First, convert to a proper date class (always a good practice) and then you could run a simple range
by group. Here's an attempt
library(data.table)
setDT(df)[, Date_Withdrawal := as.IDate(Date_Withdrawal)]
df[, as.list(range(Date_Withdrawal)), by = PersonId]
# PersonId V1 V2
# 1: A 2012-05-01 2012-10-01
# 2: B 2012-05-01 2012-12-01
# 3: C 2012-05-01 2012-07-01
Or
library(dplyr)
df %>%
mutate(Date_Withdrawal = as.Date(Date_Withdrawal)) %>%
group_by(PersonId) %>%
summarise(Min = min(Date_Withdrawal), Max = max(Date_Withdrawal))
# Source: local data frame [3 x 3]
#
# PersonId Min Max
# (fctr) (date) (date)
# 1 A 2012-05-01 2012-10-01
# 2 B 2012-05-01 2012-12-01
# 3 C 2012-05-01 2012-07-01
P.S. base aggregate
would look like aggregate(as.Date(Date_Withdrawal) ~ PersonId, df, range)
but it refuses to retain classes .
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