Visualizando todos os projetos de um país em um ano
Agora, você vai criar um gráfico de linhas usando os dados filtrados para todos os projetos que ocorreram no Brasil no ano fiscal de 2018. Nos exercícios anteriores, os rótulos foram adicionados para você. Ao criar este gráfico, você vai praticar a inclusão dos seus próprios rótulos, que aparecerão quando você compilar (knit) o relatório.
Este exercício faz parte do curso
Relatórios com R Markdown
Instruções do exercício
- No chunk de código
brazil-investment-projects-2018, crie um gráfico de dispersão com os dadosbrazil_investment_projects_2018. - Adicione o título "Investment Services Projects in Brazil in 2018" ao gráfico.
- Rotule o eixo x como "Date Disclosed" e o eixo y como "Total IFC Investment in Dollars in Millions".
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
{"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"}