Filtering for a specific year
Now that you've filtered the data for the projects in a specific country, you can filter the results further to look at all projects that occurred in the 2018 fiscal year. Recall, the fiscal year starts on July 1st of the previous year and ends on June 30th of the year of interest.
Cet exercice fait partie du cours
Reporting with R Markdown
Instructions
- In the fourth code chunk, create
brazil_investment_projects_2018by filtering theinvestment_services_projectsdata for projects in Brazil with adate_disclosedin the 2018 fiscal year, which starts on July 1, 2017 and ends on June 30, 2018. - Label the code chunk
brazil-investment-projects-2018. - Add a header to line
33using three hashes to label the sectionInvestment Projects in Brazil in 2018.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
{"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)\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}\ninvestment_annual_summary\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```\n\n\n\n```{r}\nbrazil_investment_projects_2018 <- investment_services_projects %>%\n filter(country == \"Brazil\",\n ___ >= ___,\n ___ <= ___) \n\nbrazil_investment_projects_2018\n```\n\n\n"}