Create new variables in data frames

Create a new variable in a dataset with missing values

Please copy this syntax into R-Studio and execute:

study <- data.frame(
  sen    = factor(c(0, 1, 0, 1, 0, 1), labels = c("no sen", "sen"), levels = 0:1),
  gender = factor(c(1,2,2,1,2,1), labels = c("Male", "Female"), levels = 1:2),
  age  = c(150, 156, 138, 126, 136, 162),
  IQ     = c(90, 85, 90, 87, 99, 89),
  Q1     = c(1, 5, 3, 4, 2, 3),
  Q2     = c(2, 5, 3, 4, 5, 2),
  Q3     = c(1, 5, 3, 5, 2, 1)
)

Create a new variable in a dataset

With missing values:

study$Q4 <- NA

With specific values:

study$Q5 <- c(5, 1, 4, 2, 1, 3)
study

sen	gender	age	IQ	Q1	Q2	Q3	Q4	Q5
no sen	Male	150	90	1	2	1	NA	5
sen	Female	156	85	5	5	5	NA	1
no sen	Female	138	90	3	3	3	NA	4
sen	Male	126	87	4	4	5	NA	2
no sen	Female	136	99	2	5	2	NA	1
sen	Male	162	89	3	2	1	NA	3

Create new variables from existing ones

study$age2 <- study$age / 12
study

sen	gender	age	IQ	Q1	Q2	Q3	Q4	Q5	age2
no sen	Male	150	90	1	2	1	NA	5	12.50000
sen	Female	156	85	5	5	5	NA	1	13.00000
no sen	Female	138	90	3	3	3	NA	4	11.50000
sen	Male	126	87	4	4	5	NA	2	10.50000
no sen	Female	136	99	2	5	2	NA	1	11.33333
sen	Male	162	89	3	2	1	NA	3	13.50000

Drop a variable

study$age2 <- NULL
study

sen	gender	age	IQ	Q1	Q2	Q3	Q4	Q5
no sen	Male	150	90	1	2	1	NA	5
sen	Female	156	85	5	5	5	NA	1
no sen	Female	138	90	3	3	3	NA	4
sen	Male	126	87	4	4	5	NA	2
no sen	Female	136	99	2	5	2	NA	1
sen	Male	162	89	3	2	1	NA	3

# or: study <- subset(study, select = -age2)
# or: study <- study[, -10]

Task

Create a new variable Q_sum_1_3 as the sum of Q1 to Q3.

study$Q_sum_1_3 <- with(study, Q1 + Q2 + Q3)

# or:

study$Q_sum_1_3 <- study$Q1 + study$Q2 + study$Q3

study$Q_sum_1_3

[1]  4 15  9 13  9  6

Task

Create the variables age_year and age_month where both variables do not have decimals

Use the trunc function or the %% modulo and the integer division %/% operators. Use the help function if needed)

study$age_year <- trunc(study$age /12)
study$age_month <- study$age - (study$age_year * 12)

# or

study$age_year <- study$age %/% 12
study$age_month <- study$age %% 12

study[, c("age", "age_year", "age_month")]

age	age_year	age_month
150	12	6
156	13	0
138	11	6
126	10	6
136	11	4
162	13	6

# or: study[, startsWith(names(study), "age")]

The apply function

The apply function applies a function to every row or column of a data frame.

The first argument is the data frame object.
The second argument is the margin (1 for rows and 2 for columns).
The third argument is a function name (e.g. mean).
Further arguments are arguments to the function provided in 3.

# An example:
study$Q_sum_1_2 <- apply(study[, c("Q1", "Q2")], 1, sum)
study$Q_sum_1_2

[1]  3 10  6  8  7  5

Task

Create a new variable Q_sum with the sum of Q1 to Q5 (sums should be build when NAs are in the data)

vars <- c("Q1", "Q2", "Q3", "Q4", "Q5")

study$Q_sum <- apply(study[, vars], 1, sum, na.rm = TRUE)
study$Q_sum

[1]  9 16 13 15 10  9