How to Replace Certain Values in a Specific Rows and Columns with Na in R?
In My Data Frame, I Want to Replace Certain Blank Cells and Cells with Values with Na. but the Cells I Want to Replace with Nas Has Nothing to Do with the...
In my data frame, I want to replace certain blank cells and cells with values with NA. But the cells I want to replace with NAs has nothing to do with the value that cell stores, but with the combination of row and column it is stored in.
Here's a sample data frame DF:
Fruits Price Weight Number of pieces
Apples 20 2 10
Oranges 15 4 16
Pineapple 40 8 6
Avocado 60 5 20
I want to replace Pineapple'e weight to NA and Orange's number of pieces to NA.
DF$Weight[3] <- NA
DF$`Number of pieces`[2] <- NA
This replaces any value that's stored in that position and that may change. I want to use specific row and column names to do this replacement so the position of value becomes irrelevant.
Output:
Fruits Price Weight Number of pieces
Apples 20 2 10
Oranges 15 4 NA
Pineapple 40 NA 6
Avocado 60 5 20
But if order of the table is changed, this would replace wrong values with NA.
How should I do this?
3 Answers
Since your data structure is 2 dimensional, you can find the indices of the rows containing a specific value first and then use this information.
which(DF$Fruits == "Pineapple")
[1] 3
DF$Weight[which(DF$Fruits == "Pineapple")] <- NA
You should be aware of that which will return a vector, so if you have multiple fruits called "Pineapple" then the previous command will return all indices of them.
Here is a way using function is.na<-.
is.na(DF$Weight) <- DF$Fruits == "Pineapple"
is.na(DF$`Number of pieces`) <- DF$Fruits == "Oranges"
DF
# Fruits Price Weight Number of pieces
#1 Apples 20 2 10
#2 Oranges 15 4 NA
#3 Pineapple 40 NA 6
#4 Avocado 60 5 20
Data in dput format.
DF <-
structure(list(Fruits = structure(c(1L, 3L, 4L, 2L),
.Label = c("Apples", "Avocado", "Oranges", "Pineapple"),
class = "factor"), Price = c(20L, 15L, 40L, 60L),
Weight = c(2L, 4L, 8L, 5L), `Number of pieces` = c(10L,
16L, 6L, 20L)), class = "data.frame", row.names = c(NA, -4L))
library(dplyr)
df %>%
mutate(Weight=ifelse(Fruits=="Pineapple",NA,Weight),
Number=ifelse(Fruits=="Oranges",NA,Number))#use Number of Pieces
Result: Number of pieces was truncated to Number due to reading data.
Fruits Price Weight Number
1 Apples 20 2 10
2 Oranges 15 4 NA
3 Pineapple 40 NA 6
4 Avocado 60 5 20
David Miller brings 15 years of experience in global economics, personal finance strategy, and market dynamics. He specializes in turning complex economic trends into actionable insights for everyday readers.
