See how Planview LeanKit enables engineering teams across all levels of the organization with a visual work delivery tool to apply Lean management principles to their work, helping them work smarter and deliver faster.
Forge your schedule, not spreadsheets. Drag-and-drop work orders, capacity-aware line scheduling, shop floor kiosk clocking, AI what-if scenarios, and a daily dashboard that tells you what needs attention.
sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Which is more popular?
Based on our record, Matplotlib
seems to be more popular. It has been mentioned
114 times
since March 2021.
social mentions
0 vs 114
Business & Commerce popularity
100% vs 0%
alternatives listed
86 vs 238
Base details
Website, pricing, platforms and company facts side by side.
Visual Workflow Management LeanKit offers a highly visual interface that allows users to manage their workflows effectively. With customizable Kanban boards, teams can easily see the status of tasks and identify bottlenecks.
Collaborative Features The platform supports real-time collaboration, enabling team members to work together more efficiently. Team members can comment, tag, and update tasks, facilitating better communication.
Scalability LeanKit is designed to scale with teams of varying sizes, making it suitable for both small teams and large enterprises. It supports scaling Agile practices and coordination across multiple teams.
Integration Capabilities LeanKit integrates with a wide range of other tools and platforms, including JIRA, GitHub, and Microsoft Teams, allowing for seamless integration into existing workflows.
Comprehensive Reporting and Analytics The solution provides detailed analytics and reporting features that offer insights into team performance and project progress, helping managers make informed decisions.
Possible disadvantages
Learning Curve New users may encounter a steep learning curve due to the extensive features and customization options available in LeanKit, which might require additional training.
Complexity for Small Teams The extensive feature set might be overwhelming for smaller teams or projects that do not require such robust capabilities, potentially leading to underutilization.
Cost LeanKit can be expensive for smaller teams or startups due to its pricing model, which may not be cost-effective if not all features are utilized.
Interface Customization Limitations Despite having customizable boards, some users find that the customization options for the interface are limited compared to other tools, which might affect usability.
Performance Issues Some users have reported performance issues, especially with larger boards or extensive datasets, which can lead to slower response times within the application.
Versatility Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
Customization It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
Integrations Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
Community and Documentation It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
Interactivity Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
Publication-Quality The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.
Possible disadvantages
Complexity While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
Performance Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
Modern Aesthetics Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
3D Plots Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
Size and Structure The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.
Analysis
An editorial look at what each product does well and who it suits.
LeanKit by PlanviewMatplotlib
No analysis of LeanKit by Planview yet.
Overall verdict
Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.
Why this product is good
Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.
Recommended for
Data scientists and analysts needing to create detailed, customized visual representations of their data.
Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
Python developers who require integration with other scientific computing libraries like NumPy and Pandas.
Videos
Walkthroughs and reviews on video.
LeanKit by Planview0 videos+ AddMatplotlib1 video+ Add
No LeanKit by Planview videos yet. You could help us improve this page by suggesting one.
Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial
Category popularity
How often each product is chosen within a category, 0–100% relative to the other.
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of...
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data...
Recommendations tracked on public social media and blogs since March 2021.
LeanKit by Planview0 mentionsMatplotlib114 mentions
Tracking LeanKit by Planview since Mar 2021.
The soul file
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib — the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review....
- Source: dev.to
/
8 months ago
Numbers are useful, but sometimes it’s 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...
- Source: dev.to
/
11 months ago
libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
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
/
12 months ago
Wrike is a flexible, scalable, and easy-to-use collaborative work management software that helps high-performance teams organize and accomplish their work. Try it now.
Compare Wrike to LeanKit by Planview or Matplotlib:
Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.
Compare Asana to LeanKit by Planview or Matplotlib:
Wrike
monday.com
Asana
Teamgantt
TaskBoard
Pintask
buckets.co
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
