Зміст курсу
R Introduction: Part II
R Introduction: Part II
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$Job <- c('Teacher', 'Doctor', 'Manager') test # Output data frame
You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame).
To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.
name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) test$Job <- c('Teacher', 'Doctor', 'Manager') # Drop 'gender' column subset(test, select = -gender)
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
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
storetoc('Item', 'Price'). - Add new column
'Sold'with the values ofc(67, 81, 79, 76, 42). - Output modified data frame.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
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$Job <- c('Teacher', 'Doctor', 'Manager') test # Output data frame
You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame).
To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.
name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) test$Job <- c('Teacher', 'Doctor', 'Manager') # Drop 'gender' column subset(test, select = -gender)
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
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
storetoc('Item', 'Price'). - Add new column
'Sold'with the values ofc(67, 81, 79, 76, 42). - Output modified data frame.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
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$Job <- c('Teacher', 'Doctor', 'Manager') test # Output data frame
You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame).
To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.
name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) test$Job <- c('Teacher', 'Doctor', 'Manager') # Drop 'gender' column subset(test, select = -gender)
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
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
storetoc('Item', 'Price'). - Add new column
'Sold'with the values ofc(67, 81, 79, 76, 42). - Output modified data frame.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
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$Job <- c('Teacher', 'Doctor', 'Manager') test # Output data frame
You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame).
To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.
name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) test$Job <- c('Teacher', 'Doctor', 'Manager') # Drop 'gender' column subset(test, select = -gender)
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
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
storetoc('Item', 'Price'). - Add new column
'Sold'with the values ofc(67, 81, 79, 76, 42). - Output modified data frame.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів