Find more components on Python Computer Vision

Python programming language employs NumPy arrays in order to achieve image processing and computer vision tasks in the applications of artificial intelligence. The gamut of computer vision tasks can be executed efficiently with Python's scikit image processing libraries that work in tandem with NumPy arrays to produce high-quality filtered images. In fact, a Python imaging library can be used to accomplish complex tasks such as feature extraction, face recognition, and image manipulation. In addition, the scikit learn library in Python provides deep learning modules to employ in business operations (for example, for consumer satisfaction analysis). Check out these libraries for Python computer vision to create a state-of-the-art code to deploy in data science fields. The face_recognition library touts to be the simplest API in the world for Python and command-line. If you are aiming to achieve image-to-image translation, check out the pytorch-CycleGAN-and-pix2pix library. One of the highest utility libraries in the list is perhaps the EasyOCR - a code pack for optical character recognition in over 80 languages. If machine learning is your objective, the NumPy_ML library carries pre-coded modules to insert into your code.

Python

Computer Vision

libraries

Find more components on Python Personal Finance

All new-age finance professionals committed to data analysis and data science are dependent on Python at some level. It is with Python that they can perform analysis on various financial data points. But Python turns out to be a formidable tool even while developing personal finance applications. For instance, you can scrape the web for personal finance data, download financial transactions, develop a budget tracking app, and so on, all with Python. With that in mind, let’s have a quick overview of some of the best open-source Python packages and libraries for personal finance. Ofxstatement is a tool developed with the intention to convert proprietary bank statements to OFX format which is the accepted format for major personal accounting systems. One of the best open-source Python packages, finance-dl is used for scraping personal finance data from various financial institutions. It performs best when used with beancount-import which is a tool for semi-automatic data importing. We also have MyMoney, which is essentially a web application for personal finance built with Django. It can manage your bank account, your transactions, analyze them and schedule them if they’re recurrent. MyMoney a simple tool with the goal to analyze your expenses.

Personal Finance

Cryptography is the cornerstone of information security. Over the years, encryption standards have improved and gotten tougher to crack, and older paradigms have gradually faded into oblivion. And this happened in parallel to the digital revolution that has made technological, financial, and media sectors overly dependent on encryption to keep their and their users' data secure from prying eyes. The cryptography support provided by .NET is essentially complete by default, yet we have various other open-source encryption libraries for developing advanced applications. With that in mind, here are some of the C# encryption libraries with a wide spectrum of use cases. NLog is a free and open-source logging platform for .NET. It’s flexible, which makes it easy to write to database, file, console, among other targets, and change the configuration on the go. win-acme is a simple yet powerful ACMEv2 client for Windows. You can use it to install and automatically renew certificates on a local IIS server and even build your own plugins. It’s compatible with various popular ACME services like ZeroSSL, Let’s Encrypt, etc. Yet another library, jose-jwt is an ultimate implementation of Javascript Object Signing and Encryption and JSON Web Token. It is minimalistic, JSON parsing agnostic, and has no dependencies. Through this, you can encode content as a string, sign it digitally, and encrypt it.

Encryption

Build elegant charts, interactive dashboards, custom reports and more.Get ratings, code snippets &amp; documentation for each library.

Charts

The automatic review of source code to find potential problems or flaws is known as code analysis. Code analysis is the process of automatically reviewing source code to identify potential issues or defects. It can be applied to make your code more accurate, dependable, and compliant with industry standards and best practices.&nbsp;In C#, code analysis can be done in various ways. One choice is to utilize a static code analysis tool that examines your code without running it. These tools can spot problems, including syntax and semantic mistakes and potential vulnerabilities.&nbsp;
 
Utilizing runtime analysis, which involves running your code and observing its behavior to spot problems, is an additional choice. Techniques like debugging, testing, and exception handling can be used for this.&nbsp;The software development process can benefit from code analysis since it can help you find and fix problems early on, saving you time and effort in the long run. Additionally, it is a practical technique to ensure that your code follows best practices and coding standards, making it simpler to maintain and develop over time.&nbsp;
 
For C#, several code analysis libraries are available. The most well-known ones include Roslyn, Microsoft's open-source code analysis framework; SonarQube, an open-source platform for continuous code inspection; Caliburn.micro, Code-cracker, and so on. It contains a collection of APIs that enable you to create code analysis tools for C# and Visual Basic.&nbsp;These are only a few illustrations of the C# code analysis libraries that are readily available. There are a lot more options available.&nbsp;
 
Check out the below list to find the best C# Code Analysis libraries for your application:&nbsp;

Code Analysis

Developing and deploying apps, managing infrastructure, monitoring, logging activity, and other development and operations procedures can all be automated using C-Sharp DevOps libraries.&nbsp;The programming language C# is frequently used to create various applications, including backend services, desktop, mobile, and web based. On the .NET platform, which offers a wealth of libraries and tools for creating, deploying, and maintaining applications, C# serves as the principal language for developing applications.&nbsp;&nbsp;
 
Building and deploying apps, managing infrastructure, and monitoring and logging are just a few development and operations processes that can be automated in DevOps using C# libraries. By automating and streamlining their operations, these libraries can aid developers, and DevOps engineers in producing higher-quality software more rapidly and effectively.&nbsp;DevOps aims to make it possible for businesses to produce higher-quality, more reliable, and quicker software. A software development process called DevOps strongly emphasizes teamwork, communication, and integration between IT operations teams and software developers. Azure Microsoft offers a suite of DevOps tools and services for creating, delivering, and managing applications. It is a cloud-based platform that interfaces with various tools and services, such as GitHub, Azure, and Visual Studio, to offer a full range of DevOps capabilities.&nbsp;
 
Check out the below list to find the best C# DevOps libraries for your application:&nbsp;

13 best DevOps libraries in 2023

Virtual Agent Sample

ganesh Kit

Paraphraser-sample

Paraphrasing refers to rewriting something in different words and using different expressions. It does not include changing the whole concept or meaning. It is a method in which we use words’ alternatives and different sentence structures. Paraphrasing is a restatement of any content or text. This is done by using a sentence re-phraser (Paraphraser). 

What is a good paraphrase?

 Almost all conditioned text generation models are validated on 2 factors, (1) if the generated text conveys the same meaning as the original context (Adequacy) (2) if the text is fluent / grammatically correct English (Fluency). For instance Neural Machine Translation outputs are tested for Adequacy and Fluency. But a good paraphrase should be adequate and fluent while being as different as possible on the surface lexical form. With respect to this definition, the 3 key metrics that measures the quality of paraphrases are:
<ul>
<li>Adequacy (Is the meaning preserved adequately?)</li>
<li>Fluency (Is the paraphrase fluent English?)</li>
<li>Diversity (Lexical / Phrasal / Syntactical) (How much has the paraphrase changed the original sentence?)</li>
</ul>

The aim of a paraphraser is to create paraphrases that are fluent and have the same meaning. There are many uses or applications of a Paraphraser:
<ul>
<li>Data Augmentation: Paraphrasing helps in augmenting/creating training data for Natural Language Understanding(NLU) models to build robust models for conversational engines by creating equivalent paraphrases for a particular phrase or sentence thereby creating a text corpus as training data.</li>
<li>Summarization: Paraphrasing helps to create summaries of a large text corpus for understanding the crux of the text corpus.</li>
<li>Sentence Rephrasing: Paraphrasing helps in generating sentences with similar context for a particular phrase/sentence. These rephrased sentences can be used to create plagiarism free content for articles, blogs etc. </li>

A typical process flow to create training data by data augmentation using Paraphraser is picturized below:

</ul>Group Name 1TroubleshootingFor Windows users:
While you attempt to run the kit_installer batch file, you might be view a prompt from Microsoft Defender as below:

Python object detection libraries are used for object detection in an image. It is a computer vision library to&nbsp;detect the objects present.&nbsp;
 
The Python object detection libraries can be used to build a machine learning model for detecting objects in the images or videos. One of the best in class, Detectron, is Facebook AI Research’s software system that performs object detection with various state-of-the-art machine learning algorithms like Mask R-CNN. It is powered by the Caffe2 deep learning framework with the goal to provide a high-quality codebase for object detection research.
 
Pillow or PIL is another open-source Python library for image processing. With it, you can read, rescale, and save images in different formats. Part of the OpenMMLab project, MMDetection is a PyTorch-based object detection toolbox. The following is a comprehensive list of the best open-source libraries that you can use for object detection:

Object Detection

Build your own blockchain with functions like Creating Blocks, Generating Block Hashes, Creating the Blockchain Class, Adding Blocks to the Chain Securely, Implementing Proof-of-Work with Python blockchain libraries.
 
Although blockchains are mainly implemented for cryptocurrencies, this system can be used to store and transfer or transact any type of data securely. Fundamentally, with a blockchain, you can assign these key characteristics to the data, viz., make it immutable and un-hackable with no data loss and securely distributable. Python blockchain libraries are useful for creating blockchains, mining new blocks, adding cryptographic encryption, displaying the entire blockchain, and more. The command-line tools available in Python enable developers to code blockchains. With Python, a developer can create a simple blockchain in fewer than 50 lines of code.
 
