Subscribe Categories Online Courses Mock Interviews Webinars NEW Community Write for Us Categories Artificial Intelligence BI and Visualization Big Data Blockchain Cloud Computing Cyber Security Data Science Data Warehousing and ETL Databases DevOps Front End Web Development Mobile Development Operating Systems Programming & Frameworks Project Management and Methodologies Robotic Process Automation Software Testing Home Blog Data Science Top 100 Python Interview Quest... Top 50 Important OOPs Interview Questions and Answers Top 100 Python Interview Questions You Must Prepare In 2020 Top Python Projects You Should Consider Learning Top 100 Python Interview Questions You Must Prepare In 2020 Last updated on May 07,2020954.8K Views Aayushi JohariAayushi Johari A technophile who likes writing about different technologies and spreading knowledge. 2 / 3 Blog from Interview Questions Python Certification is the most sought-after skill in programming domain. In this Python Interview Questions blog, I will introduce you to the most frequently asked questions in Python interviews. Our Python Interview Questions is the one-stop resource from where you can boost your interview preparation. We have 100+ questions on Python Programming basics which will help you with different expertise levels to reap the maximum benefit from our blog. Want to Upskill yourself to get ahead in Career? Check out the Top Trending Technologies. Let us start by taking a look at some of the most frequently asked Python interview questions. Q1. What is the difference between list and tuples in Python? Q2. What are the key features of Python? Q3. What type of language is python? Q4. How is Python an interpreted language? Q5. What is pep 8? Q6. How is memory managed in Python? Q7. What is name space in Python? Q8. What is PYTHON PATH? Q9. What are python modules? Q10. What are local variables and global variables in Python? We have compiled a list of top Python interview questions which are classified into 7 sections, namely: Basic Interview Questions OOPS Interview Questions Basic Python Programs Python Libraries Interview Questions Web Scraping Interview Questions Data Analysis Interview Questions Multiple Choice Questions (MCQ) Before moving ahead, you may go through the recording of Python Interview Questions where our instructor has shared his experience and expertise that will help you to crack any Python Interview: Python Interview Questions And Answers | Python Training | Edureka If you have other doubts regarding Python, feel free to post them in our QnA Forum. Our expert team will get back to you at the earliest. Basic Python Interview Questions Q1. What is the difference between list and tuples in Python? LIST vs TUPLES LI T TUPLES Lists are mutable i.e they can be edited . Tuples are immutable (tuples are lists which can’t be edited). Lists are slower than tupl s. Tuples are faster than list. Syntax: list_1 = [10, ‘Chelsea’, 20] Syntax: tup_1 = (10, ‘Chelsea’ , 20) Q2. What are the key features of Python? Python is an interpreted language. That means that, unlike languages like C and its variants, Python does not need to be compiled before it is run. Other interpreted languages include PHP and Ruby. Python is dynamically typed, this means that you don’t need to state the types of variables when you declare them or anything like that. You can do things like x=111 and then x="I'm a string" without error Python is well suited to object orientated programming in that it allows the definition of classes along with composition and inheritance. Python does not have access specifiers (like C++’s public, private). In Python, functions are first-class objects. This means that they can be assigned to variables, returned from other functions and passed into functions. Classes are also first class objects Writing Python code is quick but running it is often slower than compiled languages. Fortunately，Python allows the inclusion of C based extensions so bottlenecks can be optimized away and often are. The numpy package is a good example of this, it’s really quite quick because a lot of the number crunching it does isn’t actually done by Python Python finds use in many spheres – web applications, automation, scientific modeling, big data applications and many more. It’s also often used as “glue” code to get other languages and components to play nice. Q3. What type of language is python? Programming or scripting? Ans: Python is capable of scripting, but in general sense, it is considered as a general-purpose programming language. To know more about Scripting, you can refer to the Python Scripting Tutorial. Q4.How is Python an interpreted language? Ans: An interpreted language is any programming language which is not in machine level code before runtime. Therefore, Python is an interpreted language. Q5.What is pep 8? Ans: PEP stands for Python Enhancement Proposal. It is a set of rules that specify how to format Python code for maximum readability. Q6. How is memory managed in Python? Ans: Memory management in python is managed by Python private heap space. All Python objects and data structures are located in a private heap. The programmer does not have access to this private heap. The python interpreter takes care of this instead. The allocation of heap space for Python objects is done by Python’s memory manager. The core API gives access to some tools