R, change a character string in dataframe to binary values

Question

My dataframe has a column called "LandType" of characters, either "Rural" or "Urban" for a bunch of samples. All I want to do is convert them to 1's and 0's, where "Rural" is 1, and "Urban" is 0.

I thought it would as simple as:

data$LandType[data$LandType == "Rural"] <- 1
data$LandType[data$LandType == "Urban"] <- 0

But after running this with no errors and then checking my data df, the crazy thing is that ONLY "Rural" has changed to 1's but Urban still remains as a string. I tried with different numbers but same thing happened, only Rural would change to the value I assigned.

Maybe Urban is written different in data$Landtype ? Check it e.g. with table(data$Landtype) or unique(data$Landtype). — GKi
– GKi, Commented Sep 6, 2021 at 15:33
Okay I checked and it comes up as "Rural" and "Urban", and there are 72 "Rural" and 93 "Urban" samples. — CuriousDude
– CuriousDude, Commented Sep 6, 2021 at 15:34
Yes it does because that column is a string of characters. I'll try converting it but not sure why then Rural would change to a value but Urban would not... — CuriousDude
– CuriousDude, Commented Sep 6, 2021 at 15:39

Nad Pat · Accepted Answer · 2021-09-06 15:41:40Z

4

Just use ifelse

#your data
data = data.frame(Landtype = c("Rural", "Urban", "Rural", "Urban"))
#ifelse condition 
data$Landtype = ifelse(data$Landtype == "Rural", 1,0)

answered Sep 6, 2021 at 15:41

Nad Pat

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2 Comments

CuriousDude Over a year ago

This worked! It is still incredibly odd to me that Urban would not change. I guess this was a nice workaround an odd situation like this. I also tried with using "Urban" in the ifelse statement and that seemed to work. Running it individually as I wrote above does not work.

Brian Montgomery Over a year ago

This also avoids the problem of the data type on your 1's and 0's being changed to character as it did in the original. Data.frames can only have a single type per column, so when you only replace half the values, it's forced to change the 1 to "1".

rjen · Accepted Answer · 2021-09-06 15:51:01Z

2

A tidyverse option using recode()

library(dplyr)

mutate(data, Landtype = recode(Landtype, Rural = 1, Urban = 0))

# # A tibble: 4 x 1
# Landtype
# <dbl>
# 1        1
# 2        0
# 3        1
# 4        0

Data

data <- tibble(Landtype = c("Rural", "Urban", "Rural", "Urban"))

answered Sep 6, 2021 at 15:51

rjen

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Comments

akrun · Accepted Answer · 2021-09-06 18:34:52Z

0

We could use as.integer

data$Landtype <- as.integer(data$Landtype == "Rural")

data

data = data.frame(Landtype = c("Rural", "Urban", "Rural", "Urban"))

answered Sep 6, 2021 at 18:34

akrun

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Comments

GKi · Accepted Answer · 2021-09-07 06:31:29Z

0

In my case your way works:

set.seed(42)
data <- data.frame(LandType = sample(c(rep("Rural", 72), rep("Urban", 93))))

data$LandType[data$LandType == "Rural"] <- 1
data$LandType[data$LandType == "Urban"] <- 0

table(data$LandType)
# 0  1 
#93 72

To get binary values I would recommend to use the type logical (TRUE or FALSE).

data$LandType <- data$LandType == "Rural"

In case 0 and 1 is needed just add a +

data$LandType <- +(data$LandType == "Rural")

edited Sep 7, 2021 at 6:31

answered Sep 6, 2021 at 15:47

GKi

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2 Comments

CuriousDude Over a year ago

I know - there must be some weird error on my end that is not showing up in R as any warning/error. I checked the raw csv file as well and nothing seems out of place. Maybe a hidden character somewhere? That is my only conclusion.

GKi Over a year ago

Maybe dput your data to see where it comes from.

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