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Nachdem die Abbildungen angepasst wurden, fügst du Bildunterschriften hinzu, um die Abbildungen zu beschriften und kurz zu erklären, was in den einzelnen Plots zu sehen ist.

Diese Übung ist Teil des Kurses

<Kurs>Berichten mit R Markdown</Kurs>
Kurs ansehen

Übungsanweisungen

  • Füge die Bildunterschrift 'Abbildung 1.1 Die jährliche Investment-Zusammenfassung für jede Region von 2012 bis 2018' zur Abbildung im Chunk investment-annual-summary hinzu.
  • Füge die Bildunterschrift 'Abbildung 1.2 Die Investment Services Projects in Brasilien von 2012 bis 2018' zum Chunk brazil-investment-projects hinzu.
  • Füge die Bildunterschrift 'Abbildung 1.3 Die Investment Services Projects in Brasilien im Jahr 2018' zur Abbildung im Chunk brazil-investment-projects-2018 hinzu.

Interaktive praktische Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

{"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\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\n\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, out.width = '85%', ___ = ___}\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 Brazil\n\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```{r brazil-investment-projects, out.width = '95%', ___ = ___}\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\n\n```{r brazil-investment-projects-2018, out.width = '95%', ___ = ___}\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"}
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