for the programmer to code. Python also has an inbuilt garbage collector, which recycles all the unused memory and so that it can be made available to the heap space. Q7. What is namespace in Python? Ans: A namespace is a naming system used to make sure that names are unique to avoid naming conflicts. Q8. What is PYTHONPATH? Ans: It is an environment variable which is used when a module is imported. Whenever a module is imported, PYTHONPATH is also looked up to check for the presence of the imported modules in various directories. The interpreter uses it to determine which module to load. Q9. What are python modules? Name some commonly used built-in modules in Python? Ans: Python modules are files containing Python code. This code can either be functions classes or variables. A Python module is a .py file containing executable code. Some of the commonly used built-in modules are: os sys math random data time JSON Q10.What are local variables and global variables in Python? Global Variables: Variables declared outside a function or in global space are called global variables. These variables can be accessed by any function in the program. Local Variables: Any variable declared inside a function is known as a local variable. This variable is present in the local space and not in the global space. Example: 1 2 3 4 5 6 a=2 def add(): b=3 c=a+b print(c) add() Output: 5 When you try to access the local variable outside the function add(), it will throw an error. Q11. Is python case sensitive? Ans: Yes. Python is a case sensitive language. Q12.What is type conversion in Python? Ans: Type conversion refers to the conversion of one data type iinto another. int() – converts any data type into integer type float() – converts any data type into float type ord() – converts characters into integer hex() – converts integers to hexadecimal oct() – converts integer to octal tuple() – This function is used to convert to a tuple. set() – This function returns the type after converting to set. list() – This function is used to convert any data type to a list type. dict() – This function is used to convert a tuple of order (key,value) into a dictionary. str() – Used to convert integer into a string. complex(real,imag) – This functionconverts real numbers to complex(real,imag) number. Q13. How to install Python on Windows and set path variable? Ans: To install Python on Windows, follow the below steps: Install python from this link: https://www.python.org/downloads/ After this, install it on your PC. Look for the location where PYTHON has been installed on your PC using the following command on your command prompt: cmd python. Then go to advanced system settings and add a new variable and name it as PYTHON_NAME and paste the copied path. Look for the path variable, select its value and select ‘edit’. Add a semicolon towards the end of the value if it’s not present and then type %PYTHON_HOME% Q14. Is indentation required in python? Ans: Indentation is necessary for Python. It specifies a block of code. All code within loops, classes, functions, etc is specified within an indented block. It is usually done using four space characters. If your code is not indented necessarily, it will not execute accurately and will throw errors as well. Q15. What is the difference between Python Arrays and lists? Ans: Arrays and lists, in Python, have the same way of storing data. But, arrays can hold only a single data type elements whereas lists can hold any data type elements. Example: 1 2 3 4 5 import array as arr My_Array=arr.array('i',[1,2,3,4]) My_list=[1,'abc',1.20] print(My_Array) print(My_list) Output: array(‘i’, [1, 2, 3, 4]) [1, ‘abc’, 1.2] Q16. What are functions in Python? Ans: A function is a block of code which is executed only when it is called. To define a Python function, the def keyword is used. Example: 1 2 3 def Newfunc(): print("Hi, Welcome to Edureka") Newfunc(); #calling the function Output: Hi, Welcome to Edureka Q17.What is __init__? Ans: __init__ is a method or constructor in Python. This method is automatically called to allocate memory when a new object/ instance of a class is created. All classes have the __init__ method. Here is an example of how to use it. 1 2 3 4 5 6 7 8 9 10 11 class Employee: def __init__(self, name, age,salary): self.name = name self.age = age self.salary = 20000 E1 = Employee("XYZ", 23, 20000) # E1 is the instance of class Employee. #__init__ allocates memory for E1. print(E1.name) print(E1.age) print(E1.salary) Output: XYZ 23 20000 Q18.What is a lambda function? Ans: An anonymous function is known as a lambda function. This function can have any number of parameters but, can have just one statement. Example: 1 2 a = lambda x,y : x+y print(a(5, 6)) Output: 11 Q19. What is self in Python? Ans: Self is an instance or an object of a class. In Python, this is explicitly included as the first parameter. However, this is not the case in Java where it’s optional. It helps to differentiate between the methods and attributes of a class with local variables. The self variable in the init method refers to the newly created object while in other methods, it refers to the object whose method was called. Q20. How does break, continue and pass work? B eak Allows loop termination when some condition is met and the control is transferred to the next statement. Cont nue Allows skipping some part of a loop when