Вы можете использовать zoo::as.yearmon
:
library(zoo);
df %>%
mutate(Date = as.yearmon(as.character(Date), "%Y%m"))
# Date Price Stock
#1 Feb 2011 339.32 AAPL
#2 Mar 2011 353.21 AAPL
#3 Apr 2011 348.45 AAPL
#4 May 2011 348.23 AAPL
#5 Jun 2011 347.83 AAPL
#6 Jul 2011 335.67 AAPL
#7 Aug 2011 390.48 AAPL
#8 Sep 2011 384.83 AAPL
Пример данных
df <- read.table(text =
" Date Price Stock
1 201102 339.32 AAPL
2 201103 353.21 AAPL
3 201104 348.45 AAPL
4 201105 348.23 AAPL
5 201106 347.83 AAPL
6 201107 335.67 AAPL
7 201108 390.48 AAPL
8 201109 384.83 AAPL", header = T)