Based on our record, NumPy seems to be a lot more popular than GnuPlot. While we know about 107 links to NumPy, 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.
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
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: about 1 year 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
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
GeoGebra - GeoGebra is free and multi-platform dynamic mathematics software for learning and teaching.
OpenCV - OpenCV is the world's biggest computer vision library
SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.