识别重复行的组并保留组顺序

Question

I am trying to organize a spreadsheet of patient data with random repeat "chunks". Unfortunately, the rows of data are repeated at random, giving me repeat "chunks." I need to remove the repeat chunks while preserving the original order.

Here is a sample:

+---------+-----+----------+
| patient | age | children |
+---------+-----+----------+
| x       | 30  | g        |
| x       | 30  | b        |
| x       | 30  | g        |
| x       | 30  | b        |
| x       | 30  | g        |
| x       | 30  | b        |
| y       | 25  | g        |
| y       | 25  | b        |
| y       | 25  | b        |
| y       | 25  | g        |
| y       | 25  | b        |
| y       | 25  | b        |
+---------+-----+----------+

You can see, patient "x" chunk (with 2 children) is repeated three times, and patient "y" chunk (with 3 children) is repeated twice. The number of repeat chunks is random.

Here is my goal: It is important that the order of the children is preserved

+---------+-----+----------+
| patient | age | children |
+---------+-----+----------+
| x       | 30  | g        |
| x       | 30  | b        |
| y       | 25  | g        |
| y       | 25  | b        |
| y       | 25  | b        |
+---------+-----+----------+

I tried this first in excel: step 1: gave all rows unique identifier, to preserve the order of the children step 2: tried to remove duplicates, but this was a problem for patient "y" who has 2 girls, the final table removed one of them...

I usually do my analysis in R, so a dplyr solution would be great here if anyone could make a suggestion

Beyond the following, I'm lost. Is there a way to recognize unique groups?

dat %>% group_by(patient)

Answer 1

The distinct() function in dplyr might be your best bet; eg:

dat %>% distinct()

You can find more information on identifying and removing duplicate data in R by reading this blog post .