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R Introduction: Part II
course content

Course Content

R Introduction: Part II

R Introduction: Part II

1. Matrices
What is a Matrix?matrix() FunctionTransposingMatrix IndexationNamingsOperation with MatricesSales and Revenue
2. Data Frames
What is a Data Frame?data.frame() FunctionColumns AccessorsLogical IndexingManipulating ColumnsManipulating RowsData Extraction
3. Lists
What is a List?NamingsExtracting List ElementsModifying

bookColumns 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.


              
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)

# Extracting the name column using two ways
test[,"name"]
test$name
copy

Task

Let's work with the mtcars dataset. Your tasks are:

  1. Extract the cyl column values using square brackets.
  2. Extract the disp column values using the dollar $ sign.

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Section 2. Chapter 3
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bookColumns 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.


              
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)

# Extracting the name column using two ways
test[,"name"]
test$name
copy

Task

Let's work with the mtcars dataset. Your tasks are:

  1. Extract the cyl column values using square brackets.
  2. Extract the disp column values using the dollar $ sign.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 3
toggle bottom row

bookColumns 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.


              
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)

# Extracting the name column using two ways
test[,"name"]
test$name
copy

Task

Let's work with the mtcars dataset. Your tasks are:

  1. Extract the cyl column values using square brackets.
  2. Extract the disp column values using the dollar $ sign.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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.


              
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)

# Extracting the name column using two ways
test[,"name"]
test$name
copy

Task

Let's work with the mtcars dataset. Your tasks are:

  1. Extract the cyl column values using square brackets.
  2. Extract the disp column values using the dollar $ sign.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 3
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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