Muhammad Imdad Ullah

The post contains a Quiz about Python with Answers. The MCQs in this Python Quiz cover topics related to data frames in Python, some basic concepts, and an introduction to Python. Let us start with the quiz.

Online MCQs Python with Answers

1. What is indicated by the term null?

 The data has a value of zero

 The data is missing. correct

 The data has a value that is not stored for a variable in the dataset

 The data point is mandatory

2. We want to delete a list of columns from our data frame df. Which one of these methods is used to delete a column in a data frame?

 df.delete(axis=0, columns_list)

 df.delete(axis=1, columns_list)

 df.drop(axis=1, columns_list)

 df.drop(axis=0, columns_list)

3. We have a data frame called df. Which line of code aggregates the data based on a column (col_A) and counts the number of rows?

 df.groupby(‘col_A’).count()

 dg.groupby(‘col_A’).size(rows)

 df.groupby(‘col_A’).size()

 df.groupby(‘col_A’).count(rows)

4. We have a data frame called df, choose the correct pandas property that shows you the number of rows and columns in the data frame.

 df.dimension()

 df.shape

 df.dimensional

 df.shape()

5. We have a data frame called df. Which method is used to create a line chart of two columns $a$ and $b$?

 df.linechart(x=’a’, y=’b’)

 df.line(x=’a’, y=’b’)

 df.plt.line(x=’a’, y=’b’)

 df.plot(x=’a’, y=’b’)

6. A data professional is working with a NumPy array that has three rows and two columns. They want to change the data into two rows and three columns. What method can they use to do so?

 type()

 reshape()

 groupby()

 agg()

7. A data professional wants to merge two pandas’ data frames. They want to join the data so that only the keys that are in both data frames get included in the merge. What technique can they use to do so?

 Outer join

 Right join

 Inner join

 Left join

8. What will be the datatype of the output of df[‘A’] where ‘df’ is a data frame and ‘A’ is one of the columns?

 numpy array

 list

 Dataframe

 Series

9. How do you determine the median of data using Pandas?

 pd.mean(data)

 pd.median(data)

 data.median()

 data.mean()

10. What happens when you add an int and a float?

 You get a float

 You get an int

 You get a string

 You get a syntax error

11. What is the name of the attribute that we want to predict

 target (label)

 list

 feature

 dataframe

12. Which data structure is [1,2,3,4].

 Tuple

 Numpy array

 List

 Dictionary

13. Which method creates the correlation matrix of the numerical columns in a data frame df?

 df.plot.corr()

 df.correlation_matrix()

 df.corr()

 df.createCorr()

14. How would you get the columns for temperature and rainfall from a data frame using Python?

 dfTempRain = (data(‘Temperature’, ‘Rainfall’) )

 dfTempRain = (data[[‘Temprature’, ‘Rainfall’]])

 dfTempRain = data{[‘Temperature’, ‘Rainfall’]}

 dfTempRain = data([‘Temperature’, ‘Rainfall’])

15. What is the difference between a list and a tuple in Python?

 tuples are mutable, lists are immutable

 lists and tuples are both immutable

 lists and tuples are both mutable

 lists are mutable, tuples are immutable

16. We have a data frame called df, in which pandas property is used to check the columns’ data types.

 df.datatypes(columns_list)

 df.describe_columns()

 df.dtypes

 df.show_dtypes

17. Suppose you have a data frame named df What does the following method do to the data frame df.head(12)?

 Show the first 12 rows of data frame

 Shows the bottom 12 rows of data frame

 Shows the first 11 rows of the data frame

 Shows the first 12 columns of the data frame

18. What will be the datatype of the output of df[‘A’] where ‘df’ is a data frame and ‘A’ is one of the columns?

 numpy array

 Series

 list

 Dataframe

19. How would you access the column “symboling” from the data frame df?

 df[“symboling”]

 df ==”symboling”

 df=”symboling”

 df(“symboling”)

20. What is the syntax to create a tuple in Python?

 tuple =

 tuple = [1, 2, 3]

 tuple = (1, 2, 3)

