引用 CSS 文件
与其在每个 Markdown 文件中逐一添加样式，您可以创建一个层叠样式表（CSS）文件，并在每次新建包含特定样式和字体的文件时引用它。
在本练习中，您已将需要的样式添加到名为 styles.css 的 CSS 文件中。您将把该文件引用到 YAML 头部中，而不是在 Markdown 文件内直接指定样式。
本练习是课程的一部分
使用 R Markdown 生成报告
练习说明
- 在
html_document字段之后、toc字段之前，向 YAML 头部添加一个css字段。 - 列出包含您为该 Markdown 文件指定样式的 CSS 文件名
styles.css。
交互式实操练习
通过完成这段示例代码来试试这个练习。
{"investment_report.Rmd":"---\ntitle: \"Investment Report for Projects in `r params$country`\"\noutput: \n html_document:\n toc: true\n toc_float: true\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\nparams:\n country: Brazil\n year_start: 2017-07-01\n year_end: 2018-06-30\n fy: 2018\n---\n\n```{r setup, include = FALSE}\nknitr::opts_chunk$set(fig.align = 'center', echo = TRUE)\n```\n\n```{r data, include = FALSE}\nlibrary(readr)\nlibrary(dplyr)\nlibrary(ggplot2)\n\ninvestment_annual_summary <- read_csv(\"https://assets.datacamp.com/production/repositories/5756/datasets/d0251f26117bbcf0ea96ac276555b9003f4f7372/investment_annual_summary.csv\")\ninvestment_services_projects <- read_csv(\"https://assets.datacamp.com/production/repositories/5756/datasets/bcb2e39ecbe521f4b414a21e35f7b8b5c50aec64/investment_services_projects.csv\")\n```\n\n\n## Datasets \n\n### Investment Annual Summary\nThe `investment_annual_summary` dataset provides a summary of the dollars in millions provided to each region for each fiscal year, from 2012 to 2018.\n```{r investment-annual-summary}\nggplot(investment_annual_summary, aes(x = fiscal_year, y = dollars_in_millions, color = region)) +\n geom_line() +\n labs(\n title = \"Investment Annual Summary\",\n x = \"Fiscal Year\",\n y = \"Dollars in Millions\"\n )\n```\n\n### Investment Projects in `r params$country`\nThe `investment_services_projects` dataset provides information about each investment project from 2012 to 2018. Information listed includes the project name, company name, sector, project status, and investment amounts. Projects that do not have an associated investment amount are excluded from the plot.\n\n```{r country-investment-projects}\ncountry_investment_projects <- investment_services_projects %>%\n filter(country == params$country) \n\nggplot(country_investment_projects, aes(x = date_disclosed, y = total_investment, color = status)) +\n geom_point() +\n labs(\n title = \"Investment Services Projects\",\n x = \"Date Disclosed\",\n y = \"Total IFC Investment in Dollars in Millions\"\n )\n```\n\n### Investment Projects in `r params$country` in `r params$fy`\nThe `investment_services_projects` dataset was filtered below to focus on information about each investment project from the `r params$fy` fiscal year, and is referred to as `country_annual_investment_projects`. Projects that do not have an associated investment amount are excluded from the plot.\n```{r country-annual-investment-projects}\ncountry_annual_investment_projects <- investment_services_projects %>%\n filter(country == params$country,\n date_disclosed >= params$year_start,\n date_disclosed <= params$year_end) \n\nggplot(country_annual_investment_projects, aes(x = date_disclosed, y = total_investment, color = status)) +\n geom_point() +\n labs(\n title = \"Investment Services Projects\",\n x = \"Date Disclosed\",\n y = \"Total IFC Investment in Dollars in Millions\"\n ) \n```\n\n\n","styles.css":"#TOC {\n color: #708090;\n font-family: Calibri;\n font-size: 16px; \n border-color: #708090;\n}\nh1.title {\n color: #F08080;\n background-color: #F5F5F5;\n opacity: 0.6;\n font-family: Calibri;\n font-size: 20px;\n}\nh4.author {\n color: #708090;\n font-family: Calibri;\n background-color: #F5F5F5;\n}\nh4.date {\n color: #708090; \n font-family: Calibri;\n background-color: #F5F5F5;\n}\nbody {\n color: #708090;\n font-family: Calibri;\n background-color: #F5F5F5;\n}\npre {\n color: #708090;\n background-color: #F8F8FF;\n}\n\n\n"}