hvPlot provides a high-level and pandas-like plot API to easily generate modern and interactive plots
There are many high-level libraries in Python, which provide methods to easily produce various kinds of plots. For example, pandas provides very easy methods to create the most commonly used plots, which is demonstrated in one of the previous articles. Besides static plots, pandas can also create interactive plots with the help of other plotting backends, such as bokeh, plotly and holoViews/hvPlot, which have been illustrated in another previous article.
However, most of these libraries have their native plotting APIs built on Matplotlib, which lack the benefits of modern and interactive plotting features for the webs like Bokeh and HoloViews. For holoViews, I also wrote two articles to display how to use it easily to create various kinds of interactive plots.
From this article, I will start to demonstrate another modern data visualization tool, hvPlot. hvPlot provides a high-level and pandas-like plot API built on HoloViews, which can easily generate modern and interactive plots. In this article, we focus on the following contents.
This article briefly introduce to hvPlot, which is a high-level and pandas-like plot API to easily generate modern and interactive plots. It mainly answers three questions: （1）how to install hvPlot; (2) what data structures does it support; and (3) what backends do it use. In terms of data structures, we can see that hvPlot support large data visualization. For backends, it demonstrates how to change its backend and use each backend to create plots with a specific example.