
Waydev
LinearB
GitPrime
Swarmia
Haystack Analytics
CodeClimate
OKAY HQ
66Analytics
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Waydev helps managers to move from a feeling driven to a data-driven approach. Waydev includes concrete metrics for your daily stand-ups, 1-to-1 meetings, checking the history of the engineers work and benchmarking your stats with the industry.
Waydev
MatplotlibBased on our record, Matplotlib seems to be a lot more popular than Waydev. While we know about 114 links to Matplotlib, we've tracked only 2 mentions of Waydev. 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.
For example, in our traditional approach, every step and process is defined and has to be adhered to. Any change has to go through multiple approvals. The scope in itself has a very limited scope or flexibility towards change. I am on the fence looking for resources and tools that will help to slowly execute and implement these changes. With regards to resources, I am currently looking at the scrum guide and with... Source: almost 4 years ago
When youโre ready to translate data into greater visibility, and this visibility into faster, more efficient teams, you can start looking at development analytics platforms like Waydev. - Source: dev.to / over 4 years 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
LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
NumPy - NumPy is the fundamental package for scientific computing with Python
Swarmia - Swarmia is an engineering productivity software trusted by 600+ engineering teams worldwide. Use key engineering metrics to unblock the flow, align engineering with business objectives, and drive continuous improvement.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.