Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Workable
Greenhouse
Breezy.hr
Lever
Recruitee
LinkedIn Recruiter
Jobvite
SmartRecruiters
Workable is affordable, useable hiring software. It replaces email and spreadsheets with an applicant tracking system that your team will actually enjoy using.
Matplotlib WorkableWe used Workable to manage hiring across a few open roles, and overall it made the process much more organized than juggling emails and spreadsheets. Posting jobs and tracking candidates in one dashboard helped keep everyone on the same page, especially when multiple people were involved in interviews and feedback.
Where Workable shines is simplicity. You donโt need much training to get started, and most features are easy to understand. That said, if your hiring process is complex or heavily customized, you might start to feel boxed in. Some advanced reporting and automation options are also locked behind more expensive plans, which may not feel worth it for smaller teams.
Overall, Workable is a reliable, well-designed hiring tool that does exactly what it promises. Itโs not perfect, but for teams that want a clean and efficient recruiting setup without too much complexity, itโs a solid choice
Based on our record, Matplotlib seems to be a lot more popular than Workable. While we know about 114 links to Matplotlib, we've tracked only 1 mention of Workable. 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.
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 / 7 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
Link is 100% safe for work (it's a 3rd party job listing site - workable.com). Source: over 3 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Greenhouse - Greenhouse Software makes companies great at hiring.
NumPy - NumPy is the fundamental package for scientific computing with Python
Breezy.hr - A Modern Hiring Tool for the Entire Team. A uniquely simple, visual hiring tool you and your team will love.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
Lever - A modern web app for hiring. Lever is a simple, powerful way to manage lists of candidates during the hiring process.
