CODEWITHSUNDEEP
rfilter
Sant0
Sant0

Reputation: 21

Filter data for all event

I have a dataset df like this, which is the data collected from individuals using a repeating instrument:

ID <- c('A1', 'A1', 'A1', 'A1', 'A2', 'A2', 'A2', 'A2', 'A2', 'A2', 'A3', 'A3', 'A3', 'A3', 'A4', 'A4', 'A4', 'A4', 'A4', 'A4', 'A4', 'A5', 'A5', 'A5', 'A5', 'A5', 'A5')
day_stat <- c(2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, NA, NA, NA, NA, NA, 1, 1, 1, NA, NA, 1, 2, 2, 2, 1, NA)
adm_dat <- c(NA, NA, NA, NA, NA, NA, NA, '2020-10-12', NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, '2020-10-18', NA, NA)
adm_ever <- c(NA, NA, NA, 1, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA)
df <- data.frame(ID, day_stat, adm_dat, adm_ever)

I am trying to filter the data like this:

df1 = df %>% filter(day_stat==1 | adm_dat!= NA | adm_ever==1)

Current result (not wanted):

img

Desired Output:

If one of these filter conditions is true for an ID, then keep all event data of that ID.

Upvotes: 0

Views: 49

Answers (2)

akrun
akrun

Reputation: 886938

We can use data.table

library(data.table)
setDT(df)[, .SD[any(day_stat==1 | !is.na(adm_dat) | adm_ever==1)], ID]

Upvotes: 0

Ronak Shah
Ronak Shah

Reputation: 388807

To check for NA values use is.na and to select entire group use group_by :

library(dplyr)

df %>%
  group_by(ID) %>%
  filter(any(day_stat==1 | !is.na(adm_dat) | adm_ever==1))

#    ID    day_stat adm_dat    adm_ever
#   <chr>    <dbl> <chr>         <dbl>
# 1 A1           2 NA               NA
# 2 A1           1 NA               NA
# 3 A1           1 NA               NA
# 4 A1           2 NA                1
# 5 A2           2 NA               NA
# 6 A2           2 NA               NA
# 7 A2           2 NA               NA
# 8 A2           1 2020-10-12       NA
# 9 A2           1 NA               NA
#10 A2           1 NA                2
# … with 13 more rows

Upvotes: 1

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