Matplotlib VS NumPy

Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

NumPy

NumPy is the fundamental package for scientific computing with Python

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2023-06-14

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2023-05-13

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

Category Popularity

0-100% (relative to Matplotlib and NumPy)

NumPy

Technical Computing

100 100%

Technical Computing

0% 0

Data Science And Machine Learning

20 20%

Data Science And Machine Learning

80% 80

Data Science Tools

0 0%

Data Science Tools

100% 100

Data Visualization

100 100%

Data Visualization

0% 0

User comments

Share your experience with using Matplotlib and NumPy. For example, how are they different and which one is better?

Reviews

These are some of the external sources and on-site user reviews we've used to compare Matplotlib and NumPy

Matplotlib Reviews

25 Python Frameworks to Master

Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.

Source: kinsta.com

5 Best Python Libraries For Data Visualization in 2023

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 code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.

Source: www.technotification.com

15 data science tools to consider using in 2021

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 visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.

Source: searchbusinessanalytics.techtarget.com

Top Python Libraries For Image Processing In 2021

Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesn’t support all file formats.

Source: www.analyticsvidhya.com

Top 8 Python Libraries for Data Visualization

Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...

Source: www.geeksforgeeks.org

NumPy Reviews

25 Python Frameworks to Master

SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.

Source: kinsta.com

Top 8 Image-Processing Python Libraries Used in Machine Learning

Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.

Source: neptune.ai

Top Python Libraries For Image Processing In 2021

Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.

Source: www.analyticsvidhya.com

4 open source alternatives to MATLAB

NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...

Source: opensource.com

Social recommendations and mentions

NumPy might be a bit more popular than Matplotlib. We know about 107 links to it since March 2021 and only 98 links to Matplotlib. 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.

Matplotlib mentions (98)

Implementing semantic image search with Amazon Titan and Supabase Vector
Matplotlib: for displaying our image result. - Source: dev.to / 21 days ago
Releasing The Force Of Machine Learning: A Novice’s Guide 😃
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 2 months ago
How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 5 months ago
Ask HN: What plotting tools should I invest in learning?
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
PSA: You don't need fancy stuff to do good work.
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

NumPy mentions (107)

Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 1 month ago
JSON in data science projects: tips & tricks
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 / about 2 months ago
Introducing Flama for Robust Machine Learning APIs
Numpy: A library for scientific computing in Python. - Source: dev.to / 4 months ago
A Comprehensive Guide to NumPy Arrays
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
Beginning Python: Project Management With PDM
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