Question

I am new in this group (and also a quite-new R user) and I have a question. I have a data.table like this

Date             V2                       Deal Type
-----------------

1: 2009-1       Public sector bank        Corporate Bond-Investment-Grade                 
2: 2009-1       Private sector bank       Corporate Bond-Investment-Grade                 
3: 2009-7       Private sector industrial Corporate Bond-Investment-Grade                   
4: 2009-1       Private sector bank       Corporate Bond-Investment-Grade                  
5: 2009-1       Private sector bank       Covered Bond                         
6: 2009-1       Public sector bank        Corporate Bond-Investment-Grade                 
7: 2009-1       Private sector bank       Corporate Bond-Investment-Grade

The question is how do I change the names of variables (and variables) in column V2. For example i want that "public sector bank" and "private sector bank" would appear in a new column as "financial" and "private sector industrial" and "public sector industrial" as "non-financial". Hope I have been sufficiently clear. Thank you very much for your help.

Answer 1

在这种情况下，

替换（）可以很方便。假设您的数据框为 DF ，而您的新列为 V2new ：

# Creating new column V2new and replacing "Public/Private sector bank" to "financial" 
DF$V2new <- replace(DF$V2 ,DF$V2 =="Public sector bank"|DF$V2=="Private sector bank","financial") 
# Replacing "Public/Private sector industrial"  from V2new to "non-financial"
DF$V2new <-  replace(DF$V2new ,DF$V2new =="Public sector industrial"|DF$V2new =="Private sector industrial","non-financial")

Answer 2

Assuming your dataframe is called df, you could do something like:

df <- read.csv("data.csv", stringsAsFactors=FALSE)

df$newColumn[df$V2 == "Public sector bank" | df$V2 == "Private sector bank"] <- "financial"
df$newColumn[df$V2 == "Public sector industrial" | df$V2 == "Private sector industrial"] <- "non-financial"

or if you're sure that your V2 fields have the words "bank" and "industrial" in them, and thats how you're determining what to call the values in the new column, you could do this:

df$newColumn[grepl("bank", df$V2)] <- "financial"
df$newColumn[grepl("industrial", df$V2)] <- "non-financial"

This works the same way with data tables as well

Answer 3

if DT is your data.table

`DT[,':='(V3 = ifelse(V2 %in% c("Public sector bank","Private sector bank"),"Non financial","Financial")`]

It is usually a good practice to normalize text fields so you could consider:

DT[,':='(V3 = ifelse(tolower(gsub(" ","",V2)) %in% c("publicsectorbank","privatesectorbank"),"Non financial","Financial")]

Hope this helps, I also recommend https://s3.amazonaws.com/assets.datacamp.com/img/blog/data+table+cheat+sheet.pdf

Change the name of fields in R

3 个答案: