CSS ファイルを参照する
各 Markdown ファイルの中に都度スタイルを追加するのではなく、あらかじめ用意した Cascading Style Sheet (CSS) ファイルを参照することで、特定のスタイルやフォントを新しいファイル作成時に毎回適用できます。
この演習では、指定したスタイルを styles.css という CSS ファイルにまとめてあります。Markdown ファイル内でスタイルを記述する代わりに、YAML ヘッダーでこのファイルを参照します。
この演習はコースの一部です
R Markdown でレポート作成
演習の手順
html_documentフィールドの後、tocフィールドの前に、YAML ヘッダーへcssフィールドを追加します。- Markdown ファイル用に指定したスタイルを含む CSS ファイル名
styles.cssを記述します。
実践的なインタラクティブ演習
このサンプルコードを完成させて、この演習に挑戦してみましょう。
{"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"}