在 R 中过滤具有重复行的数据集

Question

I need to filter a dataset based on two conditions.

Here is how my dataset looks like:

df <- data.frame(
  id = c(1,2,2,3,3,4,5,5),
  district = c(10,10,11,12,12,13,14,15),
  value = c(10.2, 10.8, 10.8, 7.5, 9.3, 6, 7.0, 7.0))


> df
  id district value
1  1       10  10.2
2  2       10  10.8
3  2       11  10.8
4  3       12   7.5
5  3       12   9.3
6  4       13   6.0
7  5       14   7.0
8  5       15   7.0

I have duplicated rows based on id s. In order to keep the desired row, First id s having the multiple districts but the same value , I need to keep the first row: Second id s having multiple value s, but from the same district, I need the max of value row.

SO the desired filtered dataset is:

> df
  id district value
1  1       10  10.2
2  2       10  10.8
3  3       12   9.3
4  4       13   6.0
5  5       14   7.0

I was able to locate the duplicated ids only up until now.

df[duplicated(df$id),]

Does anyone have any ideas? Thanks

Answer 1

With dplyr :

df %>% 
  group_by(id) %>%
  arrange(desc(value)) %>%
  slice(1)
# # A tibble: 5 x 3
# # Groups:   id [5]
#      id district value
#   <dbl>    <dbl> <dbl>
# 1     1       10  10.2
# 2     2       10  10.8
# 3     3       12   9.3
# 4     4       13   6  
# 5     5       14   7  

There's no real need to distinguish between the max value if there are multiple values and keeping the first value if there are duplicates - if we order the data descending by value and keep the first row in each id group, it accomplishes both of those tasks with one logic.

Answer 2

library(dplyr)

df %>%
  arrange(id, -value) %>%
  distinct(id, district, .keep_all = TRUE) %>%
  distinct(id, value, .keep_all = TRUE)

      id district value
1  1       10  10.2
2  2       10  10.8
3  3       12   9.3
4  4       13   6.0
5  5       14   7.0

First we sort descending by value, then we use the distinct function to look for unique combinations.

Answer 3

In base R , we can use duplicated after order ing the rows

df1 <- df[order(df$id, -df$value),]
df1[!duplicated(df1$id),]
#  id district value
#1  1       10  10.2
#2  2       10  10.8
#5  3       12   9.3
#6  4       13   6.0
#7  5       14   7.0