EmpezarEmpieza gratis

Visualizar todos los proyectos de un país y un año

Ahora vas a crear un gráfico de líneas usando los datos filtrados para todos los proyectos que se llevaron a cabo en Brasil en el ejercicio fiscal de 2018. En los ejercicios anteriores, las etiquetas ya estaban añadidas. Al crear este gráfico, practicarás cómo añadir tus propias etiquetas para que aparezcan cuando tejas el informe.

Este ejercicio forma parte del curso

Creación de informes con R Markdown

Ver curso

Instrucciones del ejercicio

  • En el bloque de código brazil-investment-projects-2018, crea un diagrama de dispersión con los datos brazil_investment_projects_2018.
  • Añade el título "Investment Services Projects in Brazil in 2018" al gráfico.
  • Etiqueta el eje x como "Date Disclosed" y el eje y como "Total IFC Investment in Dollars in Millions".

ejercicio interactivo práctico

Prueba este ejercicio completando este código de ejemplo.

{"investment_report.Rmd":"---\ntitle: \"Investment Report\"\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\noutput: html_document\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}\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}\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}\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(___, aes(x = date_disclosed, y = total_investment, color = status)) +\n  geom_point() +\n  labs(\n    title = ___,\n    x = ___,\n    y = ___\n  ) \n```\n\n\n"}
Editar y ejecutar código