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Listed below are key features of the python programming language that make it popular:
There are multiple in-built libraries in Python which can help you to apply Python in an easy, hassle-free manner.
Numpy: It is the most essential library that is available in Python to carry out scientific computing and is widely used for various applications in machine learning and deep learning. The full form of Numpy is Numeric Python. The machine learning algorithms would be highly complicated to compute and need a lot of multidimensional array operations. There is a huge support that is offered by Numpy for the multi-dimensional array objects and there is a myriad of tools available to work with this library.
Pandas: It is an open-source package that is available in Python which offers you the best performance and comes with simple data structures and data analysis tools to use for labelled data in Python. Pandas full form is a python data analysis library. It is the best tool that is available for data wrangling and munging.
Scipy: It is the core package in Python. Scipy is built on the basis of the Numpy array object. It is also one of the major stacks that would contain a myriad of tools such as Pandas, Sympy, Matplotlib and so on. It has many efficient modules that allow you to carry out mathematical operations efficiently like algebra, integrations and statistics.
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BeautifulSoup is a parsing library that allows you to do web scraping from both XML and HTML documents. It detects encoding and would easily handle HTML documents that are embedded with special characters.
The bottle is a lightweight web framework in Python. It is considered a single module with no dependencies.
Flask is a web framework that is developed in Python. It is a third-party library that is used for developing web applications.
The request is the de facto standard library that would let you make HTTP requests in the apps developed in Python. It allows you to interact with services and consume data that is in the web application with ease.
PyQt4 is a library that contains many modules such as Qtcore, QTGui, QTOpenGL, QTSQL, and so on.
PyQt5 is used for building applications and is a cross-platform GUI toolkit using which you can develop desktop applications due to the tools that are offered by this library.
Networkx is a library in Python that allows you to study graphs and networks. It helps you learn how to optimize graphs in python. It helps you to create, manipulate and study the structure, dynamics and various functions related to complicated networks.
It works effectively with human language when compared with computer language when used with NLP (Natural language processing). There are many text processing libraries using which you can do tokenization, parsing, tagging, stemming and semantic reasoning.
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A few of the basics of python include:
Loops: Every statement is executed in sequential order. Initially, the first statement is executed followed by the second one and so on. There are times when you have to execute a series of codes simultaneously. There are different control structures that are offered by Python to execute complex execution paths. The loop requirements can be handled by different loop types such as while loop, for loop and nested loop. The while loop will repeat the same statement or a group of statements only when the condition is true. The condition is checked before the loop is executed. In the for loop, the series of statements are executed continuously. The nested loop will have single or multiple loops inside each other.
Statements: The series of instructions that are written in the source code for executing the program is known as a statement. Various types of statements are used in Python such as conditional statements, looping statements, assignment statements and so on. This will allow the user to get the output they want with ease. The best thing about using statements in Python is that the statements are easy to extend to one or multiple lines with the help of semicolons, braces, and square brackets. If the programmer would like to do calculations and the statements are tough to fit in a single line, then characters are used.
Comments: Python developers will use a comment system. However, without making use of comments, it becomes challenging for other developers to understand the code that is written by their co-developer. The useful information will be presented in the comment section which makes it simple for other developers to understand the source code. The comment can also help in improving the present code when there is no one to answer your questions. There are two types of comments available in Python. One is the single-line comment and the other is the multi-line string which is used as a comment.
Functions: A function is a code that can be run by calling it. You can either pass parameters or data to run the code and the function would give you the response data as an output. The functions are a kind of statements that can be used to carry out computational, logical and evaluative tasks. This allows you to carry out repetitive tasks instead of writing the same or almost similar code for generating different outputs. The same code is reused. This makes the programs non-repetitive.
One needs to understand the basics of Python to get the fundamentals in place and further explore the advanced applications. You can master such basics of Python by availing the Python assignment help from our qualified and experienced tutors
There are many advanced concepts in Python mastering and you can create any app or play with this programming language to resolve the issues in the existing app. Students who hold extensive knowledge on Python are hired by companies by paying lucrative pay.
Exception handling: Exception is similar to the error that you may encounter while executing the program and cause interruption to the execution. This can occur due to many reasons. For instance, while writing a program for doing division, you can observe 0 in the denominator. This is known as the zero division error. There are other exceptions that you may encounter while importing the libraries that are not existing in your library list or when gaining access to any element that is not in the list index. Many exceptions are built in Python.
Collections: Collections are known as containers in this programming language that lets you store data. A few of the containers include set, tuple, list and so on. There are various libraries available in this language to offer you data structures. The collection will help to boost the functionality of a container. Five different collections include counter, namedtuple, ordereddict, defaultdict, and deque.
Itertools: Itertools will offer many functions and these functions would work with the help of iterators.
Lambda: It is called an anonymous function. It has no body and has no def keyword that is used for definition. Lamba will have multiple arguments with just a single expression. It becomes easier to evaluate the functions and return the output.
Decorators: It is the feature present in Python that adds up value to the code that is exciting without making major modifications. There are two different types of decorators available. One is functions and the other is class decorators. Before every function name, @ would be added. You can use the decorator after defining the function in just 2 lines.
Generators: It is a function that would in return give the object which you can iterate multiple times. It has a yield, which is a keyword that would give a value from the function without making any changes to its current state. Generators are memory efficient and do not take much space in the memory.
Python is most widely used to solve Machine Learning, Deep Learning and Data Science problems. The easy-to-use and wide applications of Python make it the most popular tool for machine learning and AI applications.
A few of the machine learning algorithms that are used in Python include
Linear regression: It is a kind of supervised machine learning algorithm that is used in python. It helps you to anticipate the outcome and learn the features. It runs either with single or multiple variables. Based on the number of variables that are used, it is referred to as single linear regression or multiple linear regression. This is the widely used algorithm in Python. It will create a line by adding weights and making the right predictions. This linear regression helps you to predict accurate values for the item cost.
Logistic regression: It is a supervised ML algorithm that predicts discrete values like 0 or 1, yes or no or true or false. This works with the help of independent variables. The logistic function can be made used to estimate the output either as 0 or 1.
Support vector machines (SVM): It is a supervised learning algorithm that is used for classification. It will have a line that will segregate the categories of every dataset. The line can be optimized by accurately taking the calculation of a vector. It ensures that the points that are closer to each are actually farther from each other.
Decision tree: It is again a supervised learning algorithm that can be used for classification and regression purposes. It allows you to compare the feature with the help of a conditional statement.
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Various applications of Python include:
Statistics and Data Science: Data is a valuable asset for all companies. By extracting accurate information, you can learn the risks that the company may pose and use the data to also increase profits. You can study the data that is with you and extract the required data. There are various libraries that are available in Python such as Pandas, Numpy and so on to extract the data.
Python has a built-in statistics library. This library can be used when the datasets are not too huge or if you cannot import other libraries.
Deep Learning: Deep learning is a widely researched topic in data science. The subgroup of deep learning is artificial intelligence. The hierarchical artificial neural network would be used to make decisions similar to humans. The artificial neurons that are present would work like to that of neurons in the human brain. It can handle a huge amount of unstructured data and extract the right amount of data. Deep learning in Python allows you to create chatbots, create self-driving cars, colour images, medical care, and so on.
GUI applications: Python programming is used to develop GUI applications. There is a library called Tkinter that is provided to develop rich and appealing user interfaces. Various toolkits such as PYQT, Kivy and so on would be used to create applications that are compatible to work on different platforms. Applications that you can create using this programming language include calculators, to-do apps and many complex apps.
Web Scraping: Python is a big saviour for many companies since it can extract a huge amount of data from various websites with ease and can use this data for real-world processes like job listings, research and development, comparison of prices on the e-commerce site and so on.
