Visualizzare tutti i progetti per un paese e un anno
Ora creerai un grafico a linee usando i dati filtrati per tutti i progetti avvenuti in Brasile nell'anno fiscale 2018. Negli esercizi precedenti, le etichette sono state aggiunte per te. Creando questo grafico, farai pratica ad aggiungere le tue etichette che appariranno quando compili il report.
Questo esercizio fa parte del corso
Reportistica con R Markdown
Istruzioni dell'esercizio
- Nel blocco di codice
brazil-investment-projects-2018, crea uno scatterplot dei datibrazil_investment_projects_2018. - Aggiungi al grafico il titolo "Investment Services Projects in Brazil in 2018".
- Etichetta l'asse x con "Date Disclosed" e l'asse y con "Total IFC Investment in Dollars in Millions".
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
{"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"}