Replacing values based on multiple columns in R

Question

I have raw data with multiple observation and I have a cleaning log which contains some new values for specific columns of raw data I want to replace old values with these new ones.

My raw data is :

raw_df<- data.frame(
                    id=c(1,2,3,4),
                    name=c("a","b","c","d"),
                    age=c(15,16,20,22),
                    add=c("xyz","bc","no","da")
                   )

MY cleaning log is :

cleaning_log <- data.frame(
                             id=c(2,4),
                             question=c("name","age"), 
                             old_value=c("b",22),
                             new_value=c("bob",25)
                          )

And my expected result is :

result<-data.frame(
                      id=c(1,2,3,4),
                      name=c("a","bob","c","d"),
                      age=c(15,16,20,25),
                      add=c("xyz","bc","no","da")
                  )

Note:At the end how can I check whether these new values are replaced properly or not? In addition, in cleaning log question column I may have more than two columns like 10 to 20 which possibly will have new value but here I just give two column names as an example. Thanks in advance for you help

Ronak Shah · Accepted Answer · 2021-03-04 06:52:28Z

3

Find out the row number and column number to change in raw_df using match and replace it with cleaning_log$new_value.

row_inds <- match(cleaning_log$id, raw_df$id)
col_inds <-  match(cleaning_log$question, names(raw_df))
raw_df[cbind(row_inds, col_inds)] <- cleaning_log$new_value
raw_df

#  id name age add
#1  1    a  15 xyz
#2  2  bob  16  bc
#3  3    c  20  no
#4  4    d  25  da

answered Mar 4, 2021 at 6:52

Ronak Shah

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2 Comments

MaxMiak Over a year ago

and how to check whether they are replaced properly?

Ronak Shah Over a year ago

You can manually check 3-4 values if they are replaced correctly.

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