在r数据框中隔离部分文本

Question

I have an r data frame that contains US state and county names in one column. The data is in the format:

United States - State name - County name

where each cell is a unique county. For example:

United States - North Carolina - Wake County
United States - North Carolina - Warren County
etc.

I need to break the column into 2 columns, one containing just the state name and the other containing just the county name. I've experimented with sub and gsub but am getting no results. I understand this is probably a simple matter for r experts but I'm a newbie. I would be most grateful if anyone can point me in the right direction.

Answer 1

You can use tidyr 's separate function:

library(tidyr)
df <- separate(df, currentColumn, into = c("Country", "State", "County"), sep = " - ")

If the data is as you show in your question (including United States as country) and if your data frame is called df and the current column with the data is called currentColumn.

Example:

df <- data.frame(currentColumn = c("United States - North Carolina - Wake County",
 "United States - North Carolina - Warren County"), val = rnorm(2))

df
#                                   currentColumn       val
#1   United States - North Carolina - Wake County 0.8173619
#2 United States - North Carolina - Warren County 0.4941976

separate(df, currentColumn, into = c("Country", "State", "County"), sep = " - ")
#        Country          State        County       val
#1 United States North Carolina   Wake County 0.8173619
#2 United States North Carolina Warren County 0.4941976

Answer 2

Using read.table , and assuming your data is in df$var

read.table(text=df$var,sep="-",strip.white=TRUE,
           col.names=c("Country","State","County"))

If speed is an issue, then strsplit will be a lot quicker:

setNames(data.frame(do.call(rbind,strsplit(df$var,split=" - "))),
         c("Country","State","County"))

Both give:

#        Country          State        County
#1 United States North Carolina   Wake County
#2 United States North Carolina Warren County