.na(weather_type)),\n aes(x = temp, y = temp_feel)\n ) +\n geom_point(\n aes(color = weather_type == \"clear\",\n size = count),\n shape = 18,\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n\n## Local vs. Global（应用至当前图层或所有图层）\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"3,6\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n aes(color = season),\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"3,4\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season)\n ) +\n geom_point(\n alpha = .5\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n## Adding More Layers\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9,10,11\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season)\n ) +\n geom_point(\n alpha = .5\n ) +\n geom_smooth(\n method = \"lm\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Global Color Encoding\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,4,9,10,11\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season)\n ) +\n geom_point(\n alpha = .5\n ) +\n geom_smooth(\n method = \"lm\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Local Color Encoding\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6,9,10,11\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n aes(color = season),\n alpha = .5\n ) +\n geom_smooth(\n method = \"lm\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## The \\`group\\` Aesthetic\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point(\n aes(color = season),\n alpha = .5\n ) +\n geom_smooth(\n aes(group = day_night),\n method = \"lm\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Set Both as Global Aesthetics\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4,5\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season,\n group = day_night)\n ) +\n geom_point(\n alpha = .5\n ) +\n geom_smooth(\n method = \"lm\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Overwrite Global Aesthetics\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4,12\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season,\n group = day_night)\n ) +\n geom_point(\n alpha = .5\n ) +\n geom_smooth(\n method = \"lm\",\n color = \"black\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n\n# Statistical Layers\n\n\n## \\`stat_\\*()\\` and \\`geom_\\*()\\`\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(bikes, aes(x = temp_feel, y = count)) +\n stat_smooth(geom = \"smooth\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(bikes, aes(x = temp_feel, y = count)) +\n geom_smooth(stat = \"smooth\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n\n## \\`stat_\\*()\\` and \\`geom_\\*()\\`\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(bikes, aes(x = season)) +\n stat_count(geom = \"bar\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(bikes, aes(x = season)) +\n geom_bar(stat = \"count\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n\n## \\`stat_\\*()\\` and \\`geom_\\*()\\`\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(bikes, aes(x = date, y = temp_feel)) +\n stat_identity(geom = \"point\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"2\"}\nggplot(bikes, aes(x = date, y = temp_feel)) +\n geom_point(stat = \"identity\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Statistical Summaries\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5|3\"}\nggplot(\n bikes, \n aes(x = season, y = temp_feel)\n ) +\n stat_summary() \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n## Statistical Summaries\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6,7\"}\nggplot(\n bikes, \n aes(x = season, y = temp_feel)\n ) +\n stat_summary(\n fun.data = mean_se, ## the default\n geom = \"pointrange\" ## the default\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n## Statistical Summaries\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5|5,6,11|6,7,8,9,10,11|7,8\"}\nggplot(\n bikes, \n aes(x = season, y = temp_feel)\n ) +\n geom_boxplot() +\n stat_summary(\n fun = mean,\n geom = \"point\",\n color = \"#28a87d\",\n size = 3\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n## Statistical Summaries\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5,6,7,8,9|7,8\"}\nggplot(\n bikes, \n aes(x = season, y = temp_feel)\n ) +\n stat_summary(\n fun = mean, \n fun.max = function(y) mean(y) + sd(y), \n fun.min = function(y) mean(y) - sd(y) \n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n\n# Extending a ggplot\n\n## Store a ggplot as Object\n\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"1,16\"}\ng <-\n ggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season,\n group = day_night)\n ) +\n geom_point(\n alpha = .5\n ) +\n geom_smooth(\n method = \"lm\",\n color = \"black\"\n )\n\nclass(g)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"gg\" \"ggplot\"\n```\n\n\n:::\n:::\n\n\n## Inspect a ggplot Object\n\n\n::: {.cell}\n\n```{.r .cell-code}\ng$data\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 1,454 × 14\n date day_night year month season count is_workday is_weekend\n <date> <chr> <fct> <fct> <fct> <int> <lgl> <lgl> \n 1 2015-01-04 day 2015 1 winter 6830 FALSE TRUE \n 2 2015-01-04 night 2015 1 winter 2404 FALSE TRUE \n 3 2015-01-05 day 2015 1 winter 14763 TRUE FALSE \n 4 2015-01-05 night 2015 1 winter 5609 TRUE FALSE \n 5 2015-01-06 day 2015 1 winter 14501 TRUE FALSE \n 6 2015-01-06 night 2015 1 winter 6112 TRUE FALSE \n 7 2015-01-07 day 2015 1 winter 16358 TRUE FALSE \n 8 2015-01-07 night 2015 1 winter 4706 TRUE FALSE \n 9 2015-01-08 day 2015 1 winter 9971 TRUE FALSE \n10 2015-01-08 night 2015 1 winter 5630 TRUE FALSE \n# ℹ 1,444 more rows\n# ℹ 6 more variables: is_holiday <lgl>, temp <dbl>, temp_feel <dbl>,\n# humidity <dbl>, wind_speed <dbl>, weather_type <chr>\n```\n\n\n:::\n:::\n\n\n## Inspect a ggplot Object\n\n\n::: {.cell}\n\n```{.r .cell-code}\ng$mapping\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nAesthetic mapping: \n* `x` -> `temp_feel`\n* `y` -> `count`\n* `colour` -> `season`\n* `group` -> `day_night`\n```\n\n\n:::\n:::\n\n\n## Extend a ggplot Object: Add Layers\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code}\ng +\n geom_rug(\n