ApexCharts
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ApexCharts is a modern charting library that helps developers to create beautiful and interactive visualizations for web pages.
ApexCharts
PythonDevelopers and data scientists who need to create interactive and responsive charts quickly. It's also suitable for teams working on projects that require visually appealing and highly customizable data visualizations.
Based on our record, Python seems to be a lot more popular than ApexCharts. While we know about 299 links to Python, we've tracked only 15 mentions of ApexCharts. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
ApexCharts is an excellent library for creating interactive charts, and integrating it in [Vue.js (https://vuejs.org) is really a piece of cake. However, when it comes to displaying a time-series chart with thousands of points, the performance can suffer, sometimes causing the page to freeze during the rendering or when the user zooms or navigates through the data. - Source: dev.to / 2 months ago
If you wanted to take this one step further, you could instead export the data and build an entire app around it using something like ApexCharts or D3 to create more interactive visualisations. You could even build a dashboard that tracks your performance over time across multiple races. Lots of interesting possibilities here as the data set is pretty rich. I highly recommend checking out the pyrox-client... - Source: dev.to / 4 months ago
This is a basic HTML structure that includes Google Fonts, ApexCharts (for placeholder charts), and links to your compiled CSS and JavaScript files. The body includes classes for light and dark modes. - Source: dev.to / over 1 year ago
When working with large datasets, rendering all points in a line chart can cause significant performance issues. For example, plotting 50,000 data points directly can overwhelm the browser and make the chart unresponsive. Tools like amCharts and ApexCharts struggle with such datasets, while ECharts performs better but still isn't optimized for extremely large datasets. - Source: dev.to / over 1 year ago
ApexCharts is a modern charting library that helps developers to create beautiful and interactive visualizations for web pages. It is an open-source project licensed under MIT and is free to use in commercial applications. - Source: dev.to / almost 3 years ago
137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / 2 months ago
For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / 2 months ago
Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 4 months ago
**_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โSave this dataโ - โGet this dataโ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago
Chart.js - Easy, object oriented client side graphs for designers and developers.
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
AnyChart - Award-winning JavaScript charting library & Qlik Sense extensions from a global leader in data visualization! Loved by thousands of happy customers, including over 75% of Fortune 500 companies & over half of the top 1000 software vendors worldwide.
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation