Plotly is a free open-source graphing library that can be used to form data visualizations. So you can use Matplotlib to create plots, bar charts, pie charts, histograms, scatterplots, error charts, power spectra, stemplots, and whatever other visualization charts you want! The Pyplot module also provides a MATLAB-like interface that is just as versatile and useful as MATLAB while being free and open source. It can be used to embed plots into applications using various GUI toolkits like Tkinter, GTK+, wxPython, Qt, etc. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, etc. It comes with an interactive environment across multiple platforms. 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. These libraries are so popular because they allow analysts and statisticians to create visual data models easily according to their specifications by conveniently providing an interface, data visualization tools all in one place! This article demonstrates the Top 10 Python Libraries for Data Visualization that are commonly used these days. There are several libraries available in recent years that create beautiful and complex data visualizations. And Python is one of the most popular programming languages for data analytics as well as data visualization. They tell you information just by looking at them whereas normally you would have to read spreadsheets or text reports to understand the data. Humans are visual creatures and hence, data visualization charts like bar charts, scatterplots, line charts, geographical maps, etc. Top 10 Projects For Beginners To Practice HTML and CSS Skills.
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