alpha = .2\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Remove a Layer from the Legend\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4\"}\ng +\n geom_rug(\n alpha = .2,\n show.legend = FALSE\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Extend a ggplot Object: Add Labels\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,3,4\"}\ng +\n xlab(\"Feels-like temperature (°F)\") +\n ylab(\"Reported bike shares\") +\n ggtitle(\"TfL bike sharing trends\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Extend a ggplot Object: Add Labels\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,3,4,5,6\"}\ng +\n labs(\n x = \"Feels-like temperature (°F)\",\n y = \"Reported bike shares\",\n title = \"TfL bike sharing trends\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Extend a ggplot Object: Add Labels\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6\"}\ng <- g +\n labs(\n x = \"Feels-like temperature (°F)\",\n y = \"Reported bike shares\",\n title = \"TfL bike sharing trends\",\n color = \"Season:\"\n )\n\ng\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Extend a ggplot Object: Add Labels\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6,7,9\"}\ng +\n labs(\n x = \"Feels-like temperature (°F)\",\n y = \"Reported bike shares\",\n title = \"TfL bike sharing trends\",\n subtitle = \"Reported bike rents versus feels-like temperature in London\",\n caption = \"Data: TfL\",\n color = \"Season:\",\n tag = \"Fig. 1\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Extend a ggplot Object: Add Labels\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"3\"}\ng +\n labs(\n x = \"\",\n caption = \"Data: TfL\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"3\"}\ng +\n labs(\n x = NULL,\n caption = \"Data: TfL\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Extend a ggplot Object: Themes\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code}\ng + theme_light()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code}\ng + theme_minimal()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n## Change the Theme Base Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,3|1,2,3,4\"}\ng + theme_light(\n base_size = 14\n)\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Set a Theme Globally\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code}\ntheme_set(theme_light())\n\ng\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Change the Theme Base Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,3|1,2,3,4\"}\ntheme_set(theme_light(\n base_size = 14\n))\n\ng\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n\n## Overwrite Specific Theme Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2|3\"}\ng +\n theme(\n panel.grid.minor = element_blank()\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Overwrite Specific Theme Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4\"}\ng +\n theme(\n panel.grid.minor = element_blank(),\n plot.title = element_text(face = \"bold\")\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Overwrite Specific Theme Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5\"}\ng +\n theme(\n panel.grid.minor = element_blank(),\n plot.title = element_text(face = \"bold\"),\n legend.position = \"top\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Overwrite Specific Theme Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5\"}\ng +\n theme(\n panel.grid.minor = element_blank(),\n plot.title = element_text(face = \"bold\"),\n legend.position = \"none\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Overwrite Specific Theme Settings\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6|2,3,4,6,7\"}\ng +\n theme(\n panel.grid.minor = element_blank(),\n plot.title = element_text(face = \"bold\"),\n legend.position = \"top\",\n plot.title.position = \"plot\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Overwrite Theme Settings Globally\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1|2,3,4,5|1,2,3,4,5,6\"}\ntheme_update(\n panel.grid.minor = element_blank(),\n plot.title = element_text(face = \"bold\"),\n legend.position = \"top\",\n plot.title.position = \"plot\"\n)\n\ng\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Save the Graphic\n\n\n::: {.cell}\n\n```{.r .cell-code}\nggsave(g, filename = \"my_plot.png\")\n```\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code}\nggsave(\"my_plot.png\")\n```\n:::\n\n:::\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code}\nggsave(\"my_plot.png\", width = 8, height = 5, dpi = 600)\n```\n:::\n\n:::\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code}\nggsave(\"my_plot.pdf\", width = 20, height = 12, unit = \"cm\", device = cairo_pdf)\n```\n:::\n\n:::\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code}\ngrDevices::cairo_pdf(\"my_plot.pdf\", width = 10, height = 7)\ng\ndev.off()\n```\n:::\n\n:::\n\n------------------------------------------------------------------------\n\n<br>\n\n{fig-alt=\"A comparison of vector and raster graphics.\" fig-width=\"150%\"}\n\n# Facets（面）\n\n## Facets（面）\n\n<br>\n\n<b class='simple-highlight-grn' style='font-size:2.6rem;'>= split variables to multiple panels</b><br><br>\n\n::: fragment\nFacets are also known as:\n\n- small multiples\n- trellis graphs\n- lattice plots\n- conditioning\n:::\n\n------------------------------------------------------------------------\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n## Setup\n\n\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1,2,3,4,5,6,7,8,9,10|12\"}\ng <-\n ggplot(\n bikes,\n aes(x = temp_feel, y = count,\n color = season)\n ) +\n geom_point(\n alpha = .3,\n guide = \"none\"\n )\n\ng\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Wrapped Facets\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1,2,3,4|2,4|3\"}\ng +\n facet_wrap(\n vars(day_night)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Wrapped Facets\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3\"}\ng +\n facet_wrap(\n ~ day_night\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Multiple Variables\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3\"}\ng +\n facet_wrap(\n ~ is_workday + day_night\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Cols + Rows\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4\"}\ng +\n facet_wrap(\n ~ day_night,\n ncol = 1\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Free Scaling\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5\"}\ng +\n facet_wrap(\n ~ day_night,\n ncol = 1,\n scales = \"free\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Free Scaling\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5\"}\ng +\n facet_wrap(\n ~ day_night,\n ncol = 1,\n scales = \"free_y\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Switch Labels\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5\"}\ng +\n facet_wrap(\n ~ day_night,\n ncol = 1,\n switch = \"x\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Gridded Facets\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,5|3,4\"}\ng +\n facet_grid(\n rows = vars(day_night),\n cols = vars(is_workday)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Gridded Facets\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3\"}\ng +\n facet_grid(\n day_night ~ is_workday\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Multiple Variables\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3\"}\ng +\n facet_grid(\n day_night ~ is_workday + season\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Free Scaling\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4\"}\ng +\n facet_grid(\n day_night ~ is_workday,\n scales = \"free\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Switch Labels\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"5\"}\ng +\n facet_grid(\n day_night ~ is_workday,\n scales = \"free\",\n switch = \"y\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Proportional Spacing\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4,5|5\"}\ng +\n facet_grid(\n day_night ~ is_workday,\n scales = \"free\",\n space = \"free\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Facet Options: Proportional Spacing\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4,5\"}\ng +\n facet_grid(\n day_night ~ is_workday,\n scales = \"free_y\",\n space = \"free_y\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1,2,3,4,5,6,7,8,9,10,11,12|8,9,10\"}\nggplot(\n diamonds,\n aes(x = carat, y = price)\n ) +\n geom_point(\n alpha = .3\n ) +\n geom_smooth(\n method = \"lm\",\n se = FALSE,\n color = \"dodgerblue\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"13,14,15,16,17\"}\nggplot(\n diamonds,\n aes(x = carat, y = price)\n ) +\n geom_point(\n alpha = .3\n ) +\n geom_smooth(\n method = \"lm\",\n se = FALSE,\n color = \"dodgerblue\"\n ) +\n facet_grid(\n cut ~ clarity,\n space = \"free_x\",\n scales = \"free_x\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet (Dark Theme Bonus)\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"19,20,21,22\"}\nggplot(\n diamonds,\n aes(x = carat, y = price)\n ) +\n geom_point(\n alpha = .3,\n color = \"white\"\n ) +\n geom_smooth(\n method = \"lm\",\n se = FALSE,\n color = \"dodgerblue\"\n ) +\n facet_grid(\n cut ~ clarity,\n space = \"free_x\",\n scales = \"free_x\"\n ) +\n theme_dark(\n base_size = 14\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n# Scales（尺度）\n\n\n\n\n\n## Scales\n\n<br>\n\n<b class='simple-highlight-grn' style='font-size:2.6rem;'>= translate between variable ranges and property ranges</b><br><br>\n\n::: incremental\n- feels-like temperature ⇄ x\n- reported bike shares ⇄ y\n- season ⇄ color\n- year ⇄ shape\n- ...\n:::\n\n## Scales\n\nThe `scale_*()` components control the properties of all the<br><b class='simple-highlight-ylw'>aesthetic dimensions mapped to the data.</b>\n\n<br>Consequently, there are `scale_*()` functions for all aesthetics such as:\n\n- **positions** via `scale_x_*()` and `scale_y_*()`\n\n- **colors** via `scale_color_*()` and `scale_fill_*()`\n\n- **sizes** via `scale_size_*()` and `scale_radius_*()`\n\n- **shapes** via `scale_shape_*()` and `scale_linetype_*()`\n\n- **transparency** via `scale_alpha_*()`\n\n## Scales\n\nThe `scale_*()` components control the properties of all the<br><b class='simple-highlight-ylw'>aesthetic dimensions mapped to the data.</b>\n\n<br>The extensions (`*`) can be filled by e.g.:\n\n- `continuous()`, `discrete()`, `reverse()`, `log10()`, `sqrt()`, `date()` for positions\n\n- `continuous()`, `discrete()`, `manual()`, `gradient()`, `gradient2()`, `brewer()` for colors\n\n- `continuous()`, `discrete()`, `manual()`, `ordinal()`, `area()`, `date()` for sizes\n\n- `continuous()`, `discrete()`, `manual()`, `ordinal()` for shapes\n\n- `continuous()`, `discrete()`, `manual()`, `ordinal()`, `date()` for transparency\n\n------------------------------------------------------------------------\n\n](../../img/concepts/continuous_discrete.png){fig-size=\"120%\" fig-align=\"center\" fig-alt=\"Allison Horsts illustration ofthe correct use of continuous versus discrete; however, in {ggplot2} these are interpeted in a different way: as quantitative and qualitative.\"}\n\n## Continuous vs. Discrete in {ggplot2}\n\n::: {layout-ncol=\"2\"}\n## Continuous:<br>quantitative or numerical data\n\n- height\n- weight\n- age\n- counts\n\n## Discrete:<br>qualitative or categorical data\n\n- species\n- sex\n- study sites\n- age group\n:::\n\n## Continuous vs. Discrete in {ggplot2}\n\n::: {layout-ncol=\"2\"}\n## Continuous:<br>quantitative or numerical data\n\n- height (continuous)\n- weight (continuous)\n- age (continuous or discrete)\n- counts (discrete)\n\n## Discrete:<br>qualitative or categorical data\n\n- species (nominal)\n- sex (nominal)\n- study site (nominal or ordinal)\n- age group (ordinal)\n:::\n\n## Aesthetics + Scales\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,4\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Aesthetics + Scales\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,4,7,8,9|7,8,9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_date() +\n scale_y_continuous() +\n scale_color_discrete()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Scales\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"7\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_continuous() +\n