Scroll over to discover this complete list of the best Python blockchain libraries:
<h2>cryptocompare&nbsp;&nbsp;</h2>
<ul>
 <li>Provides comprehensive cryptocurrency market data and pricing information.&nbsp;&nbsp;</li>
 <li>Offers historical data, real-time updates, and a range of indices.&nbsp;&nbsp;</li>
 <li>Supports various cryptocurrencies and exchanges.&nbsp;&nbsp;</li>
</ul>
<h2>chia-blockchain&nbsp;&nbsp;</h2>
<ul>
 <li>Developed for the Chia blockchain, a sustainable and eco-friendly alternative to Bitcoin.&nbsp;&nbsp;</li>
 <li>Utilizes proof of space and time for consensus, reducing energy consumption.&nbsp;&nbsp;</li>
 <li>Includes farming and plotting tools for Chia network participation.&nbsp;&nbsp;</li>
</ul>
<h3>cryptofeed&nbsp;&nbsp;</h3>
<ul>
 <li>A cryptocurrency data feed handler library.&nbsp;&nbsp;</li>
 <li>Offers support for multiple exchanges and data formats.&nbsp;&nbsp;</li>
 <li>Allows for real-time data streaming and customization.&nbsp;&nbsp;</li>
</ul>
<h2>lbry-sdk&nbsp;&nbsp;</h2>
<ul>
 <li>Facilitates content sharing and publishing on the LBRY network.&nbsp;&nbsp;</li>
 <li>Supports decentralized digital content distribution.&nbsp;&nbsp;</li>
 <li>Offers tools for building apps and services on the LBRY platform.&nbsp;&nbsp;</li>
</ul>
<h2>electrum&nbsp;&nbsp;</h2>
<ul>
 <li>A popular Bitcoin wallet with a focus on speed and simplicity.&nbsp;&nbsp;</li>
 <li>Offers features like multi-signature support and hardware wallet integration.&nbsp;&nbsp;</li>
 <li>Provides a lightweight SPV (Simplified Payment Verification) client for Bitcoin.&nbsp;&nbsp;</li>
</ul>
<h2>bigchaindb&nbsp;&nbsp;</h2>
<ul>
 <li>A blockchain database designed for decentralized applications (dApps).&nbsp;&nbsp;</li>
 <li>Supports high throughput and low latency for data transactions.&nbsp;&nbsp;</li>
 <li>Enables the creation of custom assets and digital assets management.&nbsp;&nbsp;</li>
</ul>
<h2>web3.py&nbsp;&nbsp;</h2>
<ul>
 <li>A Python library for interacting with Ethereum blockchain nodes.&nbsp;&nbsp;</li>
 <li>Allows developers to build Ethereum dApps and smart contracts in Python.&nbsp;&nbsp;</li>
 <li>Supports contract deployment, transaction handling, and blockchain data retrieval.&nbsp;&nbsp;</li>
</ul>
<h2>torba&nbsp;&nbsp;</h2>
<ul>
 <li>A Python library for Steem blockchain integration.&nbsp;&nbsp;</li>
 <li>Provides tools for creating Steem-based applications.&nbsp;&nbsp;</li>
 <li>Offers efficient data retrieval and posting to the Steem network.&nbsp;&nbsp;</li>
</ul>
<h2>mythril&nbsp;&nbsp;</h2>
<ul>
 <li>Is a security analysis tool to help with Ethereum smart contracts.&nbsp;&nbsp;</li>
 <li>Detects vulnerabilities and security issues in smart contract code.&nbsp;&nbsp;</li>
 <li>Helps developers ensure the security of their Ethereum-based applications.&nbsp;&nbsp;</li>
</ul>
<h2>raiden&nbsp;&nbsp;</h2>
<ul>
 <li>An off-chain scaling solution for Ethereum.&nbsp;&nbsp;</li>
 <li>Enables fast and low-cost token transfers.&nbsp;&nbsp;</li>
 <li>Facilitates micropayments and scalability for Ethereum dApps.&nbsp;&nbsp;</li>
</ul>
<h2>SimpleCoin&nbsp;&nbsp;</h2>
<ul>
 <li>A basic cryptocurrency implementation in Python.&nbsp;&nbsp;</li>
 <li>Suitable for educational purposes and learning about blockchain concepts.&nbsp;&nbsp;</li>
 <li>Allows users to create a simple blockchain and mine coins.&nbsp;&nbsp;</li>
</ul>
<h2>sawtooth-core&nbsp;&nbsp;</h2>
<ul>
 <li>A blockchain platform to build, deploy, and run distributed ledgers.&nbsp;&nbsp;</li>
 <li>Offers modularity and extensibility for custom consensus algorithms.&nbsp;&nbsp;</li>
 <li>Suitable for enterprise blockchain applications.&nbsp;&nbsp;</li>
</ul>
<h2>smart-contracts</h2>
<ul>
 <li>A library for writing, deploying, and managing smart contracts on various blockchains.&nbsp;&nbsp;</li>
 <li>Provides a consistent interface for working with smart contracts across different platforms.&nbsp;&nbsp;</li>
 <li>Supports Ethereum, EOS, and other blockchain ecosystems.&nbsp;&nbsp;</li>
</ul>
<h2>btcrecover</h2>
<ul>
 <li>A Bitcoin wallet password and seed recovery tool.&nbsp;&nbsp;</li>
 <li>Helps users regain access to lost or forgotten Bitcoin wallet credentials.&nbsp;&nbsp;</li>
 <li>Offers dictionary and brute force attack options for password recovery.&nbsp;&nbsp;</li>
</ul>
<h2>cello</h2>
<ul>
 <li>A blockchain platform will simplify the creation of blockchain networks.&nbsp;&nbsp;</li>
 <li>Provides a web-based interface for blockchain network management.&nbsp;&nbsp;</li>
 <li>Offers tools for deploying and managing blockchain applications.&nbsp;&nbsp;</li>
</ul>
<h2>api-v1-client-python</h2>
<ul>
 <li>A Python client library for interacting with blockchain APIs.&nbsp;&nbsp;</li>
 <li>Simplifies the integration of blockchain data into applications.&nbsp;&nbsp;</li>
 <li>Supports various blockchain platforms and data retrieval methods.&nbsp;&nbsp;</li>
</ul>
<h2>dragonchain</h2>
<ul>
 <li>A hybrid blockchain platform for building scalable and secure applications.&nbsp;&nbsp;</li>
 <li>Supports multiple programming languages for smart contract development.&nbsp;&nbsp;</li>
 <li>Offers features like data privacy and interoperability.&nbsp;&nbsp;</li>
</ul>
<h2>nucypher&nbsp;</h2>
<ul>
 <li>A privacy-preserving data-sharing platform for blockchain applications.&nbsp;&nbsp;</li>
 <li>Provides cryptographic tools for secure data sharing and access control.&nbsp;&nbsp;</li>
 <li>Enables decentralized key management and data encryption.&nbsp;&nbsp;</li>
</ul>
<h2>indy-node&nbsp;</h2>
<ul>
 <li>A node implementation for the Hyperledger Indy blockchain.&nbsp;&nbsp;</li>
 <li>Supports self-sovereign identity and verifiable credentials.&nbsp;&nbsp;</li>
 <li>Enables the creation of decentralized identity solutions.&nbsp;&nbsp;</li>
</ul>
<h2>python_blockchain_app&nbsp;</h2>
<ul>
 <li>A Python-based blockchain application development framework.&nbsp;&nbsp;</li>
 <li>Facilitates the creation of custom blockchain applications.&nbsp;&nbsp;</li>
 <li>Offers tools for smart contract development and deployment.&nbsp;&nbsp;</li>
</ul>
<h2>Plutus</h2>
<ul>
 <li>A development platform for Cardano smart contracts.&nbsp;&nbsp;</li>
 <li>Utilizes the Haskell programming language for contract development.&nbsp;&nbsp;</li>
 <li>Provides a formal verification framework for contract correctness.&nbsp;&nbsp;</li>
</ul>
<h2>crypto-whale-watching-app</h2>
<ul>
 <li>An application for tracking and analyzing cryptocurrency market data.&nbsp;&nbsp;</li>
 <li>Offers real-time data updates and visualization of market trends.&nbsp;&nbsp;</li>
 <li>Useful for monitoring large cryptocurrency transactions (whale activity).&nbsp;&nbsp;</li>
</ul>
<h2>QRL</h2>
<ul>
 <li>A quantum-resistant blockchain platform.&nbsp;&nbsp;</li>
 <li>Focuses on security against quantum computing threats.&nbsp;&nbsp;</li>
 <li>Utilizes the XMSS post-quantum digital signature scheme.&nbsp;&nbsp;</li>
</ul>
<h2>cert-issuer&nbsp;</h2>
<ul>
 <li>A tool for issuing blockchain-based certificates and credentials.&nbsp;&nbsp;</li>
 <li>Integrates with various blockchain platforms.&nbsp;&nbsp;</li>
 <li>Enables the verification of certificates on the blockchain.&nbsp;&nbsp;</li>
</ul>
<h2>hydrachain&nbsp;</h2>
<ul>
 <li>A permissioned blockchain framework based on Ethereum.&nbsp;&nbsp;</li>
 <li>Provides flexibility for custom consensus algorithms and privacy features.&nbsp;&nbsp;</li>
 <li>Suitable for enterprise and consortium blockchain applications.&nbsp;&nbsp;</li>
</ul>
<h2>neo-python&nbsp;</h2>
<ul>
 <li>A Python node and SDK for the NEO blockchain.&nbsp;&nbsp;</li>
 <li>Supports NEO smart contract development and deployment.&nbsp;&nbsp;</li>
 <li>Offers features like asset management and digital identity support.&nbsp;&nbsp;</li>
</ul>
<h3>FAQ&nbsp;&nbsp;</h3>
How does the programming language of Python support blockchain programming?&nbsp;&nbsp;
Python supports blockchain programming through various libraries and frameworks. Creating blockchain applications and smart contracts is simple and versatile. Libraries such as Web3.py help interact with Ethereum and other blockchains. Tools like PyCryptodome aid in wallet management and transaction signing with cryptography.&nbsp;&nbsp;
&nbsp;&nbsp;
How does blockchain technology work for cryptocurrency trading?&nbsp;&nbsp;
Blockchain improves cryptocurrency trading by securely recording transactions, making it safer and transparent. The blockchain verifies and adds cryptocurrency transactions, ensuring trust and immutability. Traders can access real-time market data using Cryptofeed, a Python library. This helps them make informed decisions.&nbsp;&nbsp;
&nbsp;&nbsp;
Are there any Ethereum-based applications that use Python libraries?&nbsp;&nbsp;
Yes, Ethereum-based applications are using Python libraries. dApps, decentralized applications, often use Web3.py to interact with Ethereum contracts. Tools like Mythril help analyze smart contract security.&nbsp;&nbsp;
&nbsp;&nbsp;
How can I obtain coin information from the ledger using a Python library?&nbsp;&nbsp;
You can use Python libraries such as Web3.py to get coin information from blockchain ledgers. This includes account balances, transaction history, and token details. You can interact with blockchain nodes to do this.&nbsp;&nbsp;
&nbsp;&nbsp;
Is it possible to create a secure wallet using Python Blockchain Libraries?&nbsp;&nbsp;
You can use Python Blockchain Libraries to create secure wallets. They help create keys, addresses and sign transactions for security purposes. Properly implementing these libraries ensures wallet security.&nbsp;&nbsp;
&nbsp;&nbsp;
How can you track real-time cryptocurrency trading data using a Python Blockchain Library?&nbsp;&nbsp;
You can use Cryptofeed and Python to watch real-time cryptocurrency trading information. Traders can use these tools to see the current prices, order book updates, and market data. This information helps them make decisions when trading cryptocurrency.&nbsp;

24 best Python Blockchain Libraries

Build smart applications with real-time face recognition, finding and identifying faces in pictures, detecting, and manipulating facial features.&nbsp;
 
Deep learning face recognition algorithms in python detect an image by finding essential feature points in a picture, such as eyes, nose, eyebrows, corners of the mouth, lips, etc. Whereas traditional face recognition algorithm, such as the Local Binary Patterns Histograms (LBPH), breaks an image into thousands of smaller, bite-sized tasks, also known as classifiers. Certain face recognition python source code support single-shot learning. These systems can train themselves to detect a person through a single picture. However, there are some challenges faced by AI face detection programs, such as different human poses and facial expressions, low resolution, high illumination, etc.
 
The following is a comprehensive list of the best open-source python libraries for face recognition:
 
Popular among developers, the face_recognition library boasts a 99.38% accuracy. It can help perform recognition on a single image or a folder of images from the command line itself.
 
The OpenCV python face recognition library detects faces in a picture through machine learning algorithms. It breaks the process into multiple stages called ‘cascade’.&nbsp;
 
The dlib face recognition&nbsp;library employs the MMOD (Deep Learning) algorithm to draw a bounding box around every face in the image. It provides output by matching the input face with the dataset.

Face Recognition

As developers, we encounter many situations where we need to read images in our applications for image-processing tasks, including recognition, upload, enhancement, training, and many others. 
 
Python has many libraries that provide the ability to work with images. The image capabilities in Python include image manipulation, enhancement, etc. Python users frequently use Matplotlib to build static, animated, and interactive visualizations. It offers a sophisticated drawing tool for creating eye-catching and educational statistical visuals.&nbsp;Matplotlib is designed to be used with the broader SciPy stack, which includes tools for working with arrays, numerical optimization, and data analysis. It is frequently combined with other libraries, such as NumPy and Pandas, to provide robust and engaging data visualizations.&nbsp;You can use the imread() function from the matplotlib.pyplot module to read an image in Python using matplotlib. This function accepts a string representing the image's path and returns a numpy.ndarray object with the image's pixel information.&nbsp;Note that the imread() function can only read image files that are supported by matplotlib, such as PNG, JPG, and BMP. You will get an error if you try to read an unsupported image file.&nbsp;
 
Here is an illustration of how to read a picture in Python using matplotlib:&nbsp;
 

Fig 1: Preview of the output that you will get on running this code from your IDE
<h3>Code</h3>
In this solution we use the Imread function of the Matplotlib library.
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.</li>
 <li>Modify the name, location of the image to be read in the code.</li>
 <li>Run the file to read the image.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=read%20image%20in%20python" rel="noopener noreferrer" target="_blank">read image in python</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have Matplotlib that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the Matplotlib page in kandi.
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=Matplotlib" rel="noopener noreferrer" target="_blank">Matplotlib</a>.
<iframe class="ql-video" frameborder="0" allowfullscreen="true" src="https://www.youtube.com/embed/gWUF0uZS5Es?showinfo=0"></iframe>
 
<h3>Environment Tested</h3>
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.9.</li>
 <li>The solution is tested on Matplotlib 3.4.3 version.</li>
</ol>
Using this solution, we are able to read an image using the Matplotlib library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read an image in Python.
<h3>Support</h3>
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Read an Image using Matplotlib in Python

<h3>Code</h3>
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.</li>
 <li>Modify the name, location of the image to be read in the code.</li>
 <li>Run the file to read the image.</li>
</ol>

Java

Read text file from URL using Java

Image Gray scaling is converting a color image to a grayscale, a representation of the image using shades of gray only. Unlike color images, which have three channels, grayscale images only have one channel (red, green, and blue).&nbsp;
 
There are many applications of the greyscale image, like reducing the file size of an image, enhancing the contrast or sharpness of an image, simplifying an image to make it easier to analyze or process using image processing algorithms, and more for your application.&nbsp;To convert an image to grayscale using OpenCV in Python, you can use the cv2.cvtColor() method. This technique uses the cv2.COLOR BGR2GRAY color space conversion function to convert the original image to grayscale. An object of type numpy.ndarray is then returned with the grayscale image.&nbsp;Try several color space conversion codes to determine which grayscale image best suits your needs. Note that different color space conversion codes, such as cv2.COLOR BGR2HSV or cv2.COLOR BGR2YCrCb, can be used with the cv2.cvtColor() method to convert an image to grayscale.&nbsp;
 
Here is an example of how to convert an image to grayscale using OpenCV in Python:&nbsp;

Fig 1: Preview of the output that you will get on running this code from your IDE
<h3>Code</h3>
In this solution, we use the cvtColor function of the Opencv library
<ol>
 <li>Copy the code in the 'Code Snippets' section and paste it in a Python file in the IDE.</li>
 <li>Modify the location of the image to be converted to grayscale in the pasted code.</li>
 <li>Run the file to convert the image to grayscale.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=convert%20image%20to%20gray%20scale%20opencv" rel="noopener noreferrer" target="_blank">convert image to grayscale opencv</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
 
If you do not have OpenCV that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the OpenCV Github &amp; installation page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=opencv" rel="noopener noreferrer" target="_blank">OpenCV</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.9.</li>
 <li>The solution is tested on OpenCV-Python 4.5.4 version.</li>
</ol>
 
Using this solution, we are able to create grayscale images using the OpenCV library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us create a grayscale image in Python.
<h3>Support</h3>
 
<ol>
 <li>For any queries on installing/using this solution, reach out to us through the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For information on more similar learning resources, visit our Community learning page <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">here</a>.</li>
</ol>

Shell

How to Convert an Image to Grayscale using OpenCV in Python

Digital image processing uses image blurring. It helps in removing graining from an image, improving the quality of the image, and blurring the background.&nbsp;
 
An open-source and free library of computer vision and machine learning methods is called OpenCV (Open-Source Computer Vision). It is employed in several procedures, including object identification, image stitching, and video stabilization. Although it is written in C++, it provides interfaces for other programming languages like Python, Java, and C#. OpenCV is frequently employed in academic and commercial projects and is available for Windows, Linux, and macOS. To make an image blurry, you can use the GaussianBlur() method of OpenCV.
 
OpenCV-Python uses Numpy, a highly efficient library for numerical operations with a MATLAB-like syntax. Numpy arrays are translated into and out of all OpenCV array forms. The GaussianBlur() function uses the Gaussian kernel. The height and width of the kernel should be a positive and an odd number. Then you must specify the X and Y directions, which are sigmaX and sigmaY, respectively. If only one is specified, both are considered the same.
 
Here is an example of how you might use this function to make an image blurry:

Fig 1: Preview of the output that you will get on running this code from your IDE
 
<h3>Code</h3>
In this solution, we use the GaussianBlur function of the Opencv library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.</li>
 <li>Modify the name, location of the image to be blurred in the code.</li>
 <li>Run the file to create a blurred image.</li>
</ol>
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=make%20a%20blurred%20image%20using%20opencv" rel="noopener noreferrer" target="_blank">make a blurred image using opencv</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have OpenCV that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the OpenCV page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=opencv" rel="noopener noreferrer" target="_blank">OpenCV</a>.
<h3>Environment Tested</h3>
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.9.</li>
 <li>The solution is tested on OpenCV-Python 4.5.4 version.</li>
</ol>
Using this solution, we are able to make blurred images using the OpenCV library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us an image in Python.
<h3>Support</h3>
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to blur an image in OpenCV Python 

OpenCV is an open-source library of computer vision and ML methods. It is used in video stabilization, image processing, and object detection.&nbsp;It is written in C++ but offers interfaces for Python, Java, and C#, as well as other computer languages. With Windows, Linux, and macOS support, OpenCV is widely used in academic and industrial projects.&nbsp;
 
A common task in digital image processing is image scaling. Applications for resizing photographs include the following: adjusting the image size to fit a specific layout for a website or print publication; matching the dimensions of different images; reducing file size; improving resolution; and more.&nbsp;
 
The cv2.resize() function of OpenCV can be used to resize an image. This function accepts these arguments:&nbsp;
<ul>
 <li>‘src’: The source of the original picture you want to resize.&nbsp;</li>
 <li>‘dim’: The size of the output image or dimension. Tuple should be used here in the form of (width, height), where width and height are the desired dimensions of the output image.&nbsp;</li>
</ul>
 
Here is an example of how you might use this function to resize an image using OpenCV with a maximum width and maximum height:&nbsp;

Fig 1: Preview of the output that you will get on running this code from your IDE
 
 
<h3>Code</h3>
In this solution, we use the Resize function of the Opencv library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.</li>
 <li>Modify the name, location of the image to be resized in the code.</li>
 <li>Run the file to resize the image.</li>
</ol>
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=resize%20image%20using%20opencv" rel="noopener noreferrer" target="_blank">resize image using opencv</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have OpenCV that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the OpenCV page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=opencv" rel="noopener noreferrer" target="_blank">OpenCV</a>.
<h3>Environment Tested</h3>
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.9.</li>
 <li>The solution is tested on OpenCV-Python 4.5.4 version.</li>
</ol>
Using this solution, we are able to make blurred images using the OpenCV library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us an image in Python.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

Image Resizing using OpenCV in Python

Real-time speech recognition in Python refers to the ability of a computer program to transcribe spoken words into written text in real-time. You can use a library like SpeechRecognition to recognize speech in real time in Python. It supports several various engines and APIs, such as Microsoft Bing Voice Recognition and Google Speech Recognition.&nbsp;
 
Real-time voice recognition in Python has a wide range of uses, including:&nbsp;
<ul>
 <li>Voice-controlled assistants: These virtual assistants, like Siri or Alexa, can be operated via voice commands.&nbsp;</li>
 <li>Speech-to-text transcription: This tool turns audible words into written text and is useful in professions including journalism, law, and medicine.&nbsp;</li>
 <li>Voice biometrics: This application uses a person's distinctive voice patterns to authenticate and identify them.&nbsp;</li>
 <li>Real-time language translation: This program helps people who speak various languages communicate more easily by translating spoken words from one language to another.&nbsp;</li>
 <li>Speech-based accessibility: Applications that assist people with disabilities, such as text-to-speech or speech-to-text for the visually impaired.&nbsp;</li>
</ul>
 
Here is how you can recognize speech in real-time in Python:&nbsp;

Fig 1: Preview of the output that you will get on running this code from your IDE
 
<h3>Code</h3>
 
In this solution, we use the Recognizer function of the Speech Recognition library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.</li>
 <li>Run the file. You will be prompted to speak something through your microphone</li>
 <li>The speech in real-time gets processed and displayed on screen</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=speech%20recognition%20in%20python" rel="noopener noreferrer" target="_blank">speech recognition in python</a>" in kandi. You can try any such use case!
 
<h3>Dependent Libraries</h3>
If you do not have Speech Recognition that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the Speech Recognition page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=speech%20recognition" rel="noopener noreferrer" target="_blank">SpeechRecognition</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.9.</li>
 <li>The solution is tested on SpeechRecognition 3.8.1 and PyAudio 0.2.12 versions.</li>
</ol>
 
Using this solution, we are able to make blurred images using the OpenCV library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us to recognize speech in real-time in Python.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

Speech Recognition in Python

You can create a word cloud from a CSV file in Python using the wordcloud library. This program offers a straightforward and user-friendly interface for creating word clouds from text data. The procedure normally starts with loading the data from the CSV file, followed by text pre-processing (such as deleting stop words and stemming) and word cloud generation using wordcloud.WordCloud class.&nbsp;
 
Word clouds are a popular tool for visualizing the most common words in a large corpus of text data.&nbsp;
They can be used in various applications, such as:&nbsp;
<ul>
 <li>Text mining: Word clouds can be used to find important themes and trends in massive text data sets, including customer reviews and social media posts.&nbsp;</li>
 <li>Content marketing: We can use the wordcloud to help guide content planning and SEO efforts to determine the most popular subjects and keywords in a website's content.&nbsp;</li>
 <li>Data visualization: Word clouds can be employed to produce aesthetically pleasing and simple-to-understand representations of text data, making it simpler to convey findings to non-technical audiences.&nbsp;</li>
 <li>Sentiment analysis: Word clouds can also be used to analyze the sentiments of a given dataset; in the word cloud, positive or negative words will be more prevalent.&nbsp;</li>
</ul>
 
Here is how you can create a word cloud from csv in Python:&nbsp;

Fig 1: Preview of the output that you will get on running this code from your IDE
<h3>Code</h3>
In this solution we use the generate function of the WordCloud library.
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.</li>
 <li>Create a csv file with one column containing words.</li>
 <li>Modify the reading mode in the code from 'rb' to 'r'</li>
 <li>Modify the name, location of the csv to be read in the code.</li>
 <li>Run the file to create a WordCloud.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=create%20word%20cloud%20from%20csv" rel="noopener noreferrer" target="_blank">create word cloud from csv</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have Matplotlib and WordCloud that are required to run this code, you can install them by clicking on the above link and copying the pip Install command from the Matplotlib and WordCloud pages in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=Matplotlib" rel="noopener noreferrer" target="_blank">Matplotlib</a> and <a href="https://kandi.openweaver.com/search?q=word_cloud" rel="noopener noreferrer" target="_blank">WordCloud</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.9.</li>
 <li>The solution is tested on Matplotlib 3.4.3 and WordCloud 1.8.1 version.</li>
</ol>
 
Using this solution, we are able to create a Wordcloud from csv using the WordCloud and Matplotlib libraries in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us create a word cloud from csv in Python.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Create a Word Cloud from CSV in Python

A DataFrame is a two-dimensional, size-mutable, and heterogeneous tabular data structure with labeled axes (rows and columns) that can be used to store and manipulate data in a variety of formats, including numbers, strings, and dates. It is similar to a table in a relational database or a data frame in R or Python's pandas library. It can be thought of as a collection of Series (one-dimensional arrays) that share the same index.&nbsp;
 
There are several techniques to extract web data into a pandas DataFrame. Here are several possibilities:&nbsp;
<ul>
 <li>To load data from an online CSV file, use the pandas library's read_csv() method.&nbsp;</li>
 <li>read_csv(): The read_csv() function is a function in the pandas’ library for reading data from a CSV (comma-separated values) file into a pandas DataFrame.&nbsp;&nbsp;</li>
 <li>To load data from an online Excel file, use the pandas library's read_excel() method.&nbsp;</li>
 <li>read_excel(): The pandas’ library includes the read_excel() method for reading data from an Excel file into a pandas DataFrame.&nbsp;&nbsp;</li>
 <li>To load data from an online HTML table, use the pandas library's read_html() method.&nbsp;</li>
 <li>read_html(): A pandas DataFrame may be created by reading data from an HTML table using the read_html() method in the pandas package.&nbsp;</li>
</ul>
 
You can have a look at the code below to create Pandas DataFrame using online data.&nbsp;

Fig 1: Preview of the output that you will get on running this code from your Jupyter notebook
 
<h3>Code</h3>
 
In this solution, we use the read_csv function of the Pandas library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Run the cell to read online data and create a Pandas dataframe.</li>
</ol>
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=download%20csv%20to%20pandas" rel="noopener noreferrer" target="_blank">download csv to pandas</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have Pandas that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the Pandas page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=pandas" rel="noopener noreferrer" target="_blank">Pandas</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on Pandas 1.3.1 version.</li>
</ol>
 
Using this solution, we are able to read online data and create a Dataframe using the Pandas library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read data in Pandas.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Create Pandas DataFrame from Online Data in Python

A DataFrame is a tabular data structure with rows and columns that can carry any form of data and is two-dimensional size mutable. It is a crucial component of the "pandas" library, a well-liked Python library for data manipulation and analysis. A dataframe's rows and columns may be used to access and edit the data. Additionally, you may execute operations on the data using a variety of functions and methods from the pandas' library, including filtering, aggregation, and transformation.
 
In Python, DataFrames are a crucial tool for manipulating and analyzing data.&nbsp;
<ul>
 <li>pandas: It is designed to operate effectively with huge datasets. In the field of data science, it is frequently used for operations including data preparation, cleansing, and analysis.&nbsp;</li>
</ul>
You can use the to_csv() method of a pandas DataFrame to write the contents of the DataFrame to a CSV (comma-separated values) file.&nbsp;
<ul>
 <li>to_csv(): This is used to write the DataFrame to a specific location on your filesystem by specifying the full path to the file as the first argument.&nbsp;</li>
</ul>
The to_csv() function offers a wide range of additional arguments that you may use to alter the output. For instance, you may use the "header" argument to include or remove the column names in the output or the "sep" parameter to define a different delimiter for the columns.&nbsp;
 
Here's an example of how to write a Pandas DataFrame to a CSV file.
<h3>Code</h3>
 
In this solution, we use the to_csv function of the Pandas library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Modify the path the file to be written.</li>
 <li>Run the cell to write a Pandas dataframe to a csv.</li>
 <li>Install the 'openpyxl' library using the command "pip install openpyxl" and run the cell to write a Pandas dataframe to excel.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=write%20dataframe%20to%20excel" rel="noopener noreferrer" target="_blank">write dataframe to excel</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have Pandas that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the Pandas page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=pandas" rel="noopener noreferrer" target="_blank">Pandas</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on Pandas 1.3.1 version.</li>
</ol>
 
Using this solution, we are able to read online data and create a Dataframe using the Pandas library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read data in Pandas.
<h3> </h3>
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Write a Pandas DataFrame to a CSV file

Python has many libraries which provide the ability to work with data. Pandas is a comprehensive and popular Python library which provides the ability to read, process and analyze data. In this solution kit, I am sharing the code snippet and library that I use to read standard Iris data available online and create a Pandas DataFrame which can be executed directly in the Jupyter Notebook.
 

Fig 1: Preview of the output that you will get on running this code from your Jupyter notebook
 
<h3>Code</h3>
 
In this solution, we use the read_csv function of the Pandas library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Run the cell to read Iris data and create a Pandas dataframe.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=read%20iris%20data%20pandas" rel="noopener noreferrer" target="_blank">read iris data pandas</a>" in kandi. You can try any such use case!
 
<h3>Dependent Libraries</h3>
 
If you do not have Pandas that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the Pandas page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=pandas" rel="noopener noreferrer" target="_blank">Pandas</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on Pandas 1.3.1 version.</li>
</ol>
 
Using this solution, we are able to read online data and create a Dataframe using the Pandas library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read data in Pandas.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

Load Standard Iris data set in Pandas

The plot() method of a DataFrame, based on the matplotlib package, may be used to create plots with the help of pandas, which offers an easy interface. The data in a pandas DataFrame are graphically represented using a pandas’ DataFrame visualization.
 
<ul>
 <li>plot(): You may generate a variety of plots for the data in a DataFrame using the plot() function, including line plots, bar graphs, scatter plots, and more. The columns used for the x-axis and y-axis may be specified using the x and y parameters, respectively. Additionally, you may select the type of plot to be created using the kind option (e.g. "line", "bar", "scatter", etc.).&nbsp;</li>
 <li>matplotlib: Python's matplotlib package allows users to build interactive, animated, and static visualisations. It offers a sophisticated drawing tool for creating eye-catching and educational statistics visuals. The scientific Python community frequently uses matplotlib to produce various plots and charts to display data.&nbsp;&nbsp;</li>
</ul>
Here is how you can plot a dataframe using Pandas;

Fig 1: Preview of the output that you will get on running this code from your Jupyter notebook
 
<h3>Code</h3>
 
In this solution, we use the plot function of the Pandas library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Add the code "import pandas as pd" above the pasted snippet.</li>
 <li>Run the cell to create Pandas dataframe plots.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=pandas%20dataframe%20plot" rel="noopener noreferrer" target="_blank">pandas dataframe plot</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
If you do not have Pandas that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the Pandas page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=pandas" rel="noopener noreferrer" target="_blank">Pandas</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on Pandas 1.3.1 version.</li>
</ol>
 
Using this solution, we are able to read online data and create a Dataframe using the Pandas library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read data in Pandas.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Plot a Dataframe using Pandas

A DataFrame is a two-dimensional size-mutable tabular data structure with rows and columns that can hold any data type. It is a crucial data structure in the pandas library, a popular library for data manipulation and analysis in Python.&nbsp;
 
<ul>
 <li>pandas: pandas is a library for data manipulation and analysis in Python. It provides a range of tools for working with data in a variety of formats, including:&nbsp;</li>
 <li>importing and exporting data from different formats (e.g. CSV, Excel, JSON)&nbsp;</li>
 <li>data cleanup and preparation for analysis&nbsp;</li>
 <li>data manipulation and transformation&nbsp;</li>
 <li>using plots and charts to represent data&nbsp;</li>
</ul>
 
We can use the sort_values() method of a pandas DataFrame to sort the data by one or more columns. This method returns a new DataFrame sorted by the specified columns.&nbsp;
<ul>
 <li>sort_values(): This will sort the DataFrame by the values in the given column in ascending order. You can use the ascending parameter to specify the sort order and set it to False to sort in descending order.&nbsp;</li>
</ul>
Here is how you can sort Pandas dataframe;

Fig 1: Preview of the output that you will get on running this code from your Jupyter notebook
 
 
<h3>Code</h3>
 
In this solution, we use the sort_values function of the Pandas library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Run the cell to sort a Pandas dataframe.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=pandas%20sort%20dataframe" rel="noopener noreferrer" target="_blank">sort pandas dataframe</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
 
If you do not have Pandas that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the Pandas page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=pandas" rel="noopener noreferrer" target="_blank">Pandas</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on Pandas 1.3.1 version.</li>
</ol>
 
Using this solution, we are able to sort a Dataframe using the Pandas library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read data in Pandas.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Sort Pandas DataFrame

Summary statistics are statistical measures that summarize or describe a set of observations. In the context of a pandas DataFrame, summary statistics are statistical measures that summarize the data in the DataFrame.&nbsp;
 
A pandas DataFrame's describe() function allows you to generate a number of summary statistics for the data. This function provides a new DataFrame with a row for each numerical column and a column for each statistic, along with the statistical summary of the data.&nbsp;
<ul>
 <li>describe(): A number of summary statistics, including as the count, mean, standard deviation, minimum, maximum, and quartiles of the data, are computed by default using the describe() method. You may select which columns to include in the summary using the include option and which columns to omit using the exclude parameter.&nbsp;</li>
</ul>
Other techniques, including mean(), median(), min(), max(), and std(), can be used to obtain certain summary statistics for the data.&nbsp;
 
Here is how to calculate summary statistics for a Pandas DataFrame;

Fig 1: Preview of the output that you will get on running this code from your Jupyter notebook
 
<h3>Code</h3>
 
In this solution, we use the describe function of the Pandas library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Run the cell to read online data and create a Pandas dataframe.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=pandas%20columns%20for%20summary%20statistics" rel="noopener noreferrer" target="_blank">pandas summary statistics</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
 
If you do not have Pandas that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the Pandas page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=pandas" rel="noopener noreferrer" target="_blank">Pandas</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on Pandas 1.3.1 version.</li>
</ol>
 
Using this solution, we are able to create summary statistics of a Dataframe using the Pandas library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us read data in Pandas.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

How to Calculate Summary Statistics for a Pandas DataFrame

Python is a popular and powerful programming language with capabilities to build software applications. In this solution kit, I am sharing the code snippet and library that I use to create a function to check if a number is prime which can be executed directly in the Jupyter Notebook or any IDE of choice.
 

Fig 1: Preview of the output that you will get on running this code from your IDE
 
 
<h3>Code</h3>
 
In this solution, we will create a function to check if a number is prime.
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in an IDE.</li>
 <li>Run the code and call the created function to check if the number is prime.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=for%20loop%20in%20python" rel="noopener noreferrer" target="_blank">for loop in python</a>" in kandi. You can try any such use case!
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7</li>
</ol>
 
Using this solution, we are able to create a function to check a number is prime in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us check if a number is prime.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-programming-basics/19" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

Check if a number is Prime using loops and conditionals in Python

Python is a popular and powerful programming language with capabilities to build software applications. In this solution kit, I am sharing the code snippet and library that I use to create a train-test split of data in Python which can be executed directly in the Jupyter Notebook or any IDE of choice.
 

Fig 1: Preview of the output that you will get on running this code from your Jupyter notebook
 
 
<h3>Code</h3>
 
In this solution, we use the train_test_split function of the Scikit-learn library
<ol>
 <li>Copy the code using the "Copy" button above, and paste it in a cell of Jupyter notebook.</li>
 <li>Run the cell to split dataframe to train and test.</li>
</ol>
 
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
 
I found this code snippet by searching for "<a href="https://kandi.openweaver.com/search/codesnippet?q=train%20test%20split%20python" rel="noopener noreferrer" target="_blank">train test split python</a>" in kandi. You can try any such use case!
<h3>Dependent Libraries</h3>
 
If you do not have scikit-learn that is required to run this code, you can install it by clicking on the above link and following the installation instruction from either Github or Pypi links through the scikit-learn page in kandi.
 
You can search for any dependent library on kandi like <a href="https://kandi.openweaver.com/search/libraries?q=scikit-learn" rel="noopener noreferrer" target="_blank">scikit-learn</a>.
<h3>Environment Tested</h3>
 
I tested this solution in the following versions. Be mindful of changes when working with other versions.
<ol>
 <li>The solution is created in Python3.7.</li>
 <li>The solution is tested on scikit-learn 0.23.2 version.</li>
</ol>
 
Using this solution, we are able to split a Pandas Dataframe to test and train using the scikit-learn library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us split a dataframe to test and train.
<h3>Support</h3>
 
<ol>
 <li>For any support on kandi solution kits, please use the <a href="https://community.openweaver.com/chat/channel/3/kandi-support" rel="noopener noreferrer" target="_blank">chat</a></li>
 <li>For further learning resources, visit the Open Weaver Community <a href="https://community.openweaver.com/c/learning-hub-ai-ml/14" rel="noopener noreferrer" target="_blank">learning page</a>.</li>
</ol>

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