App Development: Python language is used for creating various apps. It is reliable, simple to understand and easy to adapt. It can be used for building both web and mobile apps that work cross-platform. Apps such as blockchain applications, command line applications, game app development, system administration application, business application and machine learning application.
Mobile games: Python is used to develop highly interactive games that engage gaming enthusiasts. Various libraries such as Pysoy would be used to develop a 3D game engine and Pygame is another library that helps you develop games. Many interesting and popular games are developed using Python. Some of them include - the Vega strike, Disney’s Toontown village and so on.
Data visualization: The data can also be visualized using various libraries Matplotlib, Seaborn and so on. These are used to plot the data on graphs. This is what this programming language would offer for data science.
Machine Learning & AI: Machine learning and artificial intelligence offer promising careers for students. Computers would learn by considering past experience by referring to past data and creating algorithms by
themselves. Various libraries such as Pandas, NumPy, Scikit-learn and so on. By learning the algorithm and using the library, companies can find the solution to a business challenge.
Embedded Applications: Python is based completely on C. You can use this to come up with the embedded C for developing embedded applications. This allows you to use high-level applications on small devices, which can easily process this language.
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We have years of experience in delivering quality assignments to students globally. We have listed out the problems that are often experienced by them while writing the assignments. These include:
Lack of coding skills: It is a Herculean task for students to learn the programming code of Python. The students without knowledge of the characters, syntaxes and symbols that are in Python cannot write the assignments. Therefore, look for help from subject matter experts.
Inattentive approach: This is the main problem that hampers programming skills. When they are not focused, they could not include the key elements that are useful to create an assignment. It is important for students to pay attention to minuscule details even when there is a change in the sign or syntax or character, it throws an error.
Bemusing Python code: The programmers who have just started to code could not understand the difference between two pieces of code, which look similar, but have a slight difference. Programmers who do not have enough knowledge face confusion in implementing this code.
|Data Structures for Statistics||Statistical Modeling|
|Distribution and Hypothesis Tests||Test of Means of Numerical Data|
|Tests on categorical Data||Linear Regression Models|
|Multivariate Data Analysis||Bayesian Statistics|
|Analysis of Survival Times||Decision Structures|
|Loop Structures and Booleans||Object oriented design|
|Algorithm design and recursion||Computing with strings|
|Threading||Cross-Platform Unix Programming|
|Python Integration Primer||EPM Package Manager|
|DNS Management using Python||String Pattern Matching|
|Queues||Errors And Exception Handling|
|Cobra, Groovy, Coffee script, ECMAScript, Swift||Parallel system tools|
|Graphical User Interfaces||Internet Scripting|
|Databases and Persistence||
Network Scripting, Client Side scripting, Server side scripting
These are a few best examples of Python include:
It is easy to execute a Python syntax just by writing a single command line
>>> print("Hello, World!")
The output will be Hello, World!
Indentation is the space that would be at the start of the code lines. Indentation is essential for improving readability and this is very much important in Python.
print("Five is greater than two!")
Variables will get created only when the values are assigned.
x = 5 y = “Hello, World!” print(x) print(y)
Python holds the commenting ability in the document
#This is a comment.
There is no command available in this programming language to declare a variable. Variables get created when a value is assigned. x = 5 y = "James" print(x) print(y) Output: 5 James
Casing allows you to know the data type of variables with ease. x = str(2) y = int(5) z = float(3) print(x) print(y) print(z) Output 2 5 3.0
x = 5 y = "John" print(type(x)) print(type(y)) Output Single or double quotes You can declare string either by using single or double quote x = ‘James’ x = “James” Type conversion It is easy to convert the values from one to different types with the help of int (), float () and complex () methods. Example: #convert from int to float: x = float(1) #convert from float to int: y = int(2.8) #convert from int to complex: z = complex(x) print(x) print(y) print(z) print(type(x)) print(type(y)) print(type(z)) Output: 1.0 2 (1+0j)