Adăugarea unui parametru în raport
În acest exercițiu, vei adăuga un parametru pentru country în raport și vei modifica codul existent, astfel încât să poți genera rapoarte noi despre proiectele de investiții pentru orice țară din setul de date investment_services_projects.
Acest exercițiu face parte din cursul
Raportare cu R Markdown
Instrucțiuni pentru exercițiu
- Sub câmpul
datedin antetul YAML, adaugă o secțiune pentru parametri folosindparams, adaugă un parametrucountryși specificăBrazilca valoare pentru parametrulcountry. - Revizuiește toate apelurile
filter()cu"Brazil"din document și înlocuiește-le cu o referință la parametrulcountry. - În fragmentul de cod
brazil-investment-projects, redenumește fragmentul încountry-investment-projectsși redenumește obiectulbrazil_investment_projectsîncountry_investment_projects. - În fragmentul de cod
brazil-investment-projects-2018, redenumește fragmentul încountry-investment-projects-2018și redenumește obiectulbrazil_investment_projects_2018, precum și orice referință la acesta în text, încountry_investment_projects_2018. - Elimină sintagma „in Brazil" din titlurile graficelor din raport.
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')`\"\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 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\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 `brazil_investment_projects_2018`. Projects that do not have an associated investment amount are excluded from the plot.\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(brazil_investment_projects_2018, aes(x = date_disclosed, y = total_investment, color = status)) +\n geom_point() +\n labs(\n title = \"Investment Services Projects in Brazil in 2018\",\n x = \"Date Disclosed\",\n y = \"Total IFC Investment in Dollars in Millions\"\n ) \n```\n\n\n"}