Merge rows and keep values based on another column

Question

I have formed a data frame from the number of surveys. Each survey can be sent many times with updated values. For each survey or you can say row in the dataset, there is a date when the survey was presented (created). I want to join the rows for each survey and keep the date from the first survey but other data from the last survey.

A simple example:

#>   survey    created var1 var2

#> 1     s1 2020-01-01   10   30

#> 2     s2 2020-01-02   10   90

#> 3     s2 2020-01-03   20   20

#> 4     s3 2020-01-01   45    5

#> 5     s3 2020-01-02   50   50

#> 6     s3 2020-01-03   30   10

Desired result:

#>   survey    created var1 var2

#> 1     s1 2020-01-01   10   30

#> 2     s2 2020-01-02   20   20

#> 3     s3 2020-01-01   30   10

Answer 1

You can do this in 2 ways, the first one is that after grouping by 'survey', just change the 'created' as the first or min value in 'created' and then perform the slicing in the last row (n()):

library(dplyr)

df %>% 

   group_by(survey) %>% 

   mutate(created = as.Date(first(created))) %>% 

   slice(n())

# A tibble: 3 x 4

# Groups:   survey [3]

#  survey created     var1  var2

#  <chr>  <date>     <dbl> <dbl>

#1 s1     2020-01-01    10    30

#2 s2     2020-01-02    20    20

#3 s3     2020-01-01    30    10

Or you can just do the following in base R programming:

transform(df, created = ave(created, survey, FUN = first)

         )[!duplicated(df$survey, fromLast = TRUE),]