find duplicate, compare a condition, erase one row r

问题

Using the following reproducible example:

ID1<-c("a1","a4","a6","a6","a5", "a1" )
ID2<-c("b8","b99","b5","b5","b2","b8" )
Value1<-c(2,5,6,6,2,7)
Value2<- c(23,51,63,64,23,23)
Year<- c(2004,2004,2004,2004,2005,2004)
df<-data.frame(ID1,ID2,Value1,Value2,Year)

I want to select rows where ID1 and ID2 and Year have the same value in their respective columns. For this rows I want to compare Value1 and Value2 in the duplicates rows and IF the values are not the same erase the row with the smaller value.

Expected result:

  ID1 ID2 Value1 Value2 Year         new

2  a4 b99      5     51 2004 a4_b99_2004

4  a6  b5      6     64 2004  a6_b5_2004
5  a5  b2      2     23 2005  a5_b2_2005
6  a1  b8      7     23 2004  a1_b8_2004

I tried the following: Find a unique identifier for the conditions I am interested

df$new<-paste(df$ID1,df$ID2, df$Year, sep="_")

I can use the unique identifier to find the rows of the database that contain the duplicates

IND<-which(duplicated(df$new) | duplicated(df$new, fromLast = TRUE))

In a for loop if unique identifier has duplicate compare the values and erase the rows, but the loop is too complicated and I cannot solve it.

for (i in df$new) {

  if(sum(df$new == i)>1)
           {
  ind<-which(df$new==i)
  m= min(df$Value1[ind])
  df<-df[-which.min(df$Value1[ind]),]
  m= min(df$Value2[ind])
  df<-df[-which.min(df$Value2[ind]),]

  }
}

回答1:

Consider aggregate to retrieve the max values by your grouping, ID1, ID2, and Year:

df_new <- aggregate(.~ID1 + ID2 + Year, df, max)
df_new

#   ID1 ID2 Year Value1 Value2
# 1  a6  b5 2004      6     64
# 2  a1  b8 2004      7     23
# 3  a4 b99 2004      5     51
# 4  a5  b2 2005      2     23

回答2:

Some different possibilities. Using dplyr:

df %>%
  group_by(ID1, ID2, Year) %>%
  filter(Value1 == max(Value1) & Value2 == max(Value2))

Or:

df %>%
  rowwise() %>%
  mutate(max_val = sum(Value1, Value2)) %>%
  ungroup() %>%
  group_by(ID1, ID2, Year) %>%
  filter(max_val == max(max_val)) %>%
  select(-max_val)

Using data.table:

setDT(df)[df[, .I[Value1 == max(Value1) & Value2 == max(Value2)], by = list(ID1, ID2, Year)]$V1]

Or:

setDT(df)[, max_val := sum(Value1, Value2), by = 1:nrow(df)
   ][, filter := max_val == max(max_val), by = list(ID1, ID2, Year)
       ][filter != FALSE
         ][, -c("max_val", "filter")]

Or:

subset(setDT(df)[, max_val := sum(Value1, Value2), by = 1:nrow(df)
             ][, filter := max_val == max(max_val), by = list(ID1, ID2, Year)], filter != FALSE)[, -c("max_val", "filter")]

回答3:

Solution without loading libraries:

            ID1 ID2 Value1 Value2 Year
a6.b5.2004   a6  b5      6     64 2004
a1.b8.2004   a1  b8      7     23 2004
a4.b99.2004  a4 b99      5     51 2004
a5.b2.2005   a5  b2      2     23 2005

Code

do.call(rbind, lapply(split(df, list(df$ID1, df$ID2, df$Year)),                  # make identifiers
                      function(x) {return(x[which.max(x$Value1 + x$Value2),])})) # take max of sum

来源：https://stackoverflow.com/questions/52803902/find-duplicate-compare-a-condition-erase-one-row-r

标签

if-statement

duplicates