Bir ülke ve yıl için tüm projelerin görselleştirilmesi
Şimdi, 2018 mali yılında Brezilya’da gerçekleşen tüm projeler için filtrelenmiş veriyi kullanarak bir çizgi grafiği oluşturacaksın. Önceki egzersizlerde etiketler senin için eklenmişti. Bu grafiği oluştururken, raporu örgülediğinde (knit) görünecek kendi etiketlerini ekleme konusunda pratik yapacaksın.
Bu egzersiz
R Markdown ile Raporlama
kursunun bir parçasıdırEgzersiz talimatları
brazil-investment-projects-2018kod parçasında,brazil_investment_projects_2018verisinin bir saçılım grafiğini (scatterplot) oluştur.- Grafiğe "Investment Services Projects in Brazil in 2018" başlığını ekle.
- x eksenini "Date Disclosed" ve y eksenini "Total IFC Investment in Dollars in Millions" olarak etiketle.
Uygulamalı interaktif egzersiz
Bu örnek kodu tamamlayarak bu egzersizi bitirin.
{"investment_report.Rmd":"---\ntitle: \"Investment Report\"\ndate: \"`r format(Sys.time(), '%d %B %Y')`\"\noutput: html_document\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(___, aes(x = date_disclosed, y = total_investment, color = status)) +\n geom_point() +\n labs(\n title = ___,\n x = ___,\n y = ___\n ) \n```\n\n\n"}