scale_y_continuous() +\n scale_color_discrete()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Scales\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_continuous() +\n scale_y_log10() +\n scale_color_discrete()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Scales\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_continuous() +\n scale_y_log10() +\n scale_color_viridis_d()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8,9,10|9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) + \n geom_point() +\n scale_y_continuous(\n trans = \"log10\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"7,8,9|8\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\"\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = seq(0, 60000, by = 15000)\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = 0:4*15000\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = c(0, 2:12*2500, 40000, 50000)\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8,10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares in thousands\",\n breaks = 0:4*15000,\n labels = 0:4*15\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares in thousands\",\n breaks = 0:4*15000,\n labels = paste(0:4*15000, \"bikes\")\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = 0:4*15000,\n limits = c(NA, 60000)\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = 0:4*15000,\n expand = c(0, 0)\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = -1:5*15000,\n expand = c(.5, .5) ## c(add, mult)\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = -1:5*15000,\n expand = expansion(add = 2000)\n ) \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_continuous\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_y_continuous(\n name = \"Reported bike shares\",\n breaks = 0:4*15000,\n guide = \"none\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_date\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"7,10|7,8,9,10|9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_date(\n name = NULL,\n date_breaks = \"4 months\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_date\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_date(\n name = NULL,\n date_breaks = \"20 weeks\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_date\\` with \\`strftime()\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9,10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_date(\n name = NULL,\n date_breaks = \"6 months\",\n date_labels = \"%Y/%m/%d\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_date\\` with \\`strftime()\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_x_date(\n name = NULL,\n date_breaks = \"6 months\",\n date_labels = \"%b '%y\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_discrete\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,6,9|6,7,8,9|7,8\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n scale_x_discrete(\n name = \"Period\",\n labels = c(\"Dec-Feb\", \"Mar-May\", \"Jun-Aug\", \"Sep-Nov\")\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_x\\|y_discrete\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n scale_x_discrete(\n name = \"Season\",\n expand = c(.5, 0) ## add, mult\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Discrete or Continuous?\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,5,6,7\"}\nggplot(\n bikes,\n aes(x = as.numeric(season), y = count)\n ) +\n geom_boxplot(\n aes(group = season)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Discrete or Continuous?\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"9,10,11,12,13|11|12\"}\nggplot(\n bikes,\n aes(x = as.numeric(season),\n y = count)\n ) +\n geom_boxplot(\n aes(group = season)\n ) +\n scale_x_continuous(\n name = \"Season\",\n breaks = 1:4,\n labels = levels(bikes$season)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Discrete or Continuous?\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,4\"}\nggplot(\n bikes,\n aes(x = as.numeric(season) + \n as.numeric(season) / 8,\n y = count)\n ) +\n geom_boxplot(\n aes(group = season)\n ) +\n scale_x_continuous(\n name = \"Season\",\n breaks = 1:4,\n labels = levels(bikes$season)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_color\\|fill_discrete\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"7,10|7,8,9,10|8,9\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_color_discrete(\n name = \"Season:\",\n type = c(\"#69b0d4\", \"#00CB79\", \"#F7B01B\", \"#a78f5f\")\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Inspect Assigned Colors\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1|12|14\"}\ng <- ggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_color_discrete(\n name = \"Season:\",\n type = c(\"#3ca7d9\", \"#1ec99b\", \"#F7B01B\", \"#bb7e8f\")\n )\n\ngb <- ggplot_build(g)\n\ngb$data[[1]][c(1:5, 200:205, 400:405), 1:5]\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n colour x y PANEL group\n1 #3ca7d9 16439 6830 1 1\n2 #3ca7d9 16439 2404 1 1\n3 #3ca7d9 16440 14763 1 1\n4 #3ca7d9 16440 5609 1 1\n5 #3ca7d9 16441 14501 1 1\n200 #1ec99b 16538 8830 1 2\n201 #1ec99b 16539 24019 1 2\n202 #1ec99b 16539 10500 1 2\n203 #1ec99b 16540 25640 1 2\n204 #1ec99b 16540 11830 1 2\n205 #1ec99b 16541 22216 1 2\n400 #F7B01B 16638 12079 1 3\n401 #F7B01B 16639 26646 1 3\n402 #F7B01B 16639 12446 1 3\n403 #F7B01B 16640 11312 1 3\n404 #F7B01B 16640 4722 1 3\n405 #F7B01B 16641 22748 1 3\n```\n\n\n:::\n:::\n\n\n## \\`scale_color\\|fill_discrete\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1,2,3,4,5,6|1,16\"}\nmy_colors <- c(\n `winter` = \"#3c89d9\",\n `spring` = \"#1ec99b\",\n `summer` = \"#F7B01B\",\n `autumn` = \"#a26e7c\"\n)\n\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_color_discrete(\n name = \"Season:\",\n type = my_colors\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_color\\|fill_discrete\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,5|1,16\"}\nmy_colors_alphabetical <- c(\n `autumn` = \"#a26e7c\",\n `spring` = \"#1ec99b\",\n `summer` = \"#F7B01B\",\n `winter` = \"#3c89d9\"\n)\n\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_color_discrete(\n name = \"Season:\",\n type = my_colors_alphabetical\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_color\\|fill_discrete\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1|11,12,13\"}\nlibrary(RColorBrewer)\n\nggplot(\n bikes,\n aes(x = date, y = count,\n color = season)\n ) +\n geom_point() +\n scale_color_discrete(\n name = \"Season:\",\n type = brewer.pal(\n n = 4, name = \"Dark2\"\n )\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_color\\|fill_manual\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"4,9,10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = weather_type)\n ) +\n geom_point() +\n scale_color_manual(\n name = \"Season:\",\n values = brewer.pal(n = 6, name = \"Pastel1\"),\n na.value = \"black\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## \\`scale_color\\|fill_carto_d\\`\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"7,8,9,10\"}\nggplot(\n bikes,\n aes(x = date, y = count,\n color = weather_type)\n ) +\n geom_point() +\n rcartocolor::scale_color_carto_d(\n name = \"Season:\",\n palette = \"Pastel\",\n na.value = \"black\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"1|10|20\"}\nfacet <-\n ggplot(\n diamonds,\n aes(x = carat, y = price)\n ) +\n geom_point(\n alpha = .3\n ) +\n geom_smooth(\n aes(color = cut),\n method = \"lm\",\n se = FALSE\n ) +\n facet_grid(\n cut ~ clarity,\n space = \"free_x\",\n scales = \"free_x\"\n )\n\nfacet\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code}\nfacet +\n scale_x_continuous(\n breaks = 0:5\n ) +\n scale_y_continuous(\n limits = c(0, 30000),\n breaks = 0:3*10000,\n labels = c(\"$0\", \"$10,000\", \"$20,000\", \"$30,000\")\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8,9,10,11,12,13,14\"}\nfacet +\n scale_x_continuous(\n breaks = 0:5\n ) +\n scale_y_continuous(\n limits = c(0, 30000),\n breaks = 0:3*10000,\n labels = paste0(\n \"$\", format(\n 0:3*10000, \n big.mark = \",\", \n trim = TRUE\n )\n )\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8,9,10,11,12,13\"}\nfacet +\n scale_x_continuous(\n breaks = 0:5\n ) +\n scale_y_continuous(\n limits = c(0, 30000),\n breaks = 0:3*10000,\n labels = function(y) paste0(\n \"$\", format(\n y, big.mark = \",\",\n trim = TRUE\n )\n )\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8\"}\nfacet +\n scale_x_continuous(\n breaks = 0:5\n ) +\n scale_y_continuous(\n limits = c(0, 30000),\n breaks = 0:3*10000,\n labels = scales::dollar_format()\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"10,11,12,13\"}\nfacet +\n scale_x_continuous(\n breaks = 0:5\n ) +\n scale_y_continuous(\n limits = c(0, 30000),\n breaks = 0:3*10000,\n labels = scales::dollar_format()\n ) +\n scale_color_brewer(\n palette = \"Set2\",\n guide = \"none\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Diamonds Facet\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"13,14,15\"}\nfacet +\n scale_x_continuous(\n breaks = 0:5\n ) +\n scale_y_continuous(\n limits = c(0, 30000),\n breaks = 0:3*10000,\n labels = scales::dollar_format()\n ) +\n scale_color_brewer(\n palette = \"Set2\"\n ) +\n theme(\n legend.position = \"none\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n# Coordinate Systems（投影）\n\n## Coordinate Systems\n\n<br>\n\n<b class='simple-highlight-grn' style='font-size:2.6rem;'>= interpret the position aesthetics</b><br><br>\n\n::: incremental\n- **linear coordinate systems:** preserve the geometrical shapes\n - `coord_cartesian()`\n - `coord_fixed()`\n - `coord_flip()`\n- **non-linear coordinate systems:** likely change the geometrical shapes\n - `coord_polar()`\n - `coord_map()` and `coord_sf()`\n - `coord_trans()`\n:::\n\n## Cartesian Coordinate System\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n coord_cartesian()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Cartesian Coordinate System\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6,7,8\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n coord_cartesian(\n ylim = c(NA, 15000)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Changing Limits\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6,7,8\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n coord_cartesian(\n ylim = c(NA, 15000)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6,7,8\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n scale_y_continuous(\n limits = c(NA, 15000)\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Clipping\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"8\"}\nggplot(\n bikes,\n aes(x = season, y = count)\n ) +\n geom_boxplot() +\n coord_cartesian(\n ylim = c(NA, 15000),\n clip = \"off\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Clipping\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"2,3|6,7,8,9,10|12\"}\nggplot(\n filter(bikes, is_holiday == TRUE),\n aes(x = temp_feel, y = count)\n ) +\n geom_point() +\n geom_text(\n aes(label = season),\n nudge_x = .3,\n hjust = 0\n ) +\n coord_cartesian(\n clip = \"off\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## ... or better use {ggrepel}\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n filter(bikes, is_holiday == TRUE),\n aes(x = temp_feel, y = count)\n ) +\n geom_point() +\n ggrepel::geom_text_repel(\n aes(label = season),\n nudge_x = .3,\n hjust = 0\n ) +\n coord_cartesian(\n clip = \"off\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Remove All Padding\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"7|8\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = count)\n ) +\n geom_point() +\n coord_cartesian(\n expand = FALSE,\n clip = \"off\"\n )\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Fixed Coordinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = temp)\n ) +\n geom_point() +\n coord_fixed()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp_feel, y = temp)\n ) +\n geom_point() +\n coord_fixed(ratio = 4)\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n## Flipped Coordinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = weather_type)\n ) +\n geom_bar() +\n coord_cartesian()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = weather_type)\n ) +\n geom_bar() +\n coord_flip()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Flipped Coordinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"3,6\"}\nggplot(\n bikes,\n aes(y = weather_type)\n ) +\n geom_bar() +\n coord_cartesian()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"3,6\"}\nggplot(\n bikes,\n aes(x = weather_type)\n ) +\n geom_bar() +\n coord_flip()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Reminder: Sort Your Bars!