Customizing the title, author, and date
Previously, you modified the header of the document using the #header section. Now, you'll practice customizing the title, author, and date sections individually.
Cet exercice fait partie du cours
Reporting with R Markdown
Instructions
- Replace the #headername withh1.title, so that these settings apply to the title instead of the header of the document.
- Add sections for the author and date, using h4.authorandh4.dateto refer to each section.
- For the author and date sections, add #708090for the text color,Calibrifor the font, and#F5F5F5for the background color.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
{"investment_report.Rmd":"---\ntitle: \"Investment Report for Projects in `r params$country`\"\noutput: \n  html_document:\n    toc: true\n    toc_float: true\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\nparams:\n  country: Brazil\n  year_start: 2017-07-01\n  year_end: 2018-06-30\n  fy: 2018\n---\n\n\n\n```{r setup, include = FALSE}\nknitr::opts_chunk$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"}