IT sectors allot candidates based on knowledge in the field of computer science. Python interviews are quite terrifying. If you are interested in working in the IT technical sector, you have to appear for an interview. The experts always ask high-level questions on Python. So it is best to stay prepared from before.
Here you get 25 competitive questions on Python. It might help you to survive in the technical round. The questions are divided into many parts, the basic intermediate, the advanced level questions, Python OOPS interview questions, Python interview questions for professionals, Python FAQs, and Python programs.
Keywords in Python are used to define the proper syntax and structure of the language. These keywords are considered as the variable name or the function name, or an identifier. Python 3.7 consists of 33 keywords. The keywords change in different versions of Python.
Here you get a list of Python keywords:
Keywords in Python
| False | class | finally | is | return |
| None | continue | for | lambda | try |
| True | def | from | nonlocal | while |
| and | del | global | not | with |
| as | Elif | if | or | yield |
| assert | else | import | pass | |
| break | except |
Python is the most famous computer programming language that is used in several IT sectors. The AIML professionals also use it and the data scientists. It is popular because of the following points:
1. Python is easy for debugging. It is also used to interpret in several programs.
2. Python is readable and has a clear syntax process.
3. Different languages can be used along with Python.
4. python is computer software that is free and open source.
5. Python can also integrate with several other computer languages, such as Java, C++, and many more.
6. Python is one of the most popular object-oriented computer languages that support several concepts of classes.
Literals in Python consist of the data that is given in a constant or variable. Python has various types of literal that are given below:
1. Boolean Literals-They is available in two values-True, and False is only represented with 1 and 0.
2. String Literals- They are a sequence of characters that is enclosed in the form of codes. There can be strings in single, double, or triple quotes.
3. Special Literals- The fields that are not implemented in this program are sued for various classifications. It is denoted by the value ‘ none. ‘
4. Numeric Literals- These are available in three types- float, complex, and integer.
Computer languages can be installed in your computer system. To get Python, you are required to visit Anaconda.org and press the button Download Anaconda. Hence, you can download the new version of Python from this website.
Let us take two different tuples, say:
1. tup1 = (1,”a”,True)
2. tup2 = (4,5,6)
Concatenation is to add the elements of one tuple with the end elements of the next tuple.
Now we connect tuple 2 with 1:
Code
tup 1= (1, “ a “ , True)
tup 2= ( 4, 5, 6 )
tup 1+ tup 2
Output
(1, ‘ a ‘, True, 4, 5, 6)
You need to press the + operator to initiate the operation.
Python is a universal computer programming language. The programming keys of Python are used to play music on Spotify, watch videos on YouTube, check posts on Instagram, and browse Google. Python is the most popular source for web development. It is used in several applications, services, and platforms.
Python refers to different functions like reusable codes to enable related and single events. It also consists of organized blocks that create proper modularity for various applications. You can also operate the user-defined functions.
Pandas is one of the most popular open-source Python libraries with an excellent set of data structures for several database operations. It has amazing features that serve academics and solves various business problems. Pandas can operate different types of files for initiating various functions.
Series is one of the most vital dimensional data structures in pandas. It consists of all types of data. It shows an excel column. It also operates single-dimensional data and supports various multiple operations.
Creating a pandas series from data:
Code
import pandas as PD
data=[“1″,2,”three”,4.0]
series=pd.Series(data)
print(series)
print(type(series))
Output
0 1
1 2
2 three
3 4
dtype: object
<class ‘ pandas. core. series. Series ’>
The mutable data structure in pandas is called data frames. The heterogeneous data form is available in pandas. It is arranged in rows and columns. Hence, if you want to read files then,
1. Import pandas as PD
2. df=p.read_csv(“mydata.csv”)
Here, df is the data frame, read_csv is () makes the comma-delimited files readable.
Panda offers an inner join, a left join, an outer join, and a right join.
You can get the first five entries of the data frames by selecting the (5) function. If you want to return to the top rows, you must select df.head (). The df.head (n) is used to move to the top n rows.