\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3|2\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(y = fct_infreq(weather_type))\n ) +\n geom_bar()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Reminder: Sort Your Bars!\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"3,4,5\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(y = fct_rev(\n fct_infreq(weather_type)\n ))\n ) +\n geom_bar()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Circular Corrdinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = weather_type,\n fill = weather_type)\n ) +\n geom_bar() +\n coord_polar()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = weather_type,\n fill = weather_type)\n ) +\n geom_bar() +\n coord_cartesian()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n## Circular Cordinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6,7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = fct_infreq(weather_type),\n fill = weather_type)\n ) +\n geom_bar(width = 1) +\n coord_polar()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6,7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = fct_infreq(weather_type),\n fill = weather_type)\n ) +\n geom_bar(width = 1) +\n coord_cartesian()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Circular Corrdinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = fct_infreq(weather_type),\n fill = weather_type)\n ) +\n geom_bar() +\n coord_polar(theta = \"x\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = fct_infreq(weather_type),\n fill = weather_type)\n ) +\n geom_bar() +\n coord_polar(theta = \"y\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Circular Corrdinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"5\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = 1, fill = weather_type)\n ) +\n geom_bar(position = \"stack\") +\n coord_polar(theta = \"y\") \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"5\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = 1, fill = weather_type)\n ) +\n geom_bar(position = \"stack\") +\n coord_cartesian() \n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Circular Corrdinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"4,6,7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = 1,\n fill = fct_rev(fct_infreq(weather_type)))\n ) +\n geom_bar(position = \"stack\") +\n coord_polar(theta = \"y\") +\n scale_fill_discrete(name = NULL)\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"4,6,7\"}\nggplot(\n filter(bikes, !is.na(weather_type)),\n aes(x = 1,\n fill = fct_rev(fct_infreq(weather_type)))\n ) +\n geom_bar(position = \"stack\") +\n coord_cartesian() +\n scale_fill_discrete(name = NULL)\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n\n## Transform a Coordinate System\n\n\n::: {.cell output-location='column'}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp, y = count)\n ) +\n geom_point() +\n coord_trans(y = \"log10\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n## Transform a Coordinate System\n\n::: {layout-ncol=\"2\"}\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp, y = count,\n group = day_night)\n ) +\n geom_point() +\n geom_smooth(method = \"lm\") +\n coord_trans(y = \"log10\")\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n\n::: fragment\n\n::: {.cell}\n\n```{.r .cell-code code-line-numbers=\"6\"}\nggplot(\n bikes,\n aes(x = temp, y = count,\n group = day_night)\n ) +\n geom_point() +\n geom_smooth(method = \"lm\") +\n scale_y_log10()\n```\n\n::: {.cell-output-display}\n{width=480}\n:::\n:::\n\n:::\n:::\n\n\n# 图形组合\n\n------------------------------------------------------------------------\n\n](../../img/layout/ah_patchwork.jpg){fig-align=\"center\" fig-alt=\"Allison Horsts monster illustration of the patchwork extension package.\"}\n\n::: footer\n:::\n\n------------------------------------------------------------------------\n\n::: panel-tabset\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=960}\n:::\n:::\n\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntheme_std <- theme_set(theme_minimal(base_size = 18))\ntheme_update(\n # text = element_text(family = \"Pally\"),\n panel.grid = element_blank(),\n axis.text = element_text(color = \"grey50\", size = 12),\n axis.title = element_text(color = \"grey40\", face = \"bold\"),\n axis.title.x = element_text(margin = margin(t = 12)),\n axis.title.y = element_text(margin = margin(r = 12)),\n axis.line = element_line(color = \"grey80\", size = .4),\n legend.text = element_text(color = \"grey50\", size = 12),\n plot.tag = element_text(size = 40, margin = margin(b = 15)),\n plot.background = element_rect(fill = \"white\", color = \"white\")\n)\n\nbikes_sorted <-\n bikes %>%\n filter(!is.na(weather_type)) %>%\n group_by(weather_type) %>%\n mutate(sum = sum(count)) %>%\n ungroup() %>%\n mutate(\n weather_type = forcats::fct_reorder(\n str_to_title(str_wrap(weather_type, 5)), sum\n )\n )\n\np1 <- ggplot(\n bikes_sorted,\n aes(x = weather_type, y = count, color = weather_type)\n ) +\n geom_hline(yintercept = 0, color = \"grey80\", size = .4) +\n stat_summary(\n geom = \"point\", fun = \"sum\", size = 12\n ) +\n stat_summary(\n geom = \"linerange\", ymin = 0, fun.max = function(y) sum(y),\n size = 2, show.legend = FALSE\n ) +\n coord_flip(ylim = c(0, NA), clip = \"off\") +\n scale_y_continuous(\n expand = c(0, 0), limits = c(0, 8500000),\n labels = scales::comma_format(scale = .0001, suffix = \"K\")\n ) +\n scale_color_viridis_d(\n option = \"magma\", direction = -1, begin = .1, end = .9, name = NULL,\n guide = guide_legend(override.aes = list(size = 7))\n ) +\n labs(\n x = NULL, y = \"Sum of reported bike shares\", tag = \"P1\",\n ) +\n theme(\n axis.line.y = element_blank(),\n