Muhammad Imdad Ullah

Student and Instructor of Statistics and business mathematics. Completed my Ph.D. in Statistics from the Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan. l like Applied Statistics, Mathematics and Statistical Computing. Statistical and Mathematical software used is SAS, STATA, GRETL, EVIEWS, R, SPSS, VBA in MS-Excel. Like to use type-setting LaTeX for composing Articles, thesis, etc.

Python NumPy MCQs 11

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These Python NumPy MCQs are designed to test your understanding of fundamental NumPy concepts, including array creation, manipulation, and common operations. The Python NumPy MCQs Quiz consists of multiple-choice questions (MCQs) covering essential topics such as:

  • Array creation (np.array(), np.zeros(), np.arange())
  • Array properties (.shape, .size)
  • Basic operations (dot product, arithmetic)
  • NumPy terminology

Each question is followed by the correct answer, making it useful for self-assessment, interviews, or exam preparation. Whether you are a beginner or an intermediate Python programmer, this Python Quiz helps reinforce key NumPy skills efficiently. Let us start with the Python NumPy MCQs now.

1. Which method returns the shape of a NumPy array?

 
 
 
 

2. Which of the following operations can be performed on NumPy arrays?

 
 
 
 
 

3. Which is the correct way to create a $2\times2$ NumPy array filled with ones?

 
 
 
 

4. Which function is used to create a NumPy array?

 
 
 
 

5. What line of code would produce the following: array([11, 11, 11, 11, 11])?

 
 
 
 

6. What does np.random.seed(42) do?

 
 
 
 

7. What Python libraries are commonly used for data mining?

 
 
 
 

8. Which of the following statements about creating and manipulating multi-dimensional arrays in Python using NumPy are true?

 
 
 
 
 

9. If you run the following lines of code, what values will the variable ‘out’ take?
X=np.array([[1,0],[0,1]])
Y=np.array([[2,2],[2,2]])
Z=np.dot(X,Y)

 
 
 
 

10. What outcome do the following lines of code produce?
a=np.array([0,1,0,1,0])
b=np.array([1,0,1,0,1])
a+b

 
 
 
 

11. What result will the following lines of code give?
a=np.array([0,1])
b=np.array([1,0])
np.dot(a,b)

 
 
 
 

12. Which of the following are valid ways to create a NumPy array?

 
 
 
 
 

13. If you run the following lines of code, what values will the variable ‘out’ take?
X=np.array([[1,0,1],[2,2,2]])
out=X[0:2,2]

 
 
 
 

14. What is the output of np.zeros((2,3))?

 
 
 
 

15. How do you access the element at the second row and third column of a 2D NumPy array ‘arr’?

 
 
 
 

16. After executing the given code, what value does $Z$ hold?
X=np.array([[1,0],[0,1]])
Y=np.array([[2,1],[1,2]])
Z=np.dot(X,Y)

 
 
 
 

17. What does np.arange(5) produce?

 
 
 
 

18. What does the value of $Z$ become after executing the following code?
X=np.array([[1,0],[0,1]])
Y=np.array([[0,1],[1,0]])
Z=X+Y

 

 
 
 
 

19. What is the primary purpose of the NumPy library in Python?

 
 
 
 

20. What does NumPy stand for?

 
 
 
 

Online Python NumPy MCQs with Answers

Online Python Numpy MCQs with Answers

  • What result will the following lines of code give?
    a=np.array([0,1])
    b=np.array([1,0]) np.dot(a,b)
  • What does the value of $Z$ become after executing the following code?
    X=np.array([[1,0], [0,1]])
    Y=np.array([[0,1], [1,0]])
    Z=X+Y  
  • If you run the following lines of code, what values will the variable ‘out’ take?
    X=np.array([[1,0,1],[2,2,2]])
    out=X[0:2,2]
  • If you run the following lines of code, what values will the variable ‘out’ take?
    X=np.array([[1,0], [0,1]])
    Y=np.array([[2,2], [2,2]])
    Z=np.dot(X,Y)
  • After executing the given code, what value does $Z$ hold?
    X=np.array([[1,0], [0,1]])
    Y=np.array([[2,1], [1,2]])
    Z=np.dot(X,Y)
  • What outcome do the following lines of code produce?
    a=np.array([0,1,0,1,0])
    b=np.array([1,0,1,0,1])
    a+b
  • What line of code would produce the following: array([11, 11, 11, 11, 11])?
  • Which is the correct way to create a $2\times2$ NumPy array filled with ones?
  • Which of the following are valid ways to create a NumPy array?
  • Which of the following operations can be performed on NumPy arrays?
  • How do you access the element at the second row and third column of a 2D NumPy array ‘arr’?
  • What is the primary purpose of the NumPy library in Python?
  • What Python libraries are commonly used for data mining?
  • What does NumPy stand for?
  • Which of the following statements about creating and manipulating multi-dimensional arrays in Python using NumPy are true?
  • Which function is used to create a NumPy array?
  • What is the output of np.zeros((2,3))?
  • Which method returns the shape of a NumPy array?
  • What does np.arange(5) produce?
  • What does np.random.seed(42) do?

Islamiat MCQs 9th Class Quiz

How to Save Data in R

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The post is about data in R language. Learn how to save and read data in R with this comprehensive guide. Discover methods like write.csv(), saveRDS(), and read.table(), understand keyboard input using readline(), scan(), and master file-based data loading for matrices and datasets. Perfect for beginners and intermediate R users!

