Mengatur opsi chunk secara lokal
Saat membuat laporan, Anda mungkin ingin mengatur opsi chunk secara lokal agar tampilan gambar di laporan akhir bervariasi. Data investment_annual_summary memberikan informasi latar belakang yang berguna, tetapi fokus laporan adalah proyek di Brasil. Pada latihan ini, Anda akan memodifikasi opsi chunk secara lokal sehingga plot yang menampilkan informasi tentang proyek di Brasil tampak sedikit lebih besar dalam laporan akhir dibandingkan plot yang memberikan ikhtisar data Investment Annual Summary.
Latihan ini adalah bagian dari kursus
Membuat Laporan dengan R Markdown
Petunjuk latihan
- Tambahkan pada chunk
investment-annual-summarysehingga dimensi keluaran gambar yang dihasilkan adalah 85%. - Tambahkan pada chunk
brazil-investment-projectsdanbrazil-investment-projects-2018sehingga dimensi keluaran gambar adalah 95%.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
{"investment_report.Rmd":"---\ntitle: \"Investment Report\"\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\noutput: html_document\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\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(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"}