CODEWITHSUNDEEP
r
Jay D.
Jay D.

Reputation: 5

Adding a column to a tibble using string matching

I am trying to add a new column into a data frame by matching words from a different column. To use mtcars as an example, I want to create a column "country" by scanning each rowname for a string. To go through the first few rows in pseudocode:

if "Mazda" in rowname then "Japan"
if "Datsun" in rowname then "Japan"
if "Hornet" in rowname then "USA"
etc

I've tried using mutate with the map function, but to no avail. Any help would be appreciated.

Upvotes: 0

Views: 105

Answers (3)

d.b
d.b

Reputation: 32548

Use a named vector (x in this example)

library(dplyr)
x = c(Mazda = "Japan", Datsun = "Japan", Hornet = "USA")
mtcars %>%
    mutate(Make = row.names(.)) %>%
    select(Make) %>%
    mutate(Country = x[sapply(strsplit(Make, " "), function(x) x[1])])

Upvotes: 0

Corey Pembleton
Corey Pembleton

Reputation: 757

You want to use case_when() or ifelse():

library(dplyr)

mt <- head(mtcars, 5)

mt %>% 
  mutate(new_col = case_when(
    mpg == 21.0 ~ "new",
    TRUE ~ "A"
  ))
   mpg cyl disp  hp drat    wt  qsec vs am gear carb new_col
1 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4     new
2 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4     new
3 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1       A
4 21.4   6  258 110 3.08 3.215 19.44  1  0    3    1       A
5 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2       A

Upvotes: 1

akrun
akrun

Reputation: 887153

Instead of using multiple if/else or nested ifelse, we can have a key/val dataset and join with the original data

library(tibble)
library(dplyr
library(stringr)
keyvaldat <- tibble(make = c("Mazda", "Datsun", "Hornet"),
                     Country = c("Japan", "Japan", "USA"))     

rownames_to_column(mtcars, "rn") %>%
       mutate(make = word(rn, 1)) %>%
       left_join(keyvaldat) %>%
       head(4)
#            rn  mpg cyl disp  hp drat    wt  qsec vs am gear carb   make Country
#1      Mazda RX4 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4  Mazda   Japan
#2  Mazda RX4 Wag 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4  Mazda   Japan
#3     Datsun 710 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 Datsun   Japan
#4 Hornet 4 Drive 21.4   6  258 110 3.08 3.215 19.44  1  0    3    1 Hornet     USA

NOTE: If there are 100- values to change, then it would be 100 ifelse statements. Better would be a join

Upvotes: 0

Related Questions