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R Introduction: Part II
course content

Contenido del Curso

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

bookdata.frame() Function

Good! Now you can see that data frames can be used to connect different data types. In the previous chapter, you considered one of the build-in datasets. How can we create a data frame with our data?

It can be done by using data.frame() function. This function receives vectors or lists (which we will consider in the next section) as columns. The names for columns are variable's names. For example, let's create a data frame with abstract information on three people.


              
12345678

            
# 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)
test # Outputting the data frame
copy

See, the names for columns come from variables names.

Tarea

Given two vectors: items and prices containing the names and prices of goods in an abstract local furniture store. Your tasks are:

  1. Create a data frame named store with two columns, items and prices (these are respective variables names).
  2. Output store variable value.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 2. Capítulo 2
toggle bottom row

bookdata.frame() Function

Good! Now you can see that data frames can be used to connect different data types. In the previous chapter, you considered one of the build-in datasets. How can we create a data frame with our data?

It can be done by using data.frame() function. This function receives vectors or lists (which we will consider in the next section) as columns. The names for columns are variable's names. For example, let's create a data frame with abstract information on three people.


              
12345678

            
# 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)
test # Outputting the data frame
copy

See, the names for columns come from variables names.

Tarea

Given two vectors: items and prices containing the names and prices of goods in an abstract local furniture store. Your tasks are:

  1. Create a data frame named store with two columns, items and prices (these are respective variables names).
  2. Output store variable value.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 2. Capítulo 2
toggle bottom row

bookdata.frame() Function

Good! Now you can see that data frames can be used to connect different data types. In the previous chapter, you considered one of the build-in datasets. How can we create a data frame with our data?

It can be done by using data.frame() function. This function receives vectors or lists (which we will consider in the next section) as columns. The names for columns are variable's names. For example, let's create a data frame with abstract information on three people.


              
12345678

            
# 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)
test # Outputting the data frame
copy

See, the names for columns come from variables names.

Tarea

Given two vectors: items and prices containing the names and prices of goods in an abstract local furniture store. Your tasks are:

  1. Create a data frame named store with two columns, items and prices (these are respective variables names).
  2. Output store variable value.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Good! Now you can see that data frames can be used to connect different data types. In the previous chapter, you considered one of the build-in datasets. How can we create a data frame with our data?

It can be done by using data.frame() function. This function receives vectors or lists (which we will consider in the next section) as columns. The names for columns are variable's names. For example, let's create a data frame with abstract information on three people.


              
12345678

            
# 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)
test # Outputting the data frame
copy

See, the names for columns come from variables names.

Tarea

Given two vectors: items and prices containing the names and prices of goods in an abstract local furniture store. Your tasks are:

  1. Create a data frame named store with two columns, items and prices (these are respective variables names).
  2. Output store variable value.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 2. Capítulo 2
Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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