When it comes to Python, there are few libraries which are used to create interactive plots in Python Here in this post we will see the importance, usability about these libraries.
No doubt python is right now the number one programming language after the data science related domain. Those who are about to start their carrier and those having experience are looking for opportunities in this field.
Python has a stockpile of libraries which makes it more friendly and easy to learn. Out of these libraries there are lot of libraries which are used for data visualization purpose like matplotlib, seaborne, ggplot, plotly, bokeh are namely few, but Plotly by Dash and Bokeh are the one which are used to create interactive plots in Python and always be on the top of the list.
Bokeh and Plotly are categorized as “libraries use to create Interactive charts”.
Some of the features offered by Bokeh are:
- Quickly and easily create interactive plots, dashboards, and data applications.
- interactive visualization library
- Best works with modern browsers for visualization
- versatile graphics
On the other hand, Plotly provides the following key features:
- Bindings to popular languages like Python, Node, R, etc.
- Feature parity with MATLAB/matplotlib graphing
- Its completely interactive and you can download and save the charts in local machine, hover, zoom, pan.
- Plotly provides online chart editor which allows you to create charts online with different data sources.
To get more detailed knowledge about charts in Bokeh and Plotly you can check the official website of Bokeh and Plotly by Dash. Also if you want to explore more codes/posts related to Data visualization on our website, then you can find it here.
If you have any questions or if you need any help please get in touch with me using the comment section below.
What are your thoughts and which library you use for interactive charting in Python.
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