How to Conditionally Replace Values in R Data Frame Using If/Then Statement

Replace a value in a data frame based on a conditional (`if`) statement

Easier to convert nm to characters and then make the change:

junk$nm <- as.character(junk$nm)
junk$nm[junk$nm == "B"] <- "b"

EDIT: And if indeed you need to maintain nm as factors, add this in the end:

junk$nm <- as.factor(junk$nm)

How to conditionally replace values in r data frame using if/then statement

You can use ifelse, like this:

df$customer_id <- ifelse(df$customer %in% c('paramount', 'pixar'), 99, df$customer_id)

The syntax is simple:

ifelse(condition, result if TRUE, result if FALSE)

This is vectorized, so you can use it on a dataframe column.

if/then replace values looping over rows conditional on column value(s) in R

We can get the data in long format and then use separate case_when with conditions to recode values and finally get the data back in original format.

library(dplyr)
library(tidyr)

df %>%
  pivot_longer(cols = -c(X1, X2)) %>%
  mutate(value = case_when(X1 == 12 & X2 == 'DF1' & value == 'AB' ~ 1,
                           X1 == 12 & X2 == 'DF1' & value == 'AA' ~ 2, 
                           X1 == 12 & X2 == 'DF1' & value == 'BB' ~ 3, 
                           #Add more conditions as per requirements
                           #....
                           #If none of the above condition satisfy 
                           #return a default value
                           TRUE ~ 0)) %>%
  pivot_wider()

case_when is an alternative to nested ifelse statements since it makes to easy to write for various conditions in simple steps.

Replace values in R dataframe based on conditions

Yes! There's a command called replace:

df$Age <- with(df, replace(Age, Age > 90 | Age < 16, NA)) 

Replace logical values conditionally in R

continuing from what @zephryl wrote, an even more readable code is:

screen$eligible <- with(screen, 
   (age > 17 & age < 23) 
   & (alcohol > 3 | marijuana > 3)
   & (country == 0 | ageus < 12) 
   & county_1 %in% c(17, 27, 31)
   & (residence_1 == 47))

2. to detect where are the NAs:

sapply(screen, anyNA)

Conditional replacement of values in a data.frame

Since you are conditionally indexing df$est, you also need to conditionally index the replacement vector df$a:

index <- df$b == 0
df$est[index] <- (df$a[index] - 5)/2.533 

Of course, the variable index is just temporary, and I use it to make the code a bit more readible. You can write it in one step:

df$est[df$b == 0] <- (df$a[df$b == 0] - 5)/2.533 

For even better readibility, you can use within:

df <- within(df, est[b==0] <- (a[b==0]-5)/2.533)

The results, regardless of which method you choose:

df
          a b      est
1  11.77000 2 0.000000
2  10.90000 3 0.000000
3  10.32000 2 0.000000
4  10.96000 0 2.352941
5   9.90600 0 1.936834
6  10.70000 0 2.250296
7  11.43000 1 0.000000
8  11.41000 2 0.000000
9  10.48512 4 0.000000
10 11.19000 0 2.443743

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As others have pointed out, an alternative solution in your example is to use ifelse.

Replace all values in a data frame, conditionally

library(tidyverse)

df <- data.frame(
  var1 = c(2L, 3L, 5L),
  var2 = c(3L, 6L, 3L),
  var3 = c(5L, 8L, 7L),
  var4 = c(8L, 7L, 4L)
)

df %>%
  mutate(across(.fns = ~ . >= 4)) %>%
  summarise(across(.fns = ~ sum(.)/length(.) ))
#>        var1      var2 var3 var4
#> 1 0.3333333 0.3333333    1    1

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