SVGIS
matplotlib
| SVGIS | matplotlib | |
|---|---|---|
| - | 36 | |
| 82 | 19,262 | |
| - | 0.9% | |
| 2.6 | 10.0 | |
| almost 2 years ago | 6 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Python License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SVGIS
We haven't tracked posts mentioning SVGIS yet.
Tracking mentions began in Dec 2020.
matplotlib
- How and where is matplotlib package making use of PySide?
-
Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/matplotlib/matplotlib
-
Tkinter, PyGame windows too large on Mac
as suggested here.
-
[OC] Attempted & Completed Suicide Rate in Canada, 1998/99
Tool: Matplotlib Pyplot
-
Help unpickling an old dataset
The issue was described here: https://github.com/matplotlib/matplotlib/issues/8409, but the "solution" was just "this is fixed" which was not helpful to me.
-
The Python Packages That Gave Me Nightmares: A Guide to Overcoming Common Challenges
Matplotlib: Matplotlib is a 2D plotting library that allows you to create visualizations of your data. It's a powerful tool for data analysis, but the syntax can be complex and the customization options can be overwhelming. GitHub - https://github.com/matplotlib/matplotlib
- pcolormesh very slow when using "log" axes
-
Question: What is matplotlib short for?
A quick google shows: this history.txt:
-
Linear Regression
Let's take a small subset i.e 20 data points of our prediction and compare it with actual output using matplotlib library
-
Where to find a dynamic charge density animation/simulation?
I will think more about what I want to say next, but for now, I would like to say that I need the super-particles and PIC methods as I think that is the way forward for me. Are there ways to implement these methods in matplotlib, Visit or Paraview? Do I take existing code and import it into those programs to visualize it? Or can I directly program/simulate something in those visualizion tools without needing to import any code?
What are some alternatives?
seaborn - Statistical data visualization in Python
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
pygal - PYthon svg GrAph plotting Library
bqplot - Plotting library for IPython/Jupyter notebooks
Flask JSONDash - :snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.
bokeh - Interactive Data Visualization in the browser, from Python
Altair - Declarative statistical visualization library for Python
plotnine - A Grammar of Graphics for Python