Lists in R Language

The post is about Lists in R Language. It is in the form of questions and answers for creating lists, updating and removing the elements of a list, and manipulating the elements of Listsin R Language.

What are Lists in R Language?

Lists in R language are the objects that contain elements of different data types such as strings, numbers, vectors, and other lists inside the list. A list can contain a matrix or a function as its elements. The list is created using the list() function in R. In other words, a list is a generic vector containing other objects. For example, in the code below, the variable $X$ contains copies of three vectors, n, s, b, and a numeric value 3.

n = c(2, 3, 5)
s = c("a", "b", "c", "d")
b = c(TRUE, FALSE, TRUE, TRUE, FALSE, TRUE)

# create an ex that contains copies of n, s, b, and value 3
x = list(n, s, b, 3)

Explain How to Create a List in R Language

Let us create a list that contains strings, numbers, and logical values. for example,

data <- list("Green", "Blue", c(5, 6, 7, 8), TRUE, 17.5, 15:20)
print(data)

The print(data) will result in the following output.

Lists in R Language

How to Access Elements of the Lists in R Language?

To answer this, let us create a list first, that contains a vector, a list, and a matrix.

data <- list(c("Feb","Mar","Apr"), 13.4, matrix(c(3,9,5,1,-2,8), nrow = 2))

Now let us give names to the elements of the list created above and stored in the data variable.

names(data) <- c("Months", "Value", "Matrix")

data

## Output
$Months
[1] "Feb" "Mar" "Apr"

$Value
[1] 13.4

$Matrix
     [,1] [,2] [,3]
[1,]    3    5   -2
[2,]    9    1    8

To access the first element of a list by name or by index, one can type the following command.

# access the first element of the list
data[1]   #or print(data[1])
data$Months

## Output
$Months
[1] "Feb" "Mar" "Apr"

Similarly, to access the third element, use the command

# access the third element of the list
data[3]   #or print(data[3])  #or  data[[3]]
data$Matrix

## Output
$Months
[1] "Feb" "Mar" "Apr"

How Elements of the List are Manipulated in R?

To add an element at the end of the list, use the command

data[4] <- "New List Element(s)"

To remove the element of a list use

# Remove the first element of a list
data[1] <- NULL

To update certain elements of a list

data[2] = "Updated Element"

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MCQs Data Visualization in R 24

The Quiz is about MCQs Data Visualization in R Programming Language. There are 20 multiple-choice questions covering different topics related to R Language Programming. Let us start with the MCQs Data Visualization in R Language now.

MCQs Data Visualization in R Languages

Online Multiple Choice Questions about Data Visualization in R Programming Language

1. The qplot() function has no defaults, giving you more control over the output.

 
 

2. If you do not specify a theme when creating a plot with ggplot2, which theme does it use by default?

 
 
 
 

3. Which function is used to specify appropriate names for both axes in a plot?

 
 
 
 

4. Which plot type helps you visualize time series data?

 
 
 
 

5. Which parameter of the qplot() function changes the border color of the bars in a bar chart to blue?

 
 
 
 

6. How can you improve the smoothness of a histogram?

 
 
 
 

7. Which of the following statements about histograms is true?

 
 
 
 

8. What step must you take before you can add the coord_polar() function to ggplot() to create a pie chart?

 
 
 
 

9. Which function in ggplot adds a title to the plot?

 
 
 
 

10. Which functions can you use to change the title of a plot?

 
 
 
 

11. In a scatter plot, what is the best way to change the color of the points based on a categorical variable?

 
 
 
 

12. Which R statement creates a chart object based on the data frame “salesdata”, but allows you to vary the aesthetics from one layer to another?

 
 
 
 

13. You added text labels to the data points on your plot, but now the plot looks messy because there are so many of them. What should you do?

