R Notebook

Final project: data cleaning

1. Download the dataset to R > gb1 <- read.csv(“C:\Users\Olga Z\Documents\00_data_raw\Green_Bonds.csv”)

2. Delete columns “ObjectId”, “Source”, “CTS_Full_Descriptor”, “F1985”-“F2016” > gb1 |>

• select(“Country”, “ISO3”, “Indicator”, “Use_of_Proceed”, “F2017”, “F2018”, “F2019”, “F2020”, “F2021”)

3. Rename columns “F2017”-“F2021” to “2017”-“2021” > gb1 |>

• rename(“2017” = “F2017”, “2018” = “F2018”, “2019” = “F2019”, “2020” = “F2020” , “2021” = “F2021”)

4. Pivot years and values to the long format > gb2 <- gb1 |>

• pivot_longer(cols = matches(“\d{4}”),
• names_to = “year”,
• names_transform = as.integer)