Merging depends on different fields and types of databases that will be merged. If the data structure consists of similar data along the 0 axis, they will be merged along axis 1.
To enable a dataframe () function from a dictionary, you must check the code given below:
import pandas as pd
bikes=[“bajaj”,”tvs”,”herohonda”,”kawasaki”,”bmw”]
cars=[“lamborghini”,”masserati”,”ferrari”,”hyundai”,”ford”]
d={“cars”:cars,”bikes”:bikes}
df=pd.DataFrame(d)
df
Output
| cars | bikes | |
| 0 | Lamborghini | bajaj |
| 1 | Maserati | TVs |
| 2 | Ferrari | hero honda |
| 3 | Hyundai | Kawasaki |
| 4 | ford | BMW |
The use of the tail (5) function can help you to access the last five data frame entries in pandas. You can turn to the top 5 rows by selecting default df.tail (). If you select df.tail (n), you will reach the last n rows.
Let the index be ( x ). Now we can apply loc.
Df.loc [10], where the value of the index is 10.
Code
import pandas as pd
bikes=[“bajaj”,”tvs”,”herohonda”,”kawasaki”,”bmw”]
cars=[“lamborghini”,”masserati”,”ferrari”,”hyundai”,”ford”]
d={“cars”:cars,”bikes”:bikes}
df=pd.DataFrame(d)
a=[10,20,30,40,50]
df.index=a
df.loc[10]
Output
cars lamborghini
bikes bajaj
Name: 10, dtype: object
The difference between tuples and lists are:
1. Lists are mutable
2. Tuples are immutable
Comments in Python indicate a single text that is intended for information. It becomes a relevant aspect when a group of people works on a set of codes. It can be used to debug, leave feedback or analyze codes. There are two different types of comments found in Python. Here comes the list:
1. Single-line comment
2. Multiple-line comment
Codes required for adding more comments:
#Note –single line comment
“””Note
Note
Note”””—–multiline comment
The dictionary in Python consists of a large collection of items that have no particular order. Python dictionaries are implemented with the use of values and keys. The information is written in curly brackets. Optimization of dictionaries is enabled to get values for different known keys.
Example
d={“a”:1,”b”:2}
21. import NumPy as np
22. n1=np.array([10,20,30,40,50,60])
23. print(np.mean(n1))
24. print(np.mean(n1))
25. print(np.std(n1))
One of the easiest methods to get a list of keys is to use: dict.keys()
This method returns the vital keys in the dictionary. dict = {1:a, 2:b, 3:c} dict.keys()
o/p: [1, 2, 3].
Python programs consist of two cases, the uppercase, and the lowercase. The uppercases in a string variable can be converted to lowercases by selecting: string.lower()
For example:
ex: string = ‘GREATLEARNING’ print(string.lower())
o/p: great learning
To capitalize the first letter of a string, you can use the function capitalize(). If the character is already in the capitalized form, it automatically returns to the original string.
For example:
Syntax: string_name.capitalize() ex: n = “greatlearning” print(n.capitalize())
o/p: Great learning
There are several methods to eliminate duplicate elements from a string list. But the most common method is to use the set () function to convert the elements into sets. To convert the setback to the list, you can select the list () function. You can also use these functions:
ex:
list0 = [2, 6, 4, 7, 4, 6, 7, 2]
list1 = list(set(list0)) print (“The list without duplicates : ” + str(list1)) o/p: The list without duplicates : [2, 4, 6, 7]
A classifier is used to select the class of different data points. It is a type of hypothesis that is used to label a class with several data points. It makes you understand the correct usage of the class variable and the input variable. It is a type of data structure that is mostly used in Machine Learning.
If you are going for a job interview in a high-level IT institute, it is vital to have adequate knowledge of Python. So it would be best if you went through these competitive questions about Python and its potential. Therefore, you can also go for online learning. Some so many professionals teach online. So if you want to crack your interview, then make yourself stronger.
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