Apify
import.io
Octoparse
ParseHub
Bright Data
Scrapy
Data Miner
Zyte
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Apify is a JavaScript & Node.js based data extraction tool for websites that crawls lists of URLs and automates workflows on the web. With Apify you can manage and automatically scale a pool of headless Chrome / Puppeteer instances, maintain queues of URLs to crawl, store crawling results locally or in the cloud, rotate proxies and much more.
Apify MatplotlibBased on our record, Matplotlib should be more popular than Apify. It has been mentiond 114 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.
Data collection: Apify actors, one per source, that scrape the open-data endpoints and normalize them. Quebec RBQ ships a daily bulk CSV (inside a 10.8 MB zip, ~924k rows that dedupe to ~54k active licences). Ontario HCRA has no bulk file โ it's an internal JSON API behind the public registry. - Source: dev.to / about 5 hours ago
Create a free Apify account and grab your API token from Settings โ API & Integrations. - Source: dev.to / 8 days ago
BYOK. It runs on your own Apify token. No shared keys, no lock-in, no licensing chokepoint โ a lesson the whole "Proxycurl shut down and stranded everyone" saga taught the space. - Source: dev.to / 23 days ago
You need apify-client installed (pip install apify-client pandas scikit-learn). Get a free Apify API token at apify.com โ no card required, every account starts with $5 of credit. - Source: dev.to / about 1 month ago
A free Apify account (for the API token). - Source: dev.to / about 1 month ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.
NumPy - NumPy is the fundamental package for scientific computing with Python
ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.