teleren/devto huggingface dataset:
Creating Interactive Maps with React and Mapbox
Tags: react, map, javascript, frontend
Published: 2023-10-14 15:19:10

_Embark on a journey where the world becomes your canvas, and your React application transforms into an interactive map masterpiece. In this guide, we'll unravel the secrets of seamlessly integrating Mapbox into your React realm, adding markers, popups, and custom layers that beckon exploration._

**Setting the Stage: Integrating Mapbox with React**

Before the magic unfolds, let's lay the groundwork. Install the react-map-gl library, a React wrapper for Mapbox, to seamlessly blend the power of React with the cartographic prowess of Mapbox.

`npm install react-map-gl mapbox-gl
`
Now, within your React component:

```
import ReactMapGL from 'react-map-gl';

function InteractiveMap() {
  const [viewport, setViewport] = useState({
    width: '100%',
    height: 400,
    latitude: 37.7577,
    longitude: -122.4376,
    zoom: 8,
  });

  return <ReactMapGL {...viewport} onViewportChange={setViewport} mapboxApiAccessToken={YOUR_MAPBOX_TOKEN} />;
}
```
Replace YOUR_MAPBOX_TOKEN with your Mapbox API token obtained from the Mapbox website.


![Img1](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/sountb7iz89ou1266rwm.png)

**Adding Markers and Popups: Plotting Points of Interest**

Now, let's sprinkle some magic onto our map by adding markers and popups to highlight points of interest.

```
import { Marker, Popup } from 'react-map-gl';

function InteractiveMap() {
  // ... (previous code)

  const [selectedPlace, setSelectedPlace] = useState(null);

  return (
    <ReactMapGL {...viewport} onViewportChange={setViewport} mapboxApiAccessToken={YOUR_MAPBOX_TOKEN}>
      {/* Markers */}
      <Marker latitude={37.7577} longitude={-122.4376} offsetLeft={-20} offsetTop={-10}>
        <div onClick={() => setSelectedPlace('San Francisco')}>📍</div>
      </Marker>

      {/* Popup */}
      {selectedPlace && (
        <Popup
          latitude={37.7577}
          longitude={-122.4376}
          onClose={() => setSelectedPlace(null)}
        >
          <div>
            <h2>{selectedPlace}</h2>
            <p>Beautiful city by the bay!</p>
          </div>
        </Popup>
      )}
    </ReactMapGL>
  );
}
```
Replace 
> URL_TO_YOUR_GEOJSON_DATA

 with the URL to your GeoJSON data source.

**Handling User Interactions: A Map that Responds**

React to user interactions on the map by capturing events such as clicks and movements.

```
function InteractiveMap() {
  // ... (previous code)

  const handleClick = (event) => {
    const { lngLat } = event;
    console.log(`Clicked on: ${lngLat}`);
  };

  return (
    <ReactMapGL {...viewport} onViewportChange={setViewport} mapboxApiAccessToken={YOUR_MAPBOX_TOKEN} onClick={handleClick}>
      {/* ... (previous code) */}
    </ReactMapGL>
  );
}
```
Now, your map not only displays information but also responds dynamically to the user's actions.

With these spells and incantations, you've now mastered the art of creating interactive maps with React and Mapbox. May your maps be ever-engaging and your users wander in awe of your digital cartography! 🗺️✨

### Happy Coding 🚀 !!!
Unravelling this #Hacktobersfest10 Yarn
Tags: hacktoberfest23, javascript, beginners, opensource
Published: 2023-10-14 15:14:55

###13 October 2023


I'm kind of now exploring packages and just going off track. And realising that most of the js in repos that I did not understand is probably node.js. 
And then now I just discovered that all the .yml extensions have to do with yarn or its alternative npm and maybe others.
I have discovered package managers too inadvertently.
I have discovered dependencies.
How important are dependencies ?
How to use them and why to use them?

###14 October 2023

And the rabbit hole today leads me to figure out more about package managers. 
I don't remember how I got to try yarn in the place of npm. It might have been because of an article that I read that mentioned npm and yarn together a long time ago. 
And today I remembered that I could not install npm. So yarn came to mind and then I went into the rabbit hole.

I am studying package managers and trying to understand their importance and trying to figure them out .
How and what importance are package managers?
And how to use them?
How to put them to use or approach when trying to get into using and understanding a repo.?

This all started because I'm trying to figure out why there is so many files with so many different extensions in the repos.

I have not learnt anything much yet at all but I am just discovering and finding shelf space in my head for all this knowledge.

I still do not understand what the dependencies do exactly and why they got to ruin my js github nooby #hacktober10  experience.

But I'm learning and I guess I'm contributing.
Thanx #HacktoberFest.

#hacktoberFest10.
Mastering CSS Grid and Flexbox: Layouts Made Easy
Tags: webdev, beginners, tutorial, css
Published: 2023-10-14 15:06:48

_Welcome to the realm of web design wizardry, where the spells of CSS Grid and Flexbox converge to create enchanting layouts that captivate your users. In this magical journey, we'll delve deep into the arcane arts of CSS Grid, unraveling its potent powers for crafting responsive and visually stunning designs._

## Unveiling the Power of CSS Grid


![Img1](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ysf8ad4124qlwzzukjoe.gif)

CSS Grid is the master architect of layouts, offering a two-dimensional grid system that transforms the way we structure web content. Imagine a grid as your canvas, where you can effortlessly position and size elements, creating intricate designs with ease.

```
.container {
  display: grid;
  grid-template-columns: repeat(3, 1fr);
  gap: 20px;
}

.item {
  grid-column: span 2;
}
```
Here, our incantation begins with display: grid, summoning the grid on our container. grid-template-columns orchestrates the columns, and gap introduces a harmonious spacing between elements. The grid-column spell then dictates the span of an element across columns.

**Navigating Complex Grid Structures**

_Now, let's embark on a quest to create complex grid structures tailored to different use cases. Whether it's a magazine-style layout or a portfolio grid, CSS Grid weaves its magic seamlessly._

```
.magazine-layout {
  display: grid;
  grid-template-columns: 1fr 3fr;
  gap: 20px;
}

.portfolio-grid {
  display: grid;
  grid-template-columns: repeat(auto-fill, minmax(200px, 1fr));
  gap: 15px;
}
```

The magazine-layout grid showcases a two-column structure for a sleek reading experience, while the portfolio-grid dynamically adapts to various screen sizes, thanks to auto-fill and minmax.

**Responsive Design Elegance**
_No spell is complete without the ability to shape-shift gracefully across devices. CSS Grid, with its responsive prowess, ensures your design remains captivating on screens of all sizes._

```
@media (max-width: 768px) {
  .container {
    grid-template-columns: 1fr;
  }
}
```
With a sprinkle of media queries, we command our grid to transition to a single column when the screen size is compact, ensuring a delightful experience on mobile devices.


![Img2](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/jwzqk0beh3v9ecatny8j.gif)

**Enhancing Mastery Through Games**

What better way to refine your mastery than through the art of games? Challenge yourself with CSS Grid games like "Grid Garden" or "CSS Grid Layout by Example." These interactive experiences will hone your skills and transform learning into an adventure.

So, there you have it—CSS Grid and Flexbox, the dynamic duo in your toolkit for creating layouts that defy the ordinary. May your web designs be ever-responsive and visually enchanting. 

### Happy coding! ✨
The Ultimate Guide to Python for Data Science
Tags: python, datascience, career
Published: 2023-10-14 14:44:17

## Introduction
Python is a multi-purpose programming language that is gaining popularity in the field of data science. It is best known for its clarity, readability, and adaptability. A Large and active community of Python developers has produced several libraries and data science tools. Data import, Cleaning, Analysis, and Visualisation are made simple by these packages. Python is a solid programming language for AI/ML.

### Why Learn Python for Data Science?
Python is an excellent programming language for data science for a variety of reasons. Here are a few examples:

- Python is simple to use and learn.
- A large and active development community exists for Python.
- For data science, Python includes a large selection of libraries and tools.
- Open-source and cost-free to use is Python.

### Python Libraries Used in Data Science:

- NumPy: This library is used for scientific computing. It provides a high-performance multidimensional array object and a wide range of mathematical functions.
- Pandas: Essential for data manipulation and analysis, providing data structures like DataFrames.
- Matplotlib: This Matplotlib library is used for plotting the data. It provides a wide range of plotting features, that include 2D and 3D plots, Histograms, & Scatter Plots.
- Seaborn: Used in statistical plotting. It builds on Matplotlib and provides additional features for creating beautiful and informative statistical plots.
- Scikit-learn: A go-to library for machine learning, offering tools for classification, regression, clustering, & many more.
TensorFlow and PyTorch: Deep learning libraries that are often employed to build and train neural networks.
- NLTK (Natural Language Toolkit) and SpaCy: For Natural Language Processing (NLP) tasks like text analysis and language understanding.
- StatsModels: Used for statistical modeling and hypothesis testing

## [Read the Full Article](https://medium.com/@Aniket01/the-ultimate-guide-to-python-for-data-science-c35898e02592)
The Role of Data Visualization In Data Analysis
Tags: datascience, python, analytics
Published: 2023-10-14 14:41:33

## The Role of Data Visualization in Data Analysis
Data visualization is a vital tool in data analysis because it makes it simpler for people to comprehend and analyze complicated data sets. When developing data visualizations, it’s critical to use the best practices and suitable visualization techniques for the data under consideration. Because it allows for the conclusion drawn from data and the communication of complicated information to stakeholders, data visualization is crucial to decision-making. Data visualization will be more crucial than ever to aid us in making sense of the enormous amounts of data we currently handle.

## Why is Data Visualization Important?
Data interpretation through visualization plays a difficult role as it enables the representation of data in a visually intuitive manner, facilitating the identification of patterns, trends, correlations, and outliers that might not be readily apparent in tables or spreadsheets. This becomes especially valuable when dealing with vast volumes of data. Additionally, data visualization assumes critical importance in conveying complex information to individuals who may not possess technical expertise. In sectors like public health, effective communication of data to policymakers and the general public is vital, and visualizing data becomes instrumental in achieving this objective.

## Types of Data Visualization
There are several types of Data Visualization Techniques.

## [Read The Full Article](https://medium.com/@Aniket01/the-role-of-data-visualization-in-data-analysis-42b025594dc0)
The Role of Data Science in Sports Analytics
Tags: datascience, python, analytics
Published: 2023-10-14 14:28:54

## Introduction:
Data science has become a game-changer in the current era of sports, completely altering how teams, coaches, and athletes approach competition. The days of making decisions in sports solely based on intuition and gut feelings are long gone. Data science is becoming a crucial element in sports analytics because to the development of sophisticated data-collecting tools and cutting-edge analytical approaches. This article examines how data science is essential to improving performance, creating game strategies, and reaching wise conclusions in the realm of sports.

### Enhancing Performance Through Data Analysis:
Data science gives athletes and teams the ability to examine their performance indicators in-depth and reveal previously undiscovered insights. Players and coaches may spot patterns, trends, and areas for improvement by gathering a tonne of data throughout practices and games. Machine learning algorithms and other advanced analytics approaches enable the identification of subtle relationships and correlations that could otherwise go undetected.

For instance, data science may provide the most efficient offensive and defensive methods in team sports like football or basketball, showing the ideal player placement, passing patterns, and shooting angles. Teams may create game strategies that maximise scoring possibilities and minimise defensive weaknesses by analysing player movements and ball trajectories.

## Predictive Analytics for Informed Decision — making:
Data science is essential to predictive analytics since it helps teams forecast outcomes and make informed decisions. Teams may create prediction models that anticipate player performance, injury risks, and game outcomes by analysing historical data. These models can aid managers and coaches in making tactical modifications during games as well as squad selections and replacements.

Data science also aids in the treatment and prevention of injuries. Teams can detect possible injury risks and take proactive actions to reduce them by analysing player workload, physiological data, and injury history. By using this data, training plans may be improved, player recuperation can be controlled, and long-term player fitness can be guaranteed.

## [Read The Full Article](https://medium.com/@Aniket01/the-role-of-data-science-in-sports-analytics-e92d07fe2b8e)
AI in 2023: The Year of the metaverse
Published: 2023-10-14 14:24:05

2023 is shaping up to be the year of the metaverse, and artificial intelligence (AI) is playing a major role in its development. AI is being used to create more immersive and realistic experiences in the metaverse, as well as to power new applications and services.
Here are some of the ways AI is being used in the metavers.

Creating immersive experiences: AI is being used to create more immersive and realistic experiences in the metaverse. For example, AI can be used to generate realistic 3D models of people and objects, as well as to create realistic environments. This makes it possible for users to feel like they are actually in the metaverse, which can lead to a more engaging and enjoyable experience.

Powering new applications and services: AI is also being used to power new applications and services in the metaverse. For example, AI can be used to create virtual assistants that can help users with tasks such as finding information, navigating the metaverse, and interacting with other users. AI can also be used to create new forms of entertainment, such as games and simulations.

The metaverse is still in its early stages of development, but AI is already playing a major role in its growth. As the metaverse continues to evolve, AI is likely to become even more important.

Here are some of the potential benefits of using AI in the metaverse:

Improved user experience: AI can be used to improve the user experience in the metaverse in a number of ways. For example, AI can be used to create more realistic and immersive experiences, as well as to provide users with personalized recommendations and content.
How Data Science is Revolutionizing Business Decision-Making
Tags: datascience, data, career
Published: 2023-10-14 14:23:29

Organisational processes have been transformed by Data Science. The role of data science in business decision-making has become increasingly critical. businesses may seek informed decisions that lead to greater results using information-driven experiences. This article will discuss the importance of data science in business decision-making.

### Identifying Patterns and Trends
Organizations may benefit from data science by differentiating between examples and trends in their data. Organizations may study their data and identify patterns that might otherwise be invisible using cutting-edge inspection technologies. Understanding these instances allows Organizations to make accurate and informed decisions that significantly impact their principal priority.