some specific condition is met and the control is transferred to the beginning of the loop Pass Used when you need some block of code syntactically, but you want to skip its execution. This is basically a null operation. Nothing happens when this is executed. Q21. What does [::-1} do? Ans: [::-1] is used to reverse the order of an array or a sequence. For example: 1 2 3 import array as arr My_Array=arr.array('i',[1,2,3,4,5]) My_Array[::-1] Output: array(‘i’, [5, 4, 3, 2, 1]) [::-1] reprints a reversed copy of ordered data structures such as an array or a list. the original array or list remains unchanged. Q22. How can you randomize the items of a list in place in Python? Ans: Consider the example shown below: 1 2 3 4 from random import shuffle x = ['Keep', 'The', 'Blue', 'Flag', 'Flying', 'High'] shuffle(x) print(x) The output of the following code is as below. ['Flying', 'Keep', 'Blue', 'High', 'The', 'Flag'] Q23. What are python iterators? Ans: Iterators are objects which can be traversed though or iterated upon. Q24. How can you generate random numbers in Python? Ans: Random module is the standard module that is used to generate a random number. The method is defined as: 1 2 import random random.random The statement random.random() method return the floating point number that is in the range of [0, 1). The function generates random float numbers. The methods that are used with the random class are the bound methods of the hidden instances. The instances of the Random can be done to show the multi-threading programs that creates a different instance of individual threads. The other random generators that are used in this are: randrange(a, b): it chooses an integer and define the range in-between [a, b). It returns the elements by selecting it randomly from the range that is specified. It doesn’t build a range object. uniform(a, b): it chooses a floating point number that is defined in the range of [a,b).Iyt returns the floating point number normalvariate(mean, sdev): it is used for the normal distribution where the mu is a mean and the sdev is a sigma that is used for standard deviation. The Random class that is used and instantiated creates an independent multiple random number generators. Q25. What is the difference between range & xrange? Ans: For the most part, xrange and range are the exact same in terms of functionality. They both provide a way to generate a list of integers for you to use, however you please. The only difference is that range returns a Python list object and x range returns an xrange object. This means that xrange doesn’t actually generate a static list at run-time like range does. It creates the values as you need them with a special technique called yielding. This technique is used with a type of object known as generators. That means that if you have a really gigantic range you’d like to generate a list for, say one billion, xrange is the function to use. This is especially true if you have a really memory sensitive system such as a cell phone that you are working with, as range will use as much memory as it can to create your array of integers, which can result in a Memory Error and crash your program. It’s a memory hungry beast. Q26. How do you write comments in python? Ans: Comments in Python start with a # character. However, alternatively at times, commenting is done using docstrings(strings enclosed within triple quotes). Example: #Comments in Python start like this print("Comments in Python start with a #") Output: Comments in Python start with a # Q27. What is pickling and unpickling? Ans: Pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using dump function, this process is called pickling. While the process of retrieving original Python objects from the stored string representation is called unpickling. Course Curriculum Python Certification Training for Data Science Q28. What are the generators in python? Ans: Functions that return an iterable set of items are called generators. Q29. How will you capitalize the first letter of string? Ans: In Python, the capitalize() method capitalizes the first letter of a string. If the string already consists of a capital letter at the beginning, then, it returns the original string. Q30. How will you convert a string to all lowercase? Ans: To convert a string to lowercase, lower() function can be used. Example: 1 2 stg='ABCD' print(stg.lower()) Output: abcd Q31. How to comment multiple lines in python? Ans: Multi-line comments appear in more than one line. All the lines to be commented are to be prefixed by a #. You can also a very good shortcut method to comment multiple lines. All you need to do is hold the ctrl key and left click in every place wherever you want to include a # character and type a # just once. This will comment all the lines where you introduced your cursor. Q32.What are docstrings in Python? Ans: Docstrings are not actually comments, but, they are documentation strings. These docstrings are within triple quotes. They are not assigned to any variable and therefore, at times, serve the purpose of comments as well. Example: 1 2 3 4 5 6 7 8 """ Using docstring as a comment. This code divides 2 numbers """ x=8 y=4 z=x/y print(z) Output: 2.0 Q33. What is the purpose of is, not and in operators? Ans: Operators are special functions. They take one or more values and produce a corresponding result. is: returns true