DataMelt
LabPlot
SciDaVis
RJS Graph
Aveloy Graph
IGOR Pro
DPlot
OriginPro
Python
JavaScript
Java
C++
Rust
Ruby
PHP
Elixir
DataMelt is a Java program for statistics, general data analysis and data visualization. The program is often termed "computational platform" since it can be used with different programming languages (Java, Python, Groovy..). DataMelt is not limited to a single programming language. The program is used for numeric computation, statistics, analysis of large data volumes ("big data") and scientific visualization. Full description: https://handwiki.org/wiki/Software:DataMelt
DataMelt
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students and data scientists
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DataMelt has its roots in particle physics where data mining is a primary task. It was created as Software:jHepWork project in 2005 and it was initially written for data analysis for particle physics.
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Multiplatform. Supports multiple programming languages: Java, Python (Jython), Groovy, Ruby
DataMelt's answer
Large database of examples and code snippets https://datamelt.org/code/
DataMelt's answer
Students at universities and data scientists.
DataMelt's answer
Java (JDK any new new release including JDK20)
I like this DataMelt analysis program since it has many 2D/3D visualisation and a massive number of practical examples
Based on our record, Python seems to be more popular. It has been mentiond 299 times since March 2021. 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.
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
LabPlot - LabPlot is a KDE-application for interactive graphing and analysis of scientific data.
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SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.
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C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation