How to clean messy date formats in a dataframe using R - r

Question

What is a quick way to clean a column with multiple date formats and obtain only the year?
Suppose in r there is a dataframe (df) as below, which has aDatecolumn of characters with different dates formats.
df <- data.frame(z= paste("Date",seq(1:10)), Date=c("2000-10-22", "9/21/2001", "2003", "2017/2018", "9/28/2010",
"9/27/2011","2019/2020", "2017-10/2018-12", "NA", "" ))
df:
z Date
1 Date 1 2000-10-22
2 Date 2 9/21/2001
3 Date 3 2003
4 Date 4 2017/2018
5 Date 5 9/28/2010
6 Date 6 9/27/2011
7 Date 7 2019/2020
8 Date 8 2017-10/2018-12
9 Date 9 NA
10 Date 10
Using r commands what is a quick way to extract out the years e.g. 2003, 2010 from the Date column? The first year is to be selected for cells with two years in a row.
So that the expected output would be like below:
z Date year
1 Date 1 2000-10-22 2000
2 Date 2 9/21/2001 2001
3 Date 3 2003 2003
4 Date 4 2007/2018 2017
5 Date 5 9/28/2010 2010
6 Date 6 9/27/2011 2011
7 Date 7 2007/2018 2019
8 Date 8 2017-10/2018-12 2017
9 Date 9 NA NA
10 Date 10

Answer 1

Use extract from tidyr. If there are two years it will use the first.
library(dplyr)
library(tidyr)
df %>% extract(Date, "Year", "(\\d{4})", remove = FALSE, convert = TRUE)
giving:
z Date Year
1 Date 1 2000-10-22 2000
2 Date 2 9/21/2001 2001
3 Date 3 2003 2003
4 Date 4 2017/2018 2017
5 Date 5 9/28/2010 2010
6 Date 6 9/27/2011 2011
7 Date 7 2019/2020 2019
8 Date 8 2017-10/2018-12 2017
9 Date 9 NA NA
10 Date 10 NA
If the second year is needed as well then:
df %>%
extract(Date, "Year2", "\\d{4}.*(\\d{4})", remove = FALSE, convert = TRUE) %>%
extract(Date, "Year", "(\\d{4})", remove = FALSE, convert = TRUE)
giving:
z Date Year Year2
1 Date 1 2000-10-22 2000 NA
2 Date 2 9/21/2001 2001 NA
3 Date 3 2003 2003 NA
4 Date 4 2017/2018 2017 2018
5 Date 5 9/28/2010 2010 NA
6 Date 6 9/27/2011 2011 NA
7 Date 7 2019/2020 2019 2020
8 Date 8 2017-10/2018-12 2017 2018
9 Date 9 NA NA NA
10 Date 10 NA NA