Based on our record, Matplotlib seems to be a lot more popular than GnuPlot. While we know about 98 links to Matplotlib, we've tracked only 5 mentions of GnuPlot. 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.
To some extent it extends the concept of tasks which only can be reasonably executed after the completion of other ones (though results of branches eventually may join each other) and offers an additional assisting birds' eye visual of projects. So far, I'm aware about the documentation on worg interfacing org-taskjuggler and taskjuggler, as well as a video tutorial interfacing gnuplot instead. Source: 12 months ago
Gnuplot is a program to plot diagrams. The Commands issued to use it don't change regardless if it is used in Linux/Windows/MacOS and it comes with less dependencies than a Spread sheet, or a statistics program. This is why I started to Become comfortable with it, and venture out some of its features. Here, "conditional plot" referred to "the diagram only displays a Thing/uses a pixel if the value in the table... Source: about 1 year ago
Or, does drawing diagrams refers to plotting data, but neither using matplotlib, nor gnuplot (export to .svg, .pdf, .png; pstricks, tikz to mention a few options)? Source: about 1 year ago
There may the occasion you actually need the data from a publication, and want to plot them altogether with data newly collected data in one diagram in common. An overlay, though possible, can become tricky (scaling, centering, alignment, etc.) and plotting all data in a diagram generated from scratch (gnuplot/octave, matplotlib, Origin, ...) exported as an illustration in the usual formats (.pdf/.png), or... Source: over 1 year ago
Have you looked at the graphing capabilities of Octave or Gnuplot? Gnuplot in particular has a lot of options, and a GUI for those who want it. Source: over 1 year ago
Matplotlib: for displaying our image result. - Source: dev.to / 19 days ago
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 2 months ago
Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 5 months ago
For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / 9 months ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 12 months ago
SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
GeoGebra - GeoGebra is free and multi-platform dynamic mathematics software for learning and teaching.
Plotly - Low-Code Data Apps
GeoGebra CAS Calculator - Free online algebra calculator from GeoGebra: solve equations, expand and factor expressions, find derivatives and integrals
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.