Een tabel toevoegen
Eerder heb je de gegevenssets die je in je rapport gebruikt, rechtstreeks afgedrukt zodat je publiek zelf door de data kon bladeren. Nu maak je een tabel van investment_region_summary om deze informatie duidelijker te tonen. investment_region_summary bevat het totaal van alle investeringen per regio voor de boekjaren 2012 tot en met 2018.
Deze oefening maakt deel uit van de cursus
Rapporteren met R Markdown
Oefeninstructies
- Laad het pakket
knitrin de gegevens-codechunk, na het pakketggplot2op regel15. - Maak in de codechunk
tables, die begint op regel44, een tabel van de datainvestment_region_summarymet kolomnamenRegionenDollars in Millionsen gecentreerde uitlijning voor beide kolommen. - Voeg de volgende bijschrifttekst toe aan de tabel:
"Table 1.1 The total investment summary for each region for the 2012 to 2018 fiscal years."
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
{"investment_report.Rmd":"---\ntitle: \"Investment Report\"\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\noutput: html_document\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# Load the knitr package here\n\ninvestment_annual_summary <- read_csv(\"https://assets.datacamp.com/production/repositories/5756/datasets/d0251f26117bbcf0ea96ac276555b9003f4f7372/investment_annual_summary.csv\")\ninvestment_region_summary <- read_csv(\"https://assets.datacamp.com/production/repositories/5756/datasets/52f5414f6504e0503e86eb1043afa9b3d157fab2/investment_region_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### Investment Annual Summary\nThe `investment_annual_summary` dataset provides a summary of the dollars in millions provided to each of the following regions for each fiscal year, from 2012 to 2018:\n\n1. East Asia and the Pacific \n2. Europe and Central Asia \n3. Latin America and the Caribbean\n4. Middle East and North Africa \n5. South Asia \n6. Sub-Saharan Africa\n\n```{r investment-annual-summary, out.width = '85%', fig.cap = 'Figure 1.1 The Investment Annual Summary for each region for 2012 to 2018.'}\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```{r tables}\n___(___, col.names = c(___), align = ___, caption = ___)\n```\n\n### Investment Projects in Brazil\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.\n\n```{r brazil-investment-projects, out.width = '95%', fig.cap = 'Figure 1.2 The Investment Services Projects in Brazil from 2012 to 2018.'}\nbrazil_investment_projects <- investment_services_projects %>%\n filter(country == \"Brazil\") \n\nggplot(brazil_investment_projects, aes(x = date_disclosed, y = total_investment, color = status)) +\n geom_point() +\n labs(\n title = \"Investment Services Projects in Brazil\",\n x = \"Date Disclosed\",\n y = \"Total IFC Investment in Dollars in Millions\"\n )\n```\n\n### Investment Projects in Brazil in 2018\nThe `investment_services_projects` dataset was filtered below to focus on information about each investment project from the 2018 fiscal year, and is referred to as `brazil_investment_projects_2018`. \n\n```{r brazil-investment-projects-2018, out.width = '95%', fig.cap = 'Figure 1.3 The Investment Services Projects in Brazil in 2018.'}\nbrazil_investment_projects_2018 <- investment_services_projects %>%\n filter(country == \"Brazil\",\n date_disclosed >= \"2017-07-01\",\n date_disclosed <= \"2018-06-30\") \n\nggplot(brazil_investment_projects_2018, aes(x = date_disclosed, y = total_investment, color = status)) +\n geom_point() +\n labs(\n title = \"Investment Services Projects in Brazil in 2018\",\n x = \"Date Disclosed\",\n y = \"Total IFC Investment in Dollars in Millions\"\n ) \n```\n\n\n"}