How can you Save the Data in R Language?

To save data in R Language, there are many ways. The easiest way of saving data in R is to click Data –> Active Data Set –> Export Active Data. A dialogue box will appear. Click OK in the dialogue box. The data will be saved. The other ways to save data in R are:

Saving to CSV Files

# Base R package
write.csv(Your_DataFrae, "path/to/file.csv", row.names = FALSE)

#readr (tidyverse) Package
library(readr)
write_csv(your_DataFrame, "path/to/file.csv")

Saving to MS Excel Files

To save data to Excel files, the writexl or openxlsx package can be used

library(writexl)
write_xlsx(your_DataFrame, "path/to/file.xlsx")

Saving to R’s Native Formats

Single or Multiple objects can be saved to a single file, such as RData

# .RData file
save(object1, object2, file = "path/to/data.RData")

# .rds file
saveRDS(your_DataFrame, "path/to/data.rds")

Saving to Text Files

Data can be saved to text files using the following commands:

# Using Base R Package
write.table(your_DataFrame, "path/to/file.txt", sep = "\t", row.names = FALSE)

# using readr Package
write_delim(your_DataFrame, "path/to/file.txt", delim = "\t")

Saving to JSON File Format

The data can be saved to a JSON file format using the jsonlite package.

write_json(your_DataFrame, "path/to/file.json")

Saving Data to Databases

Write data to SQL databases (for example, SQLite, PostgreSQL), for example

library(DBI)
library(RSQLIte)

# Create a database connect
con <- dbConnect(RSQLite::SQLite(), "path/to/database.db")

# Write a data frame to the database
dbWriteTable(con, "table_name", your_DataFrame)

# Disconnect when done
dbDisconnect(con)

Saving Data to Other Statistical Software Formats

The haven package can be used to save data for SPSS, Stata, or SAS. For example

library(haven)
write_sav(your_DataFrame, "path/to/file.sav")  # SPSS file format
write_dta(your_DataFrame, "path/to/file.dta")  # STATA file format

It is important to note that

  • File Paths: Use absolute file paths, for example, D:/projects/data.csv, or relative paths such as data/file.csv.
  • Overwriting: By default, R will overwrite existing files. Add checks to avoid accidental loss, for example,
    if (!file.exists("file.csv")){
    write.csv(your_DataFrame, "file.csv")
    }

How to Read Data from the Keyboard?

To read the data from the keyboard, one can use the following functions

  • scan(): read data by directly pressing keyboard keys
  • deadline(): read text lines from a file connection
  • print(): used to display specified keystrokes on the display/monitor.

Explain How to Read Data or a Matrix from a File?

  • read.table(): usually read.table() function is used to read data. The default value of a header is set to “FALSE,” and hence, when we do not have a header, we need not use this argument.
  • Use read.csv() or read.table() function to import/read spreadsheet exported files in which columns are separated by commas instead of white spaces. For MS Excel file use, read.xls() function.
  • When you read in a matrix using read.table(), the resultant object will become a data frame, even when all the entries got to be numeric. The as.matrix() function can be used to read it into a matrix form like this
    as.matrix(x, nrow = 5, byrow=T)

What is scan() Function in R?

The scan() function is used to read data into a vector or list from the console or a file.

z <- scan()
1: 12 5
3: 5
4:
Read 3 items

z
### Output
12 5 5
Data in R Language

What is readline() Function in R?

The readline() function is used to read text lines from a connection. The readline() function is used for inputting a line from the keyboard in the form of a string. For example,

w <- readline()
xyz vw u

w

## Output

xyz vw u

Statistics and Data Analysis

Python Data Visualization Quiz 10

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This Python Data Visualization Quiz focuses on Python’s Matplotlib library, a fundamental tool for data visualization. This Python Quiz tests your understanding of key concepts, functions, and best practices in creating, customizing, and saving plots using Matplotlib. Let us start with the Python Data Visualization Quiz now.

Online Python Data Visualization Quiz with Answers
Please go to Python Data Visualization Quiz 10 to view the test

Online Python Data Visualization Quiz with Answers

  • Which of the following libraries is NOT mentioned as a high-level visualization library?
  • Matplotlib is a widely used Python data visualization library.
  • Which Matplotlib function is used to create histograms?
  • What are some of the key purposes of the Matplotlib library for data visualization?
  • What function in Matplotlib is used to create a basic line plot?
  • Which Matplotlib function would you use to create scatter plots that show the relationship between two arrays?
  • Which of the following are valid ways to create a bar plot in Matplotlib?
  • Which of the following can be created using the Matplotlib library?
  • What is the primary purpose of the Matplotlib library in Python?
  • Matplotlib was created by:
  • What is the code for the Matplotlib magic function?
  • Which two of the following are not examples of Matplotlib magic functions?
  • Which of the following is not a main layer of Matplotlib?
  • Matplotlib was initially developed as what kind of tool?
  • Matplotlib’s three main layers are: Backend, Artist, and Scripting.
  • When plotting directly with Matplotlib, the pyplot module offers a convenient way to create and customize plots quickly.
  • The first step when creating a histogram in matplotlib is to import matplotlib as ———— and its scripting interface as ————–.
  • What is the process of creating a scatter plot?
  • The Python library we used to plot the graphs is ————–.
  • How do you create a scatter plot in Matplotlib?

Statistics and Data Analysis