when 2 operands are true (Example: “a” is ‘a’) not: returns the inverse of the boolean value in: checks if some element is present in some sequence Q34. What is the usage of help() and dir() function in Python? Ans: Help() and dir() both functions are accessible from the Python interpreter and used for viewing a consolidated dump of built-in functions. Help() function: The help() function is used to display the documentation string and also facilitates you to see the help related to modules, keywords, attributes, etc. Dir() function: The dir() function is used to display the defined symbols. Q35. Whenever Python exits, why isn’t all the memory de-allocated? Ans: Whenever Python exits, especially those Python modules which are having circular references to other objects or the objects that are referenced from the global namespaces are not always de-allocated or freed. It is impossible to de-allocate those portions of memory that are reserved by the C library. On exit, because of having its own efficient clean up mechanism, Python would try to de-allocate/destroy every other object. Q36. What is a dictionary in Python? Ans: The built-in datatypes in Python is called dictionary. It defines one-to-one relationship between keys and values. Dictionaries contain pair of keys and their corresponding values. Dictionaries are indexed by keys. Let’s take an example: The following example contains some keys. Country, Capital & PM. Their corresponding values are India, Delhi and Modi respectively. 1 dict={'Country':'India','Capital':'Delhi','PM':'Modi'} 1 print dict[Country] India 1 print dict[Capital] Delhi 1 print dict[PM] Modi Q37. How can the ternary operators be used in python? Ans: The Ternary operator is the operator that is used to show the conditional statements. This consists of the true or false values with a statement that has to be evaluated for it. Syntax: The Ternary operator will be given as: [on_true] if [expression] else [on_false]x, y = 25, 50big = x if x < y else y Example: The expression gets evaluated like if x Output: Enter the terms 5 0 1 1 2 3 Q68. Write a program in Python to check if a number is prime. 1 2 3 4 5 6 7 8 9 10 a=int(input("enter number")) if a>1: for x in range(2,a): if(a%x)==0: print("not prime") break else: print("Prime") else: print("not prime") Output: enter number 3 Prime Q69. Write a program in Python to check if a sequence is a Palindrome. 1 2 3 4 5 6 a=input("enter sequence") b=a[::-1] if a==b: print("palindrome") else: print("Not a Palindrome") Output: enter sequence 323 palindrome Q70. Write a one-liner that will count the number of capital letters in a file. Your code should work even if the file is too big to fit in memory. Ans: Let us first write a multiple line solution and then convert it to one-liner code. 1 2 3 4 5 6 with open(SOME_LARGE_FILE) as fh: count = 0 text = fh.read() for character in text: if character.isupper(): count += 1 We will now try to transform this into a single line. 1 count sum(1 for line in fh for character in line if character.isupper()) Q71. Write a sorting algorithm for a numerical dataset in Python. Ans: The following code can be used to sort a list in Python: 1 2 3 4 list = ["1", "4", "0", "6", "9"] list = [int(i) for i in list] list.sort() print (list) Q72. Looking at the below code, write down the final values of A0, A1, …An. 1 2 3 4 5 6 7 A0 = dict(zip(('a','b','c','d','e'),(1,2,3,4,5))) A1 = range(10)A2 = sorted([i for i in A1 if i in A0]) A3 = sorted([A0[s] for s in A0]) A4 = [i for i in A1 if i in A3] A5 = {i:i*i for i in A1} A6 = [[i,i*i] for i in A1] print(A0,A1,A2,A3,A4,A5,A6) Ans: The following will be the final outputs of A0, A1, … A6 A0 = {'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4} # the order may vary A1 = range(0, 10) A2 = [] A3 = [1, 2, 3, 4, 5] A4 = [1, 2, 3, 4, 5] A5 = {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81} A6 = [[0, 0], [1, 1], [2, 4], [3, 9], [4, 16], [5, 25], [6, 36], [7, 49], [8, 64], [9, 81]] Python Libraries Interview Questions Q73. Explain what Flask is and its benefits? Ans: Flask is a web microframework for Python based on “Werkzeug, Jinja2 and good intentions” BSD license. Werkzeug and Jinja2 are two of its dependencies. This means it will have little to no dependencies on external libraries. It makes the framework light while there is a little dependency to update and fewer security bugs. A session basically allows you to remember information from one request to another. In a flask, a session uses a signed cookie so the user can look at the session contents and modify. The user can modify the session if only it has the secret key Flask.secret_key. Q74. Is Django better than Flask? Ans: Django and Flask map the URL’s or addresses typed in the web browsers to functions in Python. Flask is much simpler compared to Django but, Flask does not do a lot for you meaning you will need to specify the details, whereas Django does a lot for you wherein you would not need to do much work. Django consists of prewritten code, which the user will need to analyze whereas Flask gives the users to create their own code, therefore, making it simpler to understand the code. Technically both are equally good and both contain their own pros and cons. Q75. Mention the differences between Django, Pyramid and Flask. Ans: Flask is a “microframework” primarily build for a small application with simpler