Menambahkan parameter ke laporan
Dalam latihan ini, Anda akan menambahkan parameter untuk country ke laporan dan memodifikasi kode yang ada sehingga Anda dapat membuat laporan baru tentang proyek investasi untuk negara mana pun yang termasuk dalam data investment_services_projects.
Latihan ini adalah bagian dari kursus
Membuat Laporan dengan R Markdown
Petunjuk latihan
- Di bawah field
datepada header YAML, tambahkan bagian parameter menggunakanparams, tambahkan parametercountry, dan tentukanBrazilsebagai negara di dalam parametercountry. - Tinjau
filter()untuk"Brazil"di seluruh dokumen, lalu ganti dengan referensi ke parametercountry. - Pada keping kode
brazil-investment-projects, ganti nama keping kode menjadicountry-investment-projectsdan ganti nama objekbrazil_investment_projectsmenjadicountry_investment_projects. - Pada keping kode
brazil-investment-projects-2018, ganti nama keping kode menjadicountry-investment-projects-2018dan ganti nama objekbrazil_investment_projects_2018serta semua referensi dalam teks kecountry_investment_projects_2018. - Hapus "in Brazil" dari judul plot dalam laporan.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
{"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"}