Remove duplicates based on second column

Question

I am trying to write a section of code that does a few things: 1) group dataset by ID 2) count the number of unique months in column data.month 3) remove all IDs that have less than 9 months 4) print distinct IDs based on the company (ie print ID twice if related to 2 companies) 5) remove duplicated ID and keep the record that has the highest data.month number.

I have the code working until 5). I cant get my code to only print the record (row) of duplicate IDs that has the highest month number.

I looked at a few examples here:

R remove duplicates based on other columns

Remove duplicates based on 2nd column condition

I can figure out how to remove duplicates, but I'm having trouble applying it to my circumstances.

This is the two codes I have tried to achieve my goal:

data.check6 <- bind %>%
group_by(bind$ABN) %>%
summarise(count = n_distinct(data.month)) %>%
filter(count>8) %>%
rrange(bind$data.month) %>%
filter(row_number() == 1)

and:

 library(tidyverse)

 data.check7 <- bind %>%
  group_by(ABN)%>%      
  filter(1 == length(unique(bind$data.month)), !duplicated(bind$data.month))

Right now, I get the error:

Error in arrange_impl(.data, dots) : incorrect size (345343) at position 1, expecting : 3749

In the end I would like to have a dataset where each ID only appears once and it is the ID record associated with the highest month (ie. column value = 12)

Please add a reproducible example along with expected output. — Ronak Shah, May 23 '19 at 07:28
By your last sentence, I think you do not want to remove duplicates, otherwise you want apply a filter in a "group by". A reproducible example is very important in these cases. — Juan Antonio Roldán Díaz, May 23 '19 at 08:23

score 1 · Accepted Answer · answered May 23 '19 at 08:20

I think you're looking for something like that:

Example data:

> bind <- data.frame(ABN = rep(1:3, 3),
+                    data.month = sample(1:12, 9),
+                    other.inf = runif(9))
> 
> bind
  ABN data.month other.inf
1   1         10 0.8102867
2   2          4 0.2919716
3   3          8 0.3391790
4   1          2 0.3698933
5   2          6 0.9155280
6   3          1 0.2680165
7   1          9 0.7541168
8   2          7 0.2018796
9   3         11 0.1546079

Solution:

> bind %>%
+   group_by(ABN) %>%      
+   filter(data.month == max(data.month))
# A tibble: 3 x 3
# Groups:   ABN [3]
    ABN data.month other.inf
  <int>      <int>     <dbl>
1     1         10     0.810
2     2          7     0.202
3     3         11     0.155

Yes, this is what I was looking for. Thanks! – Cae.rich May 24 '19 at 01:56 — Cae.rich, May 24 '19 at 01:56

Remove duplicates based on second column

1 Answers1