requirements. In flask, you have to use external libraries. Flask is ready to use. Pyramid is built for larger applications. It provides flexibility and lets the developer use the right tools for their project. The developer can choose the database, URL structure, templating style and more. Pyramid is heavy configurable. Django can also be used for larger applications just like Pyramid. It includes an ORM. Q76. Discuss Django architecture. Ans: Django MVT Pattern: Django Architecture - Python Interview Questions - EdurekaFigure: Python Interview Questions – Django Architecture The developer provides the Model, the view and the template then just maps it to a URL and Django does the magic to serve it to the user. Q77. Explain how you can set up the Database in Django. Ans: You can use the command edit mysite/setting.py, it is a normal python module with module level representing Django settings. Django uses SQLite by default; it is easy for Django users as such it won’t require any other type of installation. In the case your database choice is different that you have to the following keys in the DATABASE ‘default’ item to match your database connection settings. Engines: you can change the database by using ‘django.db.backends.sqlite3’ , ‘django.db.backeneds.mysql’, ‘django.db.backends.postgresql_psycopg2’, ‘django.db.backends.oracle’ and so on Name: The name of your database. In the case if you are using SQLite as your database, in that case, database will be a file on your computer, Name should be a full absolute path, including the file name of that file. If you are not choosing SQLite as your database then settings like Password, Host, User, etc. must be added. Django uses SQLite as a default database, it stores data as a single file in the filesystem. If you do have a database server—PostgreSQL, MySQL, Oracle, MSSQL—and want to use it rather than SQLite, then use your database’s administration tools to create a new database for your Django project. Either way, with your (empty) database in place, all that remains is to tell Django how to use it. This is where your project’s settings.py file comes in. We will add the following lines of code to the setting.py file: 1 2 3 4 5 6 DATABASES = { 'default': { 'ENGINE' : 'django.db.backends.sqlite3', 'NAME' : os.path.join(BASE_DIR, 'db.sqlite3'), } } Q78. Give an example how you can write a VIEW in Django? Ans: This is how we can use write a view in Django: 1 2 3 4 5 6 7 from django.http import HttpResponse import datetime def Current_datetime(request): now = datetime.datetime.now() html = "It is now %s % now return HttpResponse(html) Returns the current date and time, as an HTML document Q79. Mention what the Django templates consist of. Ans: The template is a simple text file. It can create any text-based format like XML, CSV, HTML, etc. A template contains variables that get replaced with values when the template is evaluated and tags (% tag %) that control the logic of the template. Django Template - Python Interview Questions - EdurekaFigure: Python Interview Questions – Django Template Q80. Explain the use of session in Django framework? Ans: Django provides a session that lets you store and retrieve data on a per-site-visitor basis. Django abstracts the process of sending and receiving cookies, by placing a session ID cookie on the client side, and storing all the related data on the server side. Django Framework - Python Interview Questions - EdurekaFigure: Python Interview Questions – Django Framework So the data itself is not stored client side. This is nice from a security perspective. Q81. List out the inheritance styles in Django. Ans: In Django, there are three possible inheritance styles: Abstract Base Classes: This style is used when you only want parent’s class to hold information that you don’t want to type out for each child model. Multi-table Inheritance: This style is used If you are sub-classing an existing model and need each model to have its own database table. Proxy models: You can use this model, If you only want to modify the Python level behavior of the model, without changing the model’s fields. Web Scraping – Python Interview Questions Q82. How To Save An Image Locally Using Python Whose URL Address I Already Know? Ans: We will use the following code to save an image locally from an URL address 1 2 import urllib.request urllib.request.urlretrieve("URL", "local-filename.jpg") Q83. How can you Get the Google cache age of any URL or web page? Ans: Use the following URL format: http://webcache.googleusercontent.com/search?q=cache:URLGOESHERE Be sure to replace “URLGOESHERE” with the proper web address of the page or site whose cache you want to retrieve and see the time for. For example, to check the Google Webcache age of edureka.co you’d use the following URL: http://webcache.googleusercontent.com/search?q=cache:edureka.co Q84. You are required to scrap data from IMDb top 250 movies page. It should only have fields movie name, year, and rating. Ans: We will use the following lines of code: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 from bs4 import BeautifulSoup import requests import sys url = 'http://www.imdb.com/chart/top' response = requests.get(url) soup = BeautifulSoup(response.text) tr = soup.findChildren("tr") tr = iter(tr) next(tr) for movie in tr: title = movie.find('td', {'class': 'titleColumn'} ).find('a').contents[0] year = movie.find('td', {'class': 'titleColumn'} ).find('span', {'class': 'secondaryInfo'}).contents[0] rating = movie.find('td', {'class': 'ratingColumn imdbRating'} ).find('strong').contents[0] row = title + ' - ' + year + ' ' + ' ' + rating print(row) The above code will help scrap data from IMDb’s top 250 list Data Analysis – Python Interview Questions Q85. What is map function in Python? Ans: map function executes the function given as the first argument on all the elements of the iterable given as the second argument. If the function given takes in more than 1 arguments, then many iterables are given. #Follow the link to know more similar functions. Q86. Is python numpy better than lists? Ans: We use python numpy array instead of a list because of the below three reasons: Less Memory Fast Convenient For more information on these parameters, you can refer to this section – Numpy Vs List. Q87. How to get indices of N maximum values in a NumPy array? Ans: We can get the indices of N maximum values in a NumPy array using the below code: 1 2 3 import numpy as np arr = np.array([1, 3, 2, 4, 5]) print(arr.argsort()[-3:][::-1]) Output [ 4 3 1 ] Q88. How do you calculate percentiles with Python/ NumPy? Ans: We can calculate percentiles with the following code 1 2 3 4 import numpy as np a = np.array([1,2,3,4,5]) p = np.percentile(a, 50) #Returns 50th percentile, e.g. median print(p) Output 3 Q89. What is the difference between NumPy and SciPy? Ans: In an ideal world, NumPy would contain nothing but the array data type and the most basic operations: indexing, sorting, reshaping, basic elementwise functions, et cetera. All numerical code would reside in SciPy. However, one of NumPy’s important goals is compatibility, so NumPy tries to retain all features supported by either of its predecessors. Thus NumPy contains some linear algebra functions, even though these more properly belong in SciPy. In any case, SciPy contains more fully-featured versions of the linear algebra modules, as well as many other numerical algorithms. If you are doing scientific computing with python, you should probably install both NumPy and SciPy. Most new features belong in SciPy rather than NumPy. Q90. How do you make 3D plots/visualizations using NumPy/SciPy? Ans: Like 2D plotting, 3D graphics is beyond the scope of NumPy and SciPy, but just as in the 2D case, packages exist that integrate with NumPy. Matplotlib provides basic 3D plotting in the mplot3d subpackage, whereas Mayavi provides a wide range of high-quality 3D visualization features, utilizing the powerful VTK engine. Multiple Choice Questions (MCQ) Q91. Which of the following statements create a dictionary? (Multiple Correct Answers Possible) a) d = {} b) d = {“john”:40, “peter”:45} c) d = {40:”john”, 45:”peter”} d) d = (40:”john”, 45:”50”) Answer: b, c & d. Course Curriculum Python Certification Training for Data Science Weekday / Weekend Batches Dictionaries are created by specifying keys and values. Q92. Which one of these is floor division? a) / b) // c) % d) None of the mentioned Answer: b) // When both of the operands are integer then python chops out the fraction part and gives you the round off value, to get the accurate answer use floor division. For ex, 5/2 = 2.5 but both of the operands are integer so answer of this expression in python is 2. To get the 2.5 as the answer, use floor division using //. So, 5//2 = 2.5 Q93. What is the maximum possible length of an identifier? a) 31 characters b) 63 characters c) 79 characters d) None of the above Answer: d) None of the above Identifiers can be of any length. Q94. Why are local variable names beginning with an underscore discouraged? a) they are used to indicate a private variables of a class b) they confuse the interpreter c) they are used to indicate global variables d) they slow down execution Answer: a) they are used to indicate a private variable of a class As Python has no concept of private variables, leading underscores are used to indicate variables that must not be accessed from outside the class. Q95. Which of the following is an invalid statement? a) abc = 1,000,000 b) a b c = 1000 2000 3000 c) a,b,c = 1000, 2000, 3000 d) a_b_c = 1,000,000 Answer: b) a b c = 1000 2000 3000 Spaces are not allowed in variable names. Q96. What is the output of the following? 1 2 3 4 5 6 7 try: if '1' != 1: raise "someError" else: print("someError has not occured") except "someError": print ("someError has occured") a) someError has occured b) someError has not occured c) invalid code d) none of the above Answer: c) invalid code A new exception class must inherit from a BaseException. There is no such inheritance here. Q97. Suppose list1 is [2, 33, 222, 14, 25], What is list1[-1] ? a) Error b) None c) 25 d) 2 Answer: c) 25 The index -1 corresponds to the last index in the list. Q98. To open a file c:scores.txt for writing, we use a) outfile = open(“c:scores.txt”, “r”) b) outfile = open(“c:scores.txt”, “w”) c) outfile = open(file = “c:scores.txt”, “r”) d) outfile = open(file = “c:scores.txt”, “o”) Answer: b) The location contains double slashes ( ) and w is used to indicate that file is being written to. Q99. What is the output of the following? 