### Predictive Analytics
Predictive analysis is yet another crucial component in data science. Organizations can predict future trends and events by looking at real facts. companies may use this information to help them make better decisions about their operations, marketing strategies, and product development.

### Customer Segmentation
Data science may help Organizations divide their clients into different groups based on their preferences and methods of behaving. This information may help businesses tailor their advertising messaging and product offerings to certain clientele groups, increasing consumer loyalty and upkeep.

### Operating Effectiveness
Data science may assist firms in improving their operations by finding prospective growth opportunities. By assessing creation, inventory networks, and strategy data, Organizations may pinpoint constraints and inefficiencies and implement corrective measures to Optimize their cycles.

### Fraud detection
fraud detection can benefit greatly from the use of data science. By segmenting value-based information, Organizations can see patterns that can indicate false movement. Organizations may use this knowledge to take remedial action and stop further disasters by using it.

### Real-Time Decision Making
Data science may help organisations make ongoing decisions by integrating cutting-edge information into their work. Continuous information may help organisations identify problems and take early corrective action, leading to increased production and benefit.

## [Read the Full Article](https://medium.com/@Aniket01/the-role-of-data-science-and-business-decision-making-14273251f735)
My Pledge
Tags: hacktoberfest23
Published: 2023-10-14 14:00:50


### Intro

Hi, I am Udayan Sharma currently a 2nd Year student at Chitkara University. My interest lies in Graphic Design and AI/ML as well as a zeal to create smooth webpages with my Frontend development skills currently learning LLMs.

### Pledge

As October dawns, I am excited to take the Hacktoberfest Pledge for 2023. This is my commitment to celebrate and contribute to the open-source community.

Why am I taking this pledge?

Learning: Hacktoberfest is a fantastic opportunity to enhance my coding and collaboration skills. I believe in continuous learning, and this event provides the perfect platform for growth.

Giving Back: I understand that open-source projects rely on the contributions of the community. By participating, I am giving back to the projects that have benefited me and countless others.

Connecting: I look forward to connecting with like-minded individuals who share my passion for technology and open source. Together, we can learn, collaborate, and make a real difference.

Swag: Of course, the prospect of earning limited-edition Hacktoberfest swag is a great motivator. But the true reward lies in the experience and the knowledge gained.

Happy Coding :)

#MyHacktoberfest PRS

1:https://github.com/dakshsinghrathore/ISRO-web/pull/64

2:https://github.com/Artlfmj/course-manager/pull/31

3:https://github.com/ivedantmistry/vedantmistryy.github.io/pull/34

4:https://github.com/ivedantmistry/vedantmistryy.github.io/pull/32

5:https://github.com/ivedantmistry/vedantmistryy.github.io/pull/15
Overriding dependency version in Spring Boot
Tags: springboot, java
Published: 2023-10-14 13:58:50

Do you know that feeling when you spend hours trying to do something without any luck and then you find out that the solution could not be easier? Well, that just happened to me. I was trying to upgrade the Hibernate version in our Spring boot app.

## What doesn't work

I tried to exclude the dependency from spring boot and include the desired one the standard gradle way. With no luck...

```
    implementation ("org.springframework.boot:spring-boot-starter-data-jpa"){
        exclude group: 'org.hibernate.orm', module: 'hibernate-core'
        exclude group: "org.hibernate.orm", module: "hibernate-jpamodelgen"
    }
    implementation "org.hibernate:hibernate-core:$hibernateVersion"
```

After hours of trying to diagnose why I always got the version included in Spring Boot, I found out that there is the [Spring Boot dependency management plugin](https://docs.spring.io/dependency-management-plugin/docs/current/reference/html/#introduction). That's the plugin which handles all the spring boot versions and enforces the versions defined by spring boot.

## What works

Fortunately, there is a way to override the version. And it's super easy.

You just need to specify the version in your `build.gradle`.

```
ext['<dependency>.version'] = '6.0.9'
```

or using `properties.gradle`:

```
spring-framework.version=6.0.9
```

as stated [here in the Spring docs](https://docs.spring.io/dependency-management-plugin/docs/current/reference/html/#dependency-management-configuration-bom-import-override-property).


And voilà! It works! You can find the list of [the version properties you can override here](https://docs.spring.io/spring-boot/docs/3.1.1/reference/html/dependency-versions.html#appendix.dependency-versions.properties).

Hope this helps future travelers who will struggle with the same.

Thanks for reading, and please consider using and staring [Tolgee platform on GitHub ⭐️](https://github.com/tolgee/tolgee-platform) - a tool healing your localization pain.