Зміст курсу
R Introduction: Part II
R Introduction: Part II
Columns Accessors
Since data frames have names on their columns, you should be able to extract necessary data using them.
There are several ways in R to refer to a particular column using naming. One of them is the same as in vectors and matrices: column name within square brackets (for example, data[, "col_name"]). The second way is unique for data frames - using the dollar $ sign. The syntax is data$col_name (yes, without quotation marks). For example, you can extract the column "Age" from the data frame created in the last chapter.
# Data name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") # Creating a data frame test <- data.frame(name, age, gender) # Extracting the name column using two ways test[,"name"] test$name
Завдання
Let's work with the mtcars dataset. Your tasks are:
- Extract the
cylcolumn values using square brackets. - Extract the
dispcolumn values using the dollar$sign.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
Columns Accessors
Since data frames have names on their columns, you should be able to extract necessary data using them.
There are several ways in R to refer to a particular column using naming. One of them is the same as in vectors and matrices: column name within square brackets (for example, data[, "col_name"]). The second way is unique for data frames - using the dollar $ sign. The syntax is data$col_name (yes, without quotation marks). For example, you can extract the column "Age" from the data frame created in the last chapter.
# Data name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") # Creating a data frame test <- data.frame(name, age, gender) # Extracting the name column using two ways test[,"name"] test$name
Завдання
Let's work with the mtcars dataset. Your tasks are:
- Extract the
cylcolumn values using square brackets. - Extract the
dispcolumn values using the dollar$sign.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
Columns Accessors
Since data frames have names on their columns, you should be able to extract necessary data using them.
There are several ways in R to refer to a particular column using naming. One of them is the same as in vectors and matrices: column name within square brackets (for example, data[, "col_name"]). The second way is unique for data frames - using the dollar $ sign. The syntax is data$col_name (yes, without quotation marks). For example, you can extract the column "Age" from the data frame created in the last chapter.
# Data name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") # Creating a data frame test <- data.frame(name, age, gender) # Extracting the name column using two ways test[,"name"] test$name
Завдання
Let's work with the mtcars dataset. Your tasks are:
- Extract the
cylcolumn values using square brackets. - Extract the
dispcolumn values using the dollar$sign.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
Since data frames have names on their columns, you should be able to extract necessary data using them.
There are several ways in R to refer to a particular column using naming. One of them is the same as in vectors and matrices: column name within square brackets (for example, data[, "col_name"]). The second way is unique for data frames - using the dollar $ sign. The syntax is data$col_name (yes, without quotation marks). For example, you can extract the column "Age" from the data frame created in the last chapter.
# Data name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") # Creating a data frame test <- data.frame(name, age, gender) # Extracting the name column using two ways test[,"name"] test$name
Завдання
Let's work with the mtcars dataset. Your tasks are:
- Extract the
cylcolumn values using square brackets. - Extract the
dispcolumn values using the dollar$sign.
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