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.
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$Job <- c('Teacher', 'Doctor', 'Manager') test # Output data frame
You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame).
To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.
12345678name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) test$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.
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
storetoc('Item', 'Price'). - Add new column
Soldwith the values ofc(67, 81, 79, 76, 42). - Output modified data frame.
Lösung
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Completion rate improved to 2.27Manipulating Columns
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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.
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$Job <- c('Teacher', 'Doctor', 'Manager') test # Output data frame
You could also add this column using test[,'Job'] <- .... Also, note that the length of the vector of values you add must equal the number of rows in the data frame (i.e., you can not add a column with two values if there are ten rows in the data frame).
To remove column(s) out of data frame use subset() function, with the first parameter being data frame, and select = - ..., where ... is the name(s) of column(s) you want to drop. For example, we can drop 'gender' column.
12345678name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) test$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.
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
storetoc('Item', 'Price'). - Add new column
Soldwith the values ofc(67, 81, 79, 76, 42). - Output modified data frame.
Lösung
Wechseln Sie zum Desktop, um in der realen Welt zu übenFahren Sie dort fort, wo Sie sind, indem Sie eine der folgenden Optionen verwendenDanke für Ihr Feedback!
Awesome!
Completion rate improved to 2.27single