1 2 3 4 5 6 7 8 f = None for i in range (5): with open("data.txt", "w") as f: if i > 2: break print f.closed a) True b) False c) None d) Error Answer: a) True The WITH statement when used with open file guarantees that the file object is closed when the with block exits. Q100. When will the else part of try-except-else be executed? a) always b) when an exception occurs c) when no exception occurs d) when an exception occurs into except block Answer: c) when no exception occurs The else part is executed when no exception occurs. I hope this set of Python Interview Questions will help you in preparing for your interviews. All the best! Got a question for us? Please mention it in the comments section and we will get back to you at the earliest. If you wish to learn Python and gain expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role, check out our interactive, live-online Python Certification Training. You will use libraries like Pandas, Numpy, Matplotlib, Scipy, Scikit, Pyspark and master the concepts like Python machine learning, scripts, sequence, web scraping and big data analytics leveraging Apache Spark. The training comes with 24*7 support to guide you throughout your learning period. Recommended videos for you diversity-of-python-programming.jpg Diversity Of Python Programming Python-Machine-Learning-Tutorial-Machine-Learning-Algorithms-Python-Training-Edureka.jpeg Machine Learning With Python – Python Machine Learning Tutorial Python-Tutorial-Python-Tutorial-for-Beginners-Python-Training-Edureka.jpeg Python Tutorial – All You Need To Know In Python Programming Python-Lists-Python-Tuples-Python-Sets-Dictionary-Python-Strings-Python-Training-Edureka.jpeg Python List, Tuple, String, Set And Dictonary – Python Sequences sentiment-analysis-in-retail-domain.jpg Sentiment Analysis In Retail Domain know-the-science-behind-product-recommendation-with-r-programming.jpg Know The Science Behind Product Recommendation With R Programming data-science-make-smarter-business-decisions.jpg Data Science : Make Smarter Business Decisions the-whys-and-hows-of-predictive-modeling-ii.jpg The Whys and Hows of Predictive Modeling-II Python-Loops-Tutorial-Python-For-Loop-While-Loop-Python-Python-Training-Edureka.jpeg Python Loops – While, For and Nested Loops in Python Programming the-whys-and-hows-of-predictive-modelling-i.jpg The Whys and Hows of Predictive Modelling-I Python-Programming-Learn-Python-Python-Tutorial-Python-Training-Edureka.jpeg Python Programming – Learn Python Programming From Scratch mastering-python-an-excellent-tool-for-web-scraping-and-data-analysis.jpg Mastering Python : An Excellent tool for Web Scraping and Data Analysis application-of-clustering-in-data-science-using-real-time-examples.jpg Application of Clustering in Data Science Using Real-Time Examples android-development-using-android-5-0-lollipop.jpg Android Development : Using Android 5.0 Lollipop introduction-to-business-analytics-with-r.jpg Introduction to Business Analytics with R 3-scenarios-where-predictive-analytics-is-a-must.jpg 3 Scenarios Where Predictive Analytics is a Must python-for-big-data-analytics.jpg Python for Big Data Analytics business-analytics-with-r.jpg Business Analytics with R linear-regression-with-r.jpg Linear Regression With R business-analytics-decision-tree-in-r.jpg Business Analytics Decision Tree in R Recommended blogs for you Data-Science-Career-Opportunities-300x165.jpg Data Science Career Opportunities: Your Guide To Unlocking Top Data Scientist Jobs blog_VS-300x177.jpg Data Analyst vs Data Engineer vs Data Scientist: Skills, Responsibilities, Salary Reverse-A-Number-In-Python-1-300x175.jpg How to reverse a number in Python? Bayesian-Network-300x175.jpg How To Implement Bayesian Networks In Python? – Bayesian Networks Explained With Examples Python-Decorator-Tutorial-300x175.jpg Python Decorator Tutorial : How To Use Decorators In Python no-image-1.png K-means Clustering Algorithm: Know How It Works Mathematics-And-Statistics-for-Machine-Learning-300x175.png Statistics for Machine Learning: A Beginner’s Guide Logistic-Regression-In-R-300x175.jpg Comprehensive Guide To Logistic Regression In R Scrapy-Tutorial-300x175.png Scrapy Tutorial: How To Make A Web-Crawler Using Scrapy? Python-XML-Parsing-Tutorial-300x175.jpg How to Parse and Modify XML in Python? naive-bayes-tutorial-300x175.png Naive Bayes Classifier: Learning Naive Bayes with Python Python-Developer-Salary-300x175.png What is the Average Python Developer Salary? Decision-Tree-Algorithm-300x175.jpg A Complete Guide On Decision Tree Algorithm Range-Function-in-Python-300x150.png Understanding Range Function and Sequences in Python Google-Data-Science-Interview-Questions-300x165.jpg Google Data Science Interview Questions : All you need to know to crack It Eval-in-Python-300x175.jpg All You Need to Know About Eval in Python Why-Python-300x175.jpg Why Python Programming Language Is a Must Have Skill? Range-in-python-300x175.png Learn What is Range in Python With Examples Data-Scientist-300x175.jpg Who is a Data Scientist? Blog-Image_How-to-become-a-Machine-Learning-Engineer-1-300x175.png How To Become A Machine Learning Engineer? – Learning Path Comments 7 Comments nareshit says: Jun 18, 2020 at 8:28 am GMT Thanks for your valuable information .We are also providing Python online training in our institute NareshIT. We are having the best and well trained experienced faculty to train you the Python. By joining in this course you will get complete knowledge about Python. we are giving 100% guidance in placement for our