Create Categories by Comparing a Numeric Column with a Fixed Value

Create categories by comparing a numeric column with a fixed value

Try

iris$Regulation <- ifelse(iris$Sepal.Length >=5, "UP", "DOWN")

Add column with values depending on another column to a dataframe

You can nest ifelse stataments. It's very handy when you are making categorical variables out of continuous ones.

data$c4 <- ifelse(data$c2 >= 0 & data$c2 <= 4, 'low',
                  ifelse(data$c2 >=5 & data$c2 <=9, 'medium',
                         ifelse(data$c2 >=10, 'High', 'something else')

matching values in different columns of a dataframe in r

A base R option

transform(
  df,
  C = c("miss","match")[(A==B)+1]
)

giving

  A B     C
1 a c  miss
2 x x match
3 t q  miss
4 l l match
5 w y  miss
6 b b match

Data

> dput(df)
structure(list(A = c("a", "x", "t", "l", "w", "b"), B = c("c", 
"x", "q", "l", "y", "b")), class = "data.frame", row.names = c("1",
"2", "3", "4", "5", "6"))

Assign a Value based on the numbers in a separate columns in R

You can use a simple ifelse :

df$new_col <- ifelse(df$likes > df$dislikes, 'positive', 'negative')

This can also be written without ifelse as :

df$new_col <- c('negative', 'positive')[as.integer(df$likes > df$dislikes) + 1]

How to add column into a dataframe based on condition? (without ifelse)

The first part effectively creates an object with two entries: the potential outcomes DOWN/UP. The second is a logical argument indexing one of those outcomes.

Might be easier if we create an object for the outcomes:

outcome <- c('DOWN','UP')

Square brackets index the object:

> outcome[ 2 ]
[1] "UP"

Inside the brackets is a logical statement returning FALSE/TRUE. Focusing only on the first 5 observations:

> iris[1:5,'Sepal.Length'] >= 5
[1]  TRUE FALSE FALSE FALSE  TRUE

Which store numerically as 0/1:

> as.numeric(iris[1:5,'Sepal.Length'] >= 5)
[1] 1 0 0 0 1

Addding 1 to the above returns 1s and 2s, which index either DOWN/UP in the outcomes object:

> condition[ (iris[1:5,'Sepal.Length'] >= 5) + 1 ]
[1] "UP"   "DOWN" "DOWN" "DOWN" "UP"

Extract AM/PM from Time in R

You can remove everything after colon, convert data to integer and assign 'PM' to all the values greater than 11 and "AM" otherwise.

df <- data.frame(Time = c('0:00', '1:00', '2:00', '13:00', '14:00'))
df$AMPM <- ifelse(as.integer(sub(':.*', '', df$Time)) > 11, 'PM', 'AM')
#Without ifelse
#c('AM', 'PM')[(as.integer(sub(':.*', '', x)) > 11) + 1]
df
#   Time AMPM
#1  0:00   AM
#2  1:00   AM
#3  2:00   AM
#4 13:00   PM
#5 14:00   PM

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