 
 
 
 

14. Which chart is a type of part of the whole chart?

 
 
 
 

15. Which ggplot2 function can create a complete plot given the data, mappings, and geom as parameters?

 
 
 
 

16. A pie chart is the same as a —————– in polar coordinates.

 
 
 
 

17. Which R packages will this course use to create data visualizations?

 
 
 
 

18. What information do you need to provide to create a visualization using the Leaflet library?

 
 
 
 

19. What can you add to a plot if you want to emphasize important elements, such as outliers or spikes in your data?

 
 
 
 

20. You want to divide a plot into subplots based on a categorical variable called “quarters”. Which function should you add to ggplot() to do this?

 
 
 
 

Online MCQs Data Visualization in R Language

  • Which function in ggplot adds a title to the plot?
  • Which function is used to specify appropriate names for both axes in a plot?
  • Which R statement creates a chart object based on the data frame “salesdata”, but allows you to vary the aesthetics from one layer to another?
  • The qplot() function has no defaults, giving you more control over the output.
  • Which R packages will this course use to create data visualizations?
  • Which chart is a type of part of the whole chart?
  • Which ggplot2 function can create a complete plot given the data, mappings, and geom as parameters?
  • Which of the following statements about histograms is true?
  • A pie chart is the same as a —————– in polar coordinates.
  • Which parameter of the qplot() function changes the border color of the bars in a bar chart to blue?
  • How can you improve the smoothness of a histogram?
  • What step must you take before you can add the coord_polar() function to ggplot() to create a pie chart?
  • In a scatter plot, what is the best way to change the color of the points based on a categorical variable?
  • Which plot type helps you visualize time series data?
  • Which functions can you use to change the title of a plot?
  • What can you add to a plot if you want to emphasize important elements, such as outliers or spikes in your data?
  • You want to divide a plot into subplots based on a categorical variable called “quarters”. Which function should you add to ggplot() to do this?
  • What information do you need to provide to create a visualization using the Leaflet library?
  • You added text labels to the data points on your plot, but now the plot looks messy because there are so many of them. What should you do?
  • If you do not specify a theme when creating a plot with ggplot2, which theme does it use by default?

statistics and data analysis

MCQs Jupyter Notebook Code Editors IDEs

This post is about the Python MCQs Jupyter Notebook Code Editors IDEs Online Test with Answers. It consists of 20 multiple-choice questions about Python IDEs such as Jupyter Notebooks, Visual Code Editor, Anaconda, Google Colab, Jypyter Lab, etc. Let’s start with the Python MCQs Online Test with Answers.

MCQs Jupyter Notebook Code Editors IDEs
Please go to MCQs Jupyter Notebook Code Editors IDEs to view the test

MCQs Jupyter Notebook Code Editors IDEs

  • What functionality is provided by the Jupyter Notebook file to Data Scientists?
  • What is the purpose of the kernel in the Jupyter Notebook?
  • What are the elements of Jupyter Notbook’s architecture?
  • What is the default kernel of JupyterLite?
  • What is the purpose of Anaconda?
  • In which formats can you share a notebook with other users?
  • What is a feature of a JupyterLab?
  • Which option outputs the currently highlighted code cell in Jupyter Notebook?
  • How can you switch the kernel in the Jupyter Notebook?
  • Which of the following can be used to work with Jupyter Notebook?
  • What do you use to convert the ipynb file to other formats?
  • What is one of the features of JupyterLite?
  • What is one of the features of Google Colab?
  • Which environment is used for creating and modifying Jupyter Notebooks on a local device?
  • How can you execute Python code in Visual Studio code?
  • Which of the following statements establishes the connection between a Jupyter Notebook SQL extension and an SQLite database ‘EMP.db’?
  • Which two of the following can be stated as uses of cell magic in Jupyter Notebooks?
  • What would be the outcome of the following Python code?
    import sqlite3
    import pandas as pd
    conn = sqlite3.connect(‘HR.db’)
    data = pd.read_csv(‘./employees.csv’)
    data.to_sql(‘Employees’, conn)
  • What would be the correct way to query a database table using Python? Assume that output in any form is acceptable.
  • Which of the following features are provided by Jupyter Notebook in the context of Python programming?

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