On 2020-08-21 13:45 +0200, Dr Eberhard Lisse wrote: | | Eric, Rasmus, | | thank you very much, | | ALLPAP %>% | group_by(Provider) %>% | mutate( minDt=min(CollectionDate), | maxDt=max(CollectionDate)) %>% | summarize( minDt = min(minDt), | maxDt = max(maxDt), .groups="keep" ) %>% | ungroup() %>% | mutate(MAX_MIN_DATE = max(minDt), | MIN_MAX_DATE = min(maxDt)) %>% | distinct(MAX_MIN_DATE, MIN_MAX_DATE) | | gives me | | # A tibble: 1 x 2 | MAX_MIN_DATE MIN_MAX_DATE | <chr> <chr> | 1 2010-02-05 2019-08-30 | | which is correct, and what I wanted. | | This is so cool :-)-O
Dear Eberhard,
handling Dates is a bit tricky in normal
R, but as long as they are characters,
like in your example there, everything
is fine. So I made this example based
on Eric's example:
set.seed(3)
size <- 20
x <- as.Date("2016-11-03") +
sample(
0:30,
size,
repl=TRUE)
provider <- paste("Dr",
sample(
LETTERS[1:3],
size,
repl=TRUE))
lDf <- data.frame(
Provider=provider,
CollectionDate=x,
stringsAsFactors=FALSE)
Provider <- sort(unique(lDf$Provider))
a <- t(sapply(Provider, function(provider, lDf) {
cd <- lDf[
lDf$Provider==provider,
"CollectionDate"]
c("Provider"=provider,
as.character(c(
"u"=min(cd),
"v"=max(cd))))
}, lDf=lDf))
a
which yields
Provider u v
Dr A "Dr A" "2016-11-06" "2016-12-01"
Dr B "Dr B" "2016-11-07" "2016-12-03"
Dr C "Dr C" "2016-11-04" "2016-11-12"
Before I did that, I thought about doing
something with reshape2, but I could not
come up with something good.
If you want to work with tibbles in that
tidyverse thing, which probably can more
easily work with Dates, rbinding tibbles
together apparently works:
a <- lapply(Provider, function(provider, lDf) {
cd <- lDf[
lDf$Provider==provider,
"CollectionDate"]
dplyr::tibble(
"Provider"=provider,
"u"=min(cd),
"v"=max(cd))
}, lDf=lDf)
a <- do.call(rbind, a)
a
which yields
# A tibble: 3 x 3
Provider u v
<chr> <date> <date>
1 Dr A 2016-11-06 2016-12-01
2 Dr B 2016-11-07 2016-12-03
3 Dr C 2016-11-04 2016-11-12
Best,
Rasmus
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