Manipulating Columns

Let's continue to expand our data frames manipulation arsenal! :)

Next on the line - is adding/deleting columns. First, to add a new column, assign a vector of values to the column with a new name. You can do it by using either name in square brackets or the dollar $ sign. For example, let's add to the people data frame column with Job titles.

# Data

name <- c("Alex", "Julia", "Finn")

age <- c(24, 43, 32)

gender <- c("M", "F", "M")

# Creating a data frame

test <- data.frame(name, age, gender)

# Adding new column

test$Job <- c('Teacher', 'Doctor', 'Manager')

test # Output data frame


              12345678910
            
# Data
name <- c("Alex", "Julia", "Finn")
age <- c(24, 43, 32)
gender <- c("M", "F", "M")
# Creating a data frame
test <- data.frame(name, age, gender)

# Adding new column
test$Job <- c('Teacher', 'Doctor', 'Manager')
test # Output data frame

You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame). To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.

name <- c("Alex", "Julia", "Finn")

age <- c(24, 43, 32)

gender <- c("M", "F", "M")

test <- data.frame(name, age, gender)

test$Job <- c('Teacher', 'Doctor', 'Manager')

# Drop 'gender' column

subset(test, select = -gender)


              12345678
            
name <- c("Alex", "Julia", "Finn")
age <- c(24, 43, 32)
gender <- c("M", "F", "M")
test <- data.frame(name, age, gender)
test$Job <- c('Teacher', 'Doctor', 'Manager')

# Drop 'gender' column
subset(test, select = -gender)

And lastly, if you want to change column names, use the same approach as for matrices - colnames() function. Remember, colnames(data) <- new_names is the syntax for this operation.

Завдання

Swipe to start coding

Given data frame store with the information on items and their prices in a small furniture store. Currently, it looks like this:

items	prices
Sofa	340
Armchair	150
Dining table	115
Dining chair	45
Bookshelf	160

You need to transform this table into this:

Item	Price	Sold
Sofa	340	67
Armchair	150	81
Dining table	115	79
Dining chair	45	76
Bookshelf	160	42

Follow the next steps:

Rename the columns names of store to c('Item', 'Price').
Add new column Sold with the values of c(67, 81, 79, 76, 42).
Output modified data frame.

Рішення

# Data

prices <- c(340, 150, 115, 45, 160)

items <- c('Sofa', 'Armchair', 'Dining table', 'Dining chair', 'Bookshelf')

store <- data.frame(items, prices)

# Rename the columns

colnames(store) <- c("Item", "Price")

# Add new column

store$Sold <- c(67, 81, 79, 76, 42)

# Output modified data frame

store

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Секція 2. Розділ 5

# Data

prices <- c(340, 150, 115, 45, 160)

items <- c('Sofa', 'Armchair', 'Dining table', 'Dining chair', 'Bookshelf')

store <- data.frame(items, prices)

# Rename the columns

___(___) <- c("___", "___")

# Add new column

store$___ <- c(67, ___, ___, 76, 42)

# Output modified data frame

___