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Tworzenie nowego raportu przy użyciu wielu parametrów

Po dodaniu parametrów obsługujących rok fiskalny możesz teraz utworzyć nowy raport dla innego kraju i roku fiskalnego na podstawie danych investment_services_projects.

To ćwiczenie jest częścią kursu

Raportowanie z R Markdown

Zobacz kurs

Instrukcje do ćwiczenia

  • Zastąp „2018" w nagłówku w wierszu 59 oraz w tekście w wierszu 60 odwołaniami do parametru roku fiskalnego.
  • Używając parametru country, utwórz raport inwestycyjny dla Bangladeszu.
  • Zmodyfikuj parametry year_start, year_end i fy tak, aby tworzony raport inwestycyjny obejmował dane z roku fiskalnego 2014.

Interaktywne ćwiczenie praktyczne

Spróbuj tego ćwiczenia, uzupełniając ten przykładowy kod.

{"investment_report.Rmd":"---\ntitle: \"Investment Report for Projects in `r params$country`\"\noutput: \n  html_document:\n    toc: true\n    toc_float: true\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\nparams:\n  country: Brazil\n  year_start: 2017-07-01\n  year_end: 2018-06-30\n  fy: 2018\n---\n\n```{r setup, include = FALSE}\nknitr::opts_chunk$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\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 `r params$country`\nThe `investment_services_projects` dataset provides information about each investment project from 2012 to 2018. Information listed includes the project name, company name, sector, project status, and investment amounts. Projects that do not have an associated investment amount are excluded from the plot.\n\n```{r country-investment-projects}\ncountry_investment_projects <- investment_services_projects %>%\n  filter(country == params$country) \n\nggplot(country_investment_projects, aes(x = date_disclosed, y = total_investment, color = status)) +\n  geom_point() +\n  labs(\n    title = \"Investment Services Projects\",\n    x = \"Date Disclosed\",\n    y = \"Total IFC Investment in Dollars in Millions\"\n  )\n```\n\n### Investment Projects in `r params$country` in 2018\nThe `investment_services_projects` dataset was filtered below to focus on information about each investment project from the 2018 fiscal year, and is referred to as `country_annual_investment_projects`. Projects that do not have an associated investment amount are excluded from the plot.\n```{r country-annual-investment-projects}\ncountry_annual_investment_projects <- investment_services_projects %>%\n  filter(country == params$country,\n         date_disclosed >= params$year_start,\n         date_disclosed <= params$year_end) \n\nggplot(country_annual_investment_projects, aes(x = date_disclosed, y = total_investment, color = status)) +\n  geom_point() +\n  labs(\n    title = \"Investment Services Projects\",\n    x = \"Date Disclosed\",\n    y = \"Total IFC Investment in Dollars in Millions\"\n  ) \n```\n\n\n"}
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