ÎncepețiÎncepe gratuit

Crearea unui raport nou folosind un parametru

Acum că ai adăugat un parametru în document, vei crea un raport nou pentru Bangladesh din datele investment_services_projects, folosind parametrul country.

Înainte de a genera raportul prin knit, vei revizui și modifica textul documentului pentru a te asigura că raportul final va reflecta țara specificată în parametru.

Acest exercițiu face parte din cursul

Raportare cu R Markdown

Vezi cursul

Instrucțiuni pentru exercițiu

  • Înlocuiește Brazil din anteturile documentului cu o referință la parametrul country.
  • Adaugă parametrul country în câmpul de titlu "Investment Report" din antetul YAML, astfel încât, după generarea prin knit, titlul raportului să apară ca "Investment Report for Projects in Bangladesh".
  • Folosind parametrul country, creează un fișier nou de raport de investiții pentru Bangladesh.

Exercițiu interactiv practic

Încearcă acest exercițiu completând acest cod de exemplu.

{"investment_report.Rmd":"---\ntitle: \"Investment Report\"\noutput: \n  html_document:\n    toc: true\n    toc_float: true\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\nparams:\n  country: Brazil \n---\n\n```{r setup, include = FALSE}\nknitr::opts_chunk$set(fig.align = 'center', echo = TRUE)\n```\n\n```{r data, include = FALSE}\nlibrary(readr)\nlibrary(dplyr)\nlibrary(ggplot2)\n\ninvestment_annual_summary <- read_csv(\"https://assets.datacamp.com/production/repositories/5756/datasets/d0251f26117bbcf0ea96ac276555b9003f4f7372/investment_annual_summary.csv\")\ninvestment_services_projects <- read_csv(\"https://assets.datacamp.com/production/repositories/5756/datasets/bcb2e39ecbe521f4b414a21e35f7b8b5c50aec64/investment_services_projects.csv\")\n```\n\n## Datasets \n\n### Investment Annual Summary\nThe `investment_annual_summary` dataset provides a summary of the dollars in millions provided to each region for each fiscal year, from 2012 to 2018.\n```{r investment-annual-summary}\nggplot(investment_annual_summary, aes(x = fiscal_year, y = dollars_in_millions, color = region)) +\n  geom_line() +\n  labs(\n    title = \"Investment Annual Summary\",\n    x = \"Fiscal Year\",\n    y = \"Dollars in Millions\"\n  )\n```\n\n### Investment Projects in Brazil\nThe `investment_services_projects` dataset provides information about each investment project from 2012 to 2018. Information listed includes the project name, company name, sector, project status, and investment amounts. Projects that do not have an associated investment amount are excluded from the plot.\n\n```{r country-investment-projects}\ncountry_investment_projects <- investment_services_projects %>%\n  filter(country == params$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 Brazil 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_investment_projects_2018`. Projects that do not have an associated investment amount are excluded from the plot.\n```{r country-investment-projects-2018}\ncountry_investment_projects_2018 <- investment_services_projects %>%\n  filter(country == params$country,\n         date_disclosed >= \"2017-07-01\",\n         date_disclosed <= \"2018-06-30\")\n\nggplot(country_investment_projects_2018, aes(x = date_disclosed, y = total_investment, color = status)) +\n  geom_point() +\n  labs(\n    title = \"Investment Services Projects in 2018\",\n    x = \"Date Disclosed\",\n    y = \"Total IFC Investment in Dollars in Millions\"\n  ) \n```\n\n\n"}
Editează și rulează codul