Optional and advanced topic

df <- read.csv("data/export.csv", sep = ";", dec = ",")
df <- df[!is.na(df$Rozloha..ha), ]

Dealing with Dates

There are few columns with dates in the data, for example Datum.prvního.vyhlášení. This column is the character data type, but if we want to work with dates, we have to convert it for further analyssis like counting the number of protected areas with certain year of declaration, etc.

We can convert the column to the Date class with the as.Date() function. Or just retrieve the desired information (year) with the substr() function.

We need to know how the dates looks like, so we list first, or first few dates:

df$Datum.prvního.vyhlášení[1:10]
class(df$Datum.prvního.vyhlášení[1:10])

So this date is formatted as dd.mm.yyyy - day.month.year, so we can use the as.Date() function with the format argument with "%d.%m.%Y" to convert the column to the Date class (in YYYY-MM-DD format):

as.Date(df$Datum.prvního.vyhlášení[1:10], format = "%d.%m.%Y")
class(as.Date(df$Datum.prvního.vyhlášení[1:10], format = "%d.%m.%Y"))

If we have task to find the newest protected area, we can use the max() function on the converted column:

max(df$Datum.prvního.vyhlášení) # nonsense, its character - text
max(as.Date(df$Datum.prvního.vyhlášení, format = "%d.%m.%Y"))

Converting column to the Date class is just replacing the values with the new values in Date class:

df$Datum.prvního.vyhlášení <- as.Date(df$Datum.prvního.vyhlášení, format = "%d.%m.%Y")
max(df$Datum.prvního.vyhlášení)

Now we can filter the data with the date, for example to get the protected areas declared after 2020:

d <- as.Date("2020-01-01")
df[df$Datum.prvního.vyhlášení > d,]