students. https://nareshit.com/python-online-training/ Reply Jason Tan says: Mar 29, 2019 at 5:36 am GMT Should be worth noting: in python 3 Q42 actually behaves opposite as mentioned. The ‘/’ operator performs true division by default, so 5/2 = 2.5, and 5//2 = 2. The ‘//’ is used to truncate the decimal and round down the solution. Reply P Adhav says: Mar 29, 2019 at 5:37 am GMT answer of second question reg access modifiers feature is very short/shallow. Reply bilzz says: Mar 29, 2019 at 5:38 am GMT The dir() method tries to return a list of valid attributes of the object. your answer is wrong. Reply Russell B says: Nov 5, 2018 at 12:41 pm GMT This post is a good start but needs some serious editing! To copy an array, don’t use a list comprehension… Use list[:] Also your floor operator details are incorrect. Reply arcenstone says: Jan 30, 2018 at 1:08 pm GMT Q41 is simply wrong, “{}” is correct literal for dict Reply Pramod Raveendran says: Mar 29, 2019 at 5:38 am GMT option d is wrong. Reply Join the discussion Trending Courses in Data Science test Python Certification Training for Data Scienc ... 75k Enrolled Learners Weekend/Weekday Live Class Reviews 5 (29900) test Python Programming Certification Course 18k Enrolled Learners Weekend/Weekday Live Class Reviews 5 (7000) test Machine Learning Certification Training using ... 10k Enrolled Learners Weekend Live Class Reviews 5 (3700) test Data Science Certification Course using R 37k Enrolled Learners Weekend Live Class Reviews 5 (14750) test Data Analytics with R Certification Training 24k Enrolled Learners Weekend Live Class Reviews 5 (9400) test SAS Training and Certification 5k Enrolled Learners Weekend Live Class Reviews 5 (1800) test Statistics Essentials for Analytics 6k Enrolled Learners Weekend/Weekday Self Paced Reviews 5 (2200) test Analytics for Retail Banks 2k Enrolled Learners Weekend/Weekday Self Paced Reviews 5 (450) test Advanced Predictive Modelling in R Certificat ... 4k Enrolled Learners Weekend Self Paced Reviews 4 (1500) test Decision Tree Modeling Using R Certification ... 2k Enrolled Learners Weekend/Weekday Self Paced Reviews 5 (650) Browse Categories Artificial IntelligenceBI and VisualizationBig DataBlockchainCloud ComputingCyber SecurityData Warehousing and ETLDatabasesDevOpsDigital MarketingEnterpriseFront End Web DevelopmentMobile DevelopmentOperating SystemsProgramming & FrameworksProject Management and MethodologiesRobotic Process AutomationSoftware TestingSystems & Architecture webinar FREE WEBINAR Statistics and Probability in 90 Minutes TRENDING CERTIFICATION COURSES DevOps Certification Training AWS Architect Certification Training Big Data Hadoop Certification Training Tableau Training & Certification Python Certification Training for Data Science Selenium Certification Training PMP® Certification Exam Training Robotic Process Automation Training using UiPath Apache Spark and Scala Certification Training Microsoft Power BI Training Online Java Course and Training Python Certification Course TRENDING MASTERS COURSES Data Scientist Masters Program DevOps Engineer Masters Program Cloud Architect Masters Program Big Data Architect Masters Program Machine Learning Engineer Masters Program Full Stack Web Developer Masters Program Business Intelligence Masters Program Data Analyst Masters Program Test Automation Engineer Masters Program Post-Graduate Program in Artificial Intelligence & Machine Learning Post-Graduate Program in Big Data Engineering COMPANY About us News & Media Reviews Contact us Blog Community Sitemap Blog Sitemap Community Sitemap Webinars WORK WITH US Careers Become an Instructor Become an Affiliate Become a Partner Hire from Edureka DOWNLOAD APP apple_store google_playstore CATEGORIES Cloud ComputingDevOpsBig DataData ScienceBI and VisualizationProgramming & FrameworksSoftware TestingProject Management and MethodologiesRobotic Process AutomationFrontend DevelopmentData Warehousing and ETLArtificial IntelligenceBlockchainDatabasesCyber SecurityMobile DevelopmentOperating SystemsArchitecture & Design PatternsDigital Marketing TRENDING BLOG ARTICLES Selenium tutorialSelenium interview questionsJava tutorialWhat is HTMLJava interview questionsPHP tutorialJavaScript interview questionsSpring tutorialPHP interview questionsInheritance in JavaPolymorphism in JavaSpring interview questionsPointers in CLinux commandsAndroid tutorialJavaScript tutorialjQuery tutorialSQL interview questionsMySQL tutorialMachine learning tutorialPython tutorialWhat is machine learningEthical hacking tutorialSQL injectionAWS certification career opportunitiesAWS tutorialWhat Is cloud computingWhat is blockchainHadoop tutorialWhat is artificial intelligenceNode TutorialCollections in JavaException handling in javaPython Programming LanguagePython interview questionsMultithreading in JavaReactJS TutorialData Science vs Big Data vs Data AnalyticsSoftware Testing Interview QuestionsR TutorialJava ProgramsJavaScript Reserved Words and KeywordsImplement thread.yield() in Java: ExamplesImplement Optical Character Recognition in PythonAll you Need to Know About Implements In Java © 2020 Brain4ce Education Solutions Pvt. Ltd. All rights Reserved. Terms & Conditions Legal & Privacy "PMP®","PMI®", "PMI-ACP®" and "PMBOK®" are registered marks of the Project Management Institute, Inc. MongoDB®, Mongo and the leaf logo are the registered trademarks of MongoDB, Inc.