I've been looking at the various answers for similar issues, but can't see anything that quite answers my problem.
I have a large data table
| Number_X | Amount |
|---|---|
| 1 | 100 |
| 2 | 100 |
| 1 | 100 |
| 3 | 100 |
| 1 | 100 |
| 2 | 100 |
I want to replace the amount with 50 for those rows where Number_X == 1. I've tried
library(dplyr)
data <- data %>%
mutate(Amount = replace(Amount, Number_X == 1, 50))
but it doesn't change the value for Amount. How can I fix this?
# set as data.table
setDT(df)
# if then
df[ Number_X == 1, Amount := 50]
With large data, a data.table solution is most appropriate.
I don't see an issue with using replace() but you can also try to use if_else()
library(dplyr, warn.conflicts = FALSE)
data <- tibble(
Number_X = c(1L, 2L, 1L, 3L, 1L, 2L),
Amount = c(100L, 100L, 100L, 100L, 100L, 100L)
)
data %>%
mutate(Amount = replace(Amount, Number_X == 1, 50L))
#> # A tibble: 6 x 2
#> Number_X Amount
#> <int> <int>
#> 1 1 50
#> 2 2 100
#> 3 1 50
#> 4 3 100
#> 5 1 50
#> 6 2 100
data %>%
mutate(Amount = if_else(Number_X == 1, 50L, Amount))
#> # A tibble: 6 x 2
#> Number_X Amount
#> <int> <int>
#> 1 1 50
#> 2 2 100
#> 3 1 50
#> 4 3 100
#> 5 1 50
#> 6 2 100
Created on 2022-02-04 by the reprex package (v2.0.1)
Tip: Use dput() with your data to share it more easily:
dput(data)
#> structure(list(Number_X = c(1L, 2L, 1L, 3L, 1L, 2L), Amount = c(100L,
#> 100L, 100L, 100L, 100L, 100L)), class = c("tbl_df", "tbl", "data.frame"
#> ), row.names = c(NA, -6L))
If you want a tidyverse approach:
data %>%
mutate(Amount = ifelse(Number_X == 1, 50, Amount))
If you want almost the speed of data.table and the grammar of dplyr, you can consider dtplyr.
