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Matplotlib VS Google Charts

Compare Matplotlib VS Google Charts and see what are their differences

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Matplotlib logo Matplotlib

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

Google Charts logo Google Charts

Interactive charts for browsers and mobile devices.
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Google Charts Landing page
    Landing page //
    2023-05-10

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Google Charts videos

+ Add

Data Visualization for the Web Using Google Charts

More videos:

  • Review - Incorporating Google Charts in a FileMaker Solution | FileMaker Training
  • Review - Google Charts for Native Android Apps

Category Popularity

0-100% (relative to Matplotlib and Google Charts)

Matplotlib

Google Charts

Technical Computing
100 100%
Technical Computing
0% 0
Data Dashboard
22 22%
Data Dashboard
78% 78
Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Charting Libraries
0 0%
Charting Libraries
100% 100

User comments

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Reviews

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

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

Google Charts Reviews

15 JavaScript Libraries for Creating Beautiful Charts
Google Charts also comes with various customization options that help in changing the look of the graph. Charts are rendered using HTML5/SVG to provide cross-browser compatibility and cross-platform portability to iPhones, iPads, and Android. It also includes VML for supporting older IE versions.
Source: www.sitepoint.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Google Charts is an excellent choice for projects that do not require complicated customization and prefer simplicity and stability.
Source: hackernoon.com
A Complete Overview of the Best Data Visualization Tools
Google Charts is a powerful, free data visualization tool that is specifically for creating interactive charts for embedding online. It works with dynamic data and the outputs are based purely on HTML5 and SVG, so they work in browsers without the use of additional plugins. Data sources include Google Spreadsheets, Google Fusion Tables, Salesforce, and other SQL databases.
Source: www.toptal.com
The Best Data Visualization Tools - Top 30 BI Software
Google Charts runs on SVG and HTML5, aiming for Android, iOS and total cross-browser compatibility, including older versions of Internet Explorer. All of the charts you can create are interactive and you may be able zoom in on some of them. The site offers a fairly comprehensive gallery where you can find a variety of types of visualizations and interactions that you can use.
Source: improvado.io

Social recommendations and mentions

Based on our record, Matplotlib should be more popular than Google Charts. It has been mentiond 98 times since March 2021. 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 / about 1 month 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 / 3 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: about 1 year ago
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Google Charts mentions (10)

  • The top 11 React chart libraries for data visualization
    This library leverages the robustness of Google’s chart tools combined with a React-friendly experience. It is ideal for developers familiar with Google’s visualization ecosystem. - Source: dev.to / 7 months ago
  • Using Images in a chart?
    I tried adding the images as labels and it didn't work. If this is possible at all, it would probably require Google Charts. Source: about 1 year ago
  • What are some good graph visualization libraries?
    Google's is a bit simpler to work with but more basic in terms of features https://developers.google.com/chart. Source: over 1 year ago
  • 5 Best Free JS Chart Libraries
    Google charts Https://developers.google.com/chart. - Source: dev.to / over 1 year ago
  • Suggestions for super simple QR code generator
    I did find a nice solution for Access forms where you can use a web browser control and developers.google.com/chart to render a QR code in that control based on the contents of other controls (textboxes, comboboxes, etc.,.). This would be perfect if it didn't a) rely on an active WAN connection and b) rely on that specific URL being active indefinitely. Source: almost 2 years ago
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What are some alternatives?

When comparing Matplotlib and Google Charts, you can also consider the following products

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

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.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

Plotly - Low-Code Data Apps

Chart.js - Easy, object oriented client side graphs for designers and developers.

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