axis.text.y = element_text(family = \"Pally\", color = \"grey50\", face = \"bold\",\n margin = margin(r = 15), lineheight = .9)\n )\n\np1\n```\n:::\n\n:::\n\n------------------------------------------------------------------------\n\n::: panel-tabset\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=960}\n:::\n:::\n\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np2 <- bikes_sorted %>%\n filter(season == \"winter\", is_weekend == TRUE, day_night == \"night\") %>%\n group_by(weather_type, .drop = FALSE) %>%\n mutate(id = row_number()) %>%\n ggplot(\n aes(x = weather_type, y = id, color = weather_type)\n ) +\n geom_point(size = 4.5) +\n scale_color_viridis_d(\n option = \"magma\", direction = -1, begin = .1, end = .9, name = NULL,\n guide = guide_legend(override.aes = list(size = 7))\n ) +\n labs(\n x = NULL, y = \"Reported bike shares on\\nweekend winter nights\", tag = \"P2\",\n ) +\n coord_cartesian(ylim = c(.5, NA), clip = \"off\")\n\np2\n```\n:::\n\n:::\n\n------------------------------------------------------------------------\n\n::: panel-tabset\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=960}\n:::\n:::\n\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\nmy_colors <- c(\"#cc0000\", \"#000080\")\n\np3 <- bikes %>%\n group_by(week = lubridate::week(date), day_night, year) %>%\n summarize(count = sum(count)) %>%\n group_by(week, day_night) %>%\n mutate(avg = mean(count)) %>%\n ggplot(aes(x = week, y = count, group = interaction(day_night, year))) +\n geom_line(color = \"grey65\", size = 1) +\n geom_line(aes(y = avg, color = day_night), stat = \"unique\", size = 1.7) +\n annotate(\n geom = \"text\", label = c(\"Day\", \"Night\"), color = my_colors,\n x = c(5, 18), y = c(125000, 29000), size = 8, fontface = \"bold\", family = \"Pally\"\n ) +\n scale_x_continuous(breaks = c(1, 1:10*5)) +\n scale_y_continuous(labels = scales::comma_format()) +\n scale_color_manual(values = my_colors, guide = \"none\") +\n labs(\n x = \"Week of the Year\", y = \"Reported bike shares\\n(cumulative # per week)\", tag = \"P3\",\n )\n\np3\n```\n:::\n\n:::\n\n## {patchwork}\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code code-line-numbers=\"3|2,3\"}\n# install.packages(\"patchwork\")\nrequire(patchwork)\n(p1 + p2) / p3\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## \"Collect Guides\"\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\n(p1 + p2) / p3 + plot_layout(guides = \"collect\")\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Apply Theming\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\n((p1 + p2) / p3 & theme(legend.justification = \"top\")) +\nplot_layout(guides = \"collect\")\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Apply Theming\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\n(p1 + p2) / p3 & theme(legend.position = \"none\",\n plot.background = element_rect(color = \"black\", size = 3))\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Adjust Widths and Heights\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code code-line-numbers=\"2\"}\n((p1 + p2) / p3 & theme(legend.position = \"none\")) +\n plot_layout(heights = c(.2, .1), widths = c(2, 1))\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Use A Custom Layout\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code code-line-numbers=\"1,2,3,4|5\"}\npicasso <- \"\nAAAAAA#BBBB\nCCCCCCCCC##\nCCCCCCCCC##\"\n(p1 + p2 + p3 & theme(legend.position = \"none\")) +\nplot_layout(design = picasso)\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Add Labels\n\n\n::: {.cell}\n\n```{.r .cell-code}\npl1 <- p1 + labs(tag = NULL, title = \"Plot One\") + theme(legend.position = \"none\")\npl2 <- p2 + labs(tag = NULL, title = \"Plot Two\") + theme(legend.position = \"none\")\npl3 <- p3 + labs(tag = NULL, title = \"Plot Three\") + theme(legend.position = \"none\")\n```\n:::\n\n\n## Add Labels\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code code-line-numbers=\"2\"}\n(pl1 + pl2) / pl3 +\n plot_annotation(tag_levels = \"1\",\n tag_prefix = \"P\",\n title = \"An overarching title for all 3 plots, placed on the very top while all other titles are sitting below the tags.\")\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Add Text\n\n::: panel-tabset\n### Graphic\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n{fig-align='center' width=864}\n:::\n:::\n\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntext <- tibble::tibble(\n x = 0, y = 0, label = \"Lorem ipsum dolor sit amet, **consectetur adipiscing elit**, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation <b style='color:#000080;'>ullamco laboris nisi</b> ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat <b style='color:#cc0000;'>cupidatat non proident</b>, sunt in culpa qui officia deserunt mollit anim id est laborum.\"\n)\npt <- ggplot(text, aes(x = x, y = y)) +\n ggtext::geom_textbox(\n aes(label = label),\n box.color = NA, width = unit(23, \"lines\"),\n color = \"grey40\", size = 6.5, lineheight = 1.4\n ) +\n coord_cartesian(expand = FALSE, clip = \"off\") +\n theme_void()\npt\n```\n:::\n\n:::\n\n## Add Text\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\n(p1 + pt) / p3\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n## Add Inset Plots\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\npl1 + inset_element(pl2,\n l = .6, b = .1, r = 1, t = .6)\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1152}\n:::\n:::\n\n\n## Add Inset Plots\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\npl1 + inset_element(pl2,\n l = .6, b = 0, r = 1, t = .5, align_to = 'full')\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1152}\n:::\n:::\n\n\n## Add Inset Plots\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\n(pl1 + inset_element(pl2,\n l = .6, b = .1, r = 1, t = .6) + pt) / pl3\n```\n\n::: {.cell-output-display}\n{fig-align='center' width=1440}\n:::\n:::\n\n\n\n## 练习\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(palmerpenguins)\nlibrary(ggthemes)\npenguins\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 344 × 8\n species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g\n <fct> <fct> <dbl> <dbl> <int> <int>\n 1 Adelie Torgersen 39.1 18.7 181 3750\n 2 Adelie Torgersen 39.5 17.4 186 3800\n 3 Adelie Torgersen 40.3 18 195 3250\n 4 Adelie Torgersen NA NA NA NA\n 5 Adelie Torgersen 36.7 19.3 193 3450\n 6 Adelie Torgersen 39.3 20.6 190 3650\n 7 Adelie Torgersen 38.9 17.8 181 3625\n 8 Adelie Torgersen 39.2 19.6 195 4675\n 9 Adelie Torgersen 34.1 18.1 193 3475\n10 Adelie Torgersen 42 20.2 190 4250\n# ℹ 334 more rows\n# ℹ 2 more variables: sex <fct>, year <int>\n```\n\n\n:::\n:::\n\n\n## 效果\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(\n data = penguins,\n mapping = aes(x = flipper_length_mm, y = body_mass_g)\n) +\n geom_point(aes(color = species, shape = species)) +\n geom_smooth(method = \"lm\") +\n labs(\n title = \"Body mass and flipper length\",\n subtitle = \"Dimensions for Adelie, Chinstrap, and Gentoo Penguins\",\n x = \"Flipper length (mm)\", y = \"Body mass (g)\",\n color = \"Species\", shape = \"Species\"\n ) +\n scale_color_colorblind()\n```\n:::\n\n\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(\n data = penguins,\n mapping = aes(x = flipper_length_mm, y = body_mass_g)) +\n geom_point(aes(color = bill_depth_mm)) +\n geom_smooth()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(\n data = penguins,\n mapping = aes(x = flipper_length_mm, y = body_mass_g, color = island)\n) +\n geom_point() +\n geom_smooth(se = FALSE)\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 分层展示\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(\n data = penguins,\n mapping = aes(x = flipper_length_mm, y = body_mass_g)\n) +\n geom_point() +\n geom_smooth()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 柱状图\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins, aes(x = species)) +\n geom_bar()\n```\n:::\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 柱状图\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins, aes(x = fct_infreq(species))) +\n geom_bar()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n\n## 直方图\n\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins, aes(x = body_mass_g)) +\n geom_histogram(binwidth = 200)\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 直方图\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell layout-ncol=\"2\"}\n\n```{.r .cell-code}\np1 <- ggplot(penguins, aes(x = body_mass_g)) +\n geom_histogram(binwidth = 20)\np2 <- ggplot(penguins, aes(x = body_mass_g)) +\n geom_histogram(binwidth = 2000)\np <- p1 + p2\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=960}\n:::\n:::\n\n\n::::\n\n## 密度图\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins, aes(x = body_mass_g)) +\n geom_density()\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n\n## 箱图\n\n\n:::: {.panel-tabset}\n\n### Code\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = species, y = body_mass_g)) +\n geom_boxplot()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 分组\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = body_mass_g, color = species)) +\n geom_density(linewidth = 0.75)\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 分组\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = body_mass_g, color = species, fill = species)) +\n geom_density(alpha = 0.5)\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n\n## 分组\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = island, fill = species)) +\n geom_bar()\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n\n## 分组\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = island, fill = species)) +\n geom_bar(position = \"fill\")\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 分组\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = flipper_length_mm, y = body_mass_g)) +\n geom_point()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 分组\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = flipper_length_mm, y = body_mass_g)) +\n geom_point(aes(color = species, shape = island))\n```\n:::\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n\n## 分面\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = flipper_length_mm, y = body_mass_g)) +\n geom_point(aes(color = species, shape = species)) +\n facet_wrap(~island)\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 分面\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(\n data = penguins,\n mapping = aes(\n x = bill_length_mm, y = bill_depth_mm, \n color = species, shape = species\n )\n) +\n geom_point() +\n labs(color = \"Species\")\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell layout-ncol=\"2\"}\n\n```{.r .cell-code}\np1 <- ggplot(penguins, aes(x = island, fill = species)) +\n geom_bar(position = \"fill\")\np2 <- ggplot(penguins, aes(x = species, fill = island)) +\n geom_bar(position = \"fill\")\np <- p1 + p2\n```\n:::\n\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=960}\n:::\n:::\n\n\n::::\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(penguins,\n aes(x = flipper_length_mm, y = body_mass_g)) +\n geom_point()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 练习\n\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(mpg, aes(x = class)) +\ngeom_bar()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(mpg, aes(x = cty, y = hwy)) +\ngeom_point()\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 练习\n\n:::: {.panel-tabset}\n\n### Code\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- ggplot(data = mpg) +\ngeom_point(mapping = aes(x = displ, y = hwy))\n```\n:::\n\n\n### Graphic\n\n\n::: {.cell}\n::: {.cell-output-display}\n{width=768}\n:::\n:::\n\n\n::::\n\n## 欢迎讨论！{.center}\n\n\n[<svg viewBox=\"0 0 576 512\" style=\"height:1em;position:relative;display:inline-block;top:.1em;\" xmlns=\"http://www.w3.org/2000/svg\">\n <path d=\"M280.37 148.26L96 300.11V464a16 16 0 0 0 16 16l112.06-.29a16 16 0 0 0 15.92-16V368a16 16 0 0 1 16-16h64a16 16 0 0 1 16 16v95.64a16 16 0 0 0 16 16.05L464 480a16 16 0 0 0 16-16V300L295.67 148.26a12.19 12.19 0 0 0-15.3 0zM571.6 251.47L488 182.56V44.05a12 12 0 0 0-12-12h-56a12 12 0 0 0-12 12v72.61L318.47 43a48 48 0 0 0-61 0L4.34 251.47a12 12 0 0 0-1.6 16.9l25.5 31A12 12 0 0 0 45.15 301l235.22-193.74a12.19 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