Introduction to plotly.py
Plotly.py is a powerful, open-source graphing library for Python that facilitates the creation of interactive and aesthetically pleasing graphs within web browsers. It stands on the foundation of Plotly.js and brings forth an extensive variety of visualization capabilities suited for different domains, ranging from scientific to financial and beyond.
Overview
The plotly.py library is part of the Plotly ecosystem and it leverages over 30 types of charts provided by its underlying technology, Plotly.js. Users have access to a plethora of visualization options including 3D models, statistical graphs, SVG maps, and more. Embracing modern web standards, plotly.py allows for interactive charting and graph creation—aiding in bringing data stories to life without the need to study complex coding patterns or syntax.
Licensed under the MIT License, plotly.py promotes flexibility and ease of distribution. It supports seamless integration into Jupyter notebooks—a popular interactive computing environment, as well as Dash applications, which are web-based applications that help data analysts visualize Python data.
Quickstart Guide
Getting started with plotly.py is straightforward. A simple installation through pip can have the library ready for use:
pip install plotly==5.24.1
Within Jupyter, a user can easily generate visualizations. For example, a basic bar chart can be generated with these few lines of code:
import plotly.express as px
fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2])
fig.show()
Installation Process
For those who prefer conda for package management, plotly.py can also be installed via:
conda install -c plotly plotly=5.24.1
Plotly.py is designed to work smoothly with both JupyterLab and Jupyter Notebook. For JupyterLab, it is recommended to have both jupyterlab and ipywidgets installed. Similarly, the compatibility with older versions is maintained through specific packages.
Exporting Static Images
In creating reports or sharing visuals that cannot be interacted with online, plotly.py offers static image export using Kaleido or the legacy Orca command line tool. Kaleido is particularly notable due to its ease of installation and wide compatibility:
pip install -U kaleido
Extended Geographic Support
Plotly.py can produce intricate geographic visualizations that require substantial geospatial data. The necessary resources for this are available through the separate plotly-geo package, easily installable via pip or conda.
Migration Guides
Transitioning from older versions of plotly.py to version 4 or 3 is simplified with dedicated migration guides. These documents help developers smoothly upgrade their visualization workflows without disruption.
Conclusion
Plotly.py is a versatile, user-friendly tool for the Python community to render dynamic and informative visualizations with minimal effort. Continuous community support, coupled with exhaustive documentation, makes plotly.py not only robust but also accessible to data enthusiasts and professionals seeking to depict data in new, engaging ways.