 tuple = {1, 2, 3}

 Loading …

Python Quiz with Answers

• We have a data frame called df. Which line of code aggregates the data based on a column (col_A) and counts the number of rows?
• We have a data frame called df. Which method is used to create a line chart of two columns $a$ and $b$?
• We want to delete a list of columns from our data frame df. Which one of these methods is used to delete a column in a data frame?
• Which method creates the correlation matrix of the numerical columns in a data frame df?
• How would you access the column “symboling” from the data frame df?
• We have a data frame called df, in which the pandas property is used to check the columns’ data types.
• We have a data frame called df, choose the correct pandas property that shows you the number of rows and columns in the data frame.
• Suppose you have a data frame named df What does the following method do to the data frame df.head(12)?
• A data professional wants to merge two pandas’ data frames. They want to join the data so that only the keys that are in both data frames get included in the merge. What technique can they use to do so?
• How do you determine the median of data using Pandas?
• How would you get the columns for temperature and rainfall from a data frame using Python?
• What will be the datatype of the output of df[‘A’] where ‘df’ is a data frame and ‘A’ is one of the columns?
• What will be the datatype of the output of df[‘A’] where ‘df’ is a data frame and ‘A’ is one of the columns?
• A data professional is working with a NumPy array that has three rows and two columns. They want to change the data into two rows and three columns. What method can they use to do so?
• Which data structure is [1,2,3,4].
• What is indicated by the term null?
• What is the name of the attribute that we want to predict
• What is the difference between a list and a tuple in Python?
• What is the syntax to create a tuple in Python?
• What happens when you add an int and a float?

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Click the links below to start with important Online Python Quizzes. These Online Python Quizzes cover topics related to Python Basics, Data types, Data Structures, Functions, Libraries, Editors, Conditional Statements, Loops, Performing Data Analysis, etc.

Python is a powerful programming language widely used in statistics and other fields of life for data analysis.

Why Learn Python?

The following are important reasons why Python is a great language to learn:

• Simple and Easy Language: Python is a simple language that makes it an excellent choice for beginners to learn the fundamentals of programming.
• In-Demand Skill: Python is one of the most popular programming languages in the world, making it a valuable skill for various job opportunities.
• Wide Applications: Python has wide applications such as it is being used for web development, data analysis, machine learning, and more making it highly versatile.
• Active Community: The large and supportive Python community offers a wealth of resources and assistance for learners.

Python and Statistics

The following are the important reasons for the computations of different statistics in Python:

1. Ease of Use: Python has a clear and concise syntax, making it relatively easy to learn and use compared to other languages. This allows statisticians to focus on the analysis itself rather than struggling with complex code.
2. Extensive Libraries: Python boasts a rich ecosystem of statistical libraries. Here are some of the most popular ones:
   • statistics: Built-in module for basic descriptive statistics like mean, median, and standard deviation. Ideal for small datasets or even beginners of Python.
   • NumPy: The foundation for scientific computing in Python. Provides efficient arrays and functions for numerical computations commonly used in statistics.
   • SciPy: Extends NumPy with a wider range of statistical functions, including hypothesis testing, random number generation, and more.
   • Pandas: A library specifically designed for data manipulation and analysis. Offers data structures like DataFrames that make handling statistical data a breeze.

All of the above and other libraries provide a vast collection of tools for various statistical tasks, from data cleaning and exploration to complex modeling and statistical inference.

With its ease of use, vast capabilities, and supportive community, Python is an excellent computer programming language for beginners and experienced programmers alike. So, dive in and start exploring the exciting world of Python!

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The post contains 20 Top Python MCQs with Answers about basic concepts of the language. The quiz is about the Introduction to Python. Let us start with the Python MCQs with Answers

Please go to Top Python MCQs with Answers 1 to view the test

What is Python?

Python is a powerful, versatile, and beginner-friendly high-level programming language.

• Readability: With clear and simple syntax python resembles plain English. Therefore, Python code is easier to learn, understand, and write compared to some other programming languages.
• Large Standard Library: Python comes with a very huge collection of built-in modules, functions, and libraries as a toolkit for many tasks without needing to write everything from scratch.
• Versatility: Python is used in a wide range of applications, such as web development, data analysis, machine learning, scripting, scientific computing, etc.
• Strong Community: Python has a large and active community of developers, providing extensive support, libraries, and learning resources.

Top Python MCQs with Answers

• What is the primary instrument used in Pandas?
• What libraries do you use for data visualization.
• What data type do you expect the column that contains price to be
• Suppose you have a dataframe called $df$. Which pandas method is used to create a histogram of a column in a dataframe?
• What type of data can be stored in a list in Python?
• How do we create a dataframe using Pandas?
• What does method df.dropna() do?
• Which of the following is not important when writing Python code?
• What datatype would the following variable have main_data=read.csv(“path/to/myfile.csv”).
• Which Python libraries were used to create the boxplots?
• Which of the following is not comparison operator (these return a boolean value of true or false).
• Before using pandas which code must first be run to make the library available?
• In Python, ————- typically contain a collection of functions and global variables.
• A data professional is working with a pandas dataframe named $sales$ that contains sales data for a retail website. The data professional wants to know the average price of an item. What code can he use to calculate the mean value of the Price column?
• Given the variables below, determine which print statement would return False. a = True or False b = False and True c = False and False
• What is a Python library?
• How can we tell what version of Python we are currently using?
• Why is Python such a popular language?
• How would you generate descriptive statistics for all the columns for the dataframe $df$.
• Which of the following are not functions?

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