How to Write Ifelse Statement With Multiple Conditions in R

If else statement with multiple conditions and 4 outcomes

I get "Occaisonal" using your code.

Your if statements are looking at logical vectors, but returning one value for ALL rows, for example:

df[,2] is the whole column: 0.50 0.11 0.23 0.06 0.36 0.19

df[,2]>mean(relabund) returns a logical vector of:

TRUE FALSE FALSE FALSE TRUE FALSE

by using && you are performing a logical comparison to two logical vectors. As these vectors aren't the same, you always get false:

df[,2]>mean(relabund) && df[,3]>mean(freq)

==

c(TRUE, FALSE, FALSE, FALSE, TRUE, FALSE) && c(FALSE, FALSE, TRUE, FALSE, TRUE, FALSE)

==

FALSE

Also, df$Classification sets the column to be the same value, i.e. it's working on the whole dataset rather than row by row. What you need to do it perform vector operations on each row.

Using dplyr you can get an easier to read answer (for some!)

library(tidyverse)

species <- c("a", "b", "c", "d", "e", "f")
relabund <- c(.5, .11, .23, .06, .36, .19) #relative abundance
freq <- c(6, 3, 20, 2, 11, 4) #number of sites species occurs at
df = data.frame(species, relabund, freq)

df %>% 
  mutate(classify = 
           ifelse(freq < mean(freq) & relabund < mean(relabund),
                  "Rare",
           ifelse(freq < mean(freq) & relabund > mean(relabund),
                  "Occaisonal",
           ifelse(freq > mean(freq) & relabund < mean(relabund),
                 "Common",
           ifelse(freq > mean(freq) & relabund > mean(relabund),
                 "Dominant",
                 "ERROR")))))

How to use ifelse in r with multiple conditions to change another variable to NA

The assignment should be outside the ifelse

df$RAIN <- ifelse(df$STATION==1 & df$YEAR==2001, NA, df$RAIN)

Also, instead of repeating thee 'df$', it would be much easier if we wrap inside with

df$RAIN <- with(df, ifelse(STATION == 1 & YEAR == 2001, NA, RAIN))
df
#  STATION YEAR RAIN
#1       1 2000    5
#2       1 2001   NA
#3       1 2002    3
#4       2 2000    4
#5       2 2001    3
#6       2 2002    5

NOTE: In addition to the assignment, the && should be & as the former returns only a single TRUE/FALSE as output. Also, data.frame(cbind would mess up the types of columns as cbind returns a matrix first and matrix can have only a single class.

NA should not be quoted.

Regarding why only 5 is returned, as mentioned above the && returns a single TRUE/FALSE

df$STATION==1&&df$YEAR==2001
#[1] FALSE

In the ifelse, now the no part becomes active, and the first value for 'RAIN' is 5

ifelse(df$STATION==1&&df$YEAR==2001, NA,df$RAIN) # modified syntax related issues
#[1] 5

This gets assigned to the whole column

data

df <- data.frame(STATION,YEAR,RAIN)

How to make an ifelse statement with multiple conditions

The %in% operator allows you to check against a vector of possible values.

game$homewin <- ifelse(game$outcome %in% c("home win OT",
                    "home win REG", "home win SO"), 1, 0)

You could also take advantage of the fact that TRUE has a numerical representation of 1 and FALSE of 0 and write:

game$homewin <- as.numeric(game$outcome %in% c("home win OT",
                    "home win REG", "home win SO"))

multiple ifelse with and and or conditions in R

I think by multiple ifelse you mean nested ifelse. if that is the case, here is a solution

df$bigcity <- ifelse(grepl("london|paris", df$location), ifelse(grepl("2011|2012", df$year), 1, 0), 0)

what I did here is, IF the first condition is true, place the second condition in TRUE parameter.

Using if else statement for multiple conditions

This can be done using either ifelse

with(dat, ifelse(x < 0.15 & dif <0, 3, ifelse(x > 0.15 & dif < 0, 2, 1)))

with(dat, as.numeric(factor(1+4*(x < 0.15 & dif < 0) + 2*(x>=0.15 & dif < 0))))

R if statement with multiple conditions and multiple outcomes

Here's a simple approach using some math and logical vectors. This leverages the fact that + TRUE evaluates to 1.

First, make a character vector with the choices. Then Test if X1 is greater than the cutoff. That will equal 1 when TRUE. Then test if X2 is greater than the cutoff and multiply by 2. Then, add those two numbers together and add 1. The total will equal 1 when neither, 2 when X1 is greater, 3 when X2 is greater, and 4 when both are.

Finally, subset your character vector using the integer vector you just created.

test$above <- c("neither","X1","X2","both")[((test$X1 > cutoff.X1) + ((test$X2 > cutoff.X2) * 2)) + 1]
head(test,10)
   X1 X2   above
1  64 51      X1
2  39 31      X1
3  24 14      X1
4  74 57      X1
5  67 91    both
6   7  6 neither
7  14 78      X2
8  74 92    both
9  18 93      X2
10 27 31      X1

If you don't like that, there's always dplyr::case_when, which is admittedly easier to read:

library(dplyr)
test$above <- case_when(test$X1 > cutoff.X1 & test$X2 > cutoff.X2 ~ "both",
                        test$X1 > cutoff.X1 ~ "X1",
                        test$X2 > cutoff.X2 ~ "X2",
                        TRUE ~ "neither")

Just remember that case_when evaluates each condition until one evaluates TRUE, so be sure to put the "both" condition first.