Adding New Column with Conditional Values Using Ifelse

Apply if else condition to make new column in r

We can use case_when like this:

library(tidyverse)

dat <- tibble(P.col = seq(0, 20000, 1000))

mutate(dat, P.bin = case_when(P.col >= 4000 ~ ">4000",
                              P.col <= 3000 & P.col >= 2000 ~ "2000-3000",
                              P.col <= 3000 & P.col >= 2000 ~ "2000-3000",
                              P.col <= 2000 & P.col >=1000 ~ "1000-2000",
                              P.col < 1000 ~ "1000"))
#> # A tibble: 21 x 2
#>    P.col P.bin    
#>    <dbl> <chr>    
#>  1     0 1000     
#>  2  1000 1000-2000
#>  3  2000 2000-3000
#>  4  3000 2000-3000
#>  5  4000 >4000    
#>  6  5000 >4000    
#>  7  6000 >4000    
#>  8  7000 >4000    
#>  9  8000 >4000    
#> 10  9000 >4000    
#> # … with 11 more rows

^{Created on 2021-06-11 by the reprex package (v2.0.0)}

Using If else to check multiple columns and create a new column based on the response for string responses

This is not the more efficient answer, neither the more general solution, but may satisfy a solution:

#create columns
st <- rep(NA,nrow(hairdf));
cur <- rep(NA,nrow(hairdf));
wav <- rep(NA,nrow(hairdf));
mix <- rep(NA,nrow(hairdf));

#join and define words
hairdf <- cbind(hairdf,st,cur,wav,mix);
words <- c("straight","curly","wavy","mixed");
words_ast <- paste(words,"*",sep=""); #just get the "*" words

#make a loop according to positions of columns st,cur,wav,mix
for (j in 1:length(words_ast)){ #let's see if we can evaluate 2 in words_ast
  for (i in c(2,3,4)){ #but only in columns we selected
    a <- subset(hairdf,hairdf[,i]==words_ast[j]) #subset columns which satisfay condition. [Note that this can be written as hairdf %>% subset(.[,i]==words_ast[j]) ]
    hairdf[row.names(a),7+j] <- 2 #replace value from column 8
  }
}
#repeat process for "words"

for (j in 1:length(words)){
  for (i in c(2,3,4)){
    a <- subset(hairdf,hairdf[,i]==words[j])
    hairdf[row.names(a),7+j] <- 1
  }
}

This should allow you to get the expected result. Alternatively, you can use the assign() function, i.e

assign(x,value=1)

where x is each element in words.

So in a loop:

assign(words[n],value=1) ; assign(words_ast[n],value=2)

add new column to dataframe with if, else statement

I'm not sure about your data, but in your if-else if-else statement, conditions like counties$Series_Complete >= 75 are now comparing whole vector with single value, and if using print, it may not give you proper result. Instead, try using dplyr::case_when

library(dplyr)
counties %>%
  mutate(class = case_when(
    Series_Complete >=75 ~ 4,
    Series_Complete >= 50 ~ 3,
    Series_Complete >= 25 ~ 2,
    TRUE ~ 1
  ))

Create new column in dataframe using if {} else {} in R

The if statement is not suitable for this. You need to use ifelse:

activityTimeAvgs$stepsImp <- ifelse(is.na(activityTimeAvgs$steps), activityTimeAvgs$avgsteps, activityTimeAvgs$steps)

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