Plotly Python: An Introduction
While learning Python, I found countless articles going over the two core graphing libraries — Matplotlib and Seaborn.
However, I found that they lacked some of the ‘professional’ level aesthetic that I was looking for.
I ultimately found Plotly (and Dash) and quickly realized the power, flexibility, and overall ease of use.
In this introductory article, I want to give you an overview of the Plotly library using a sample Kaggle dataset.
I will do my coding via Google Colab notebook. If you are not familiar with Colab, you can refer to an overview article written here.
What is Plotly?
Plotly Python is an open-source library built on top of plotly.js which allows users to create professional quality, interactive, web-based or standalone visualizations or applications.
Visualizations can be displayed in Jupyter notebooks, standalone HTML files, or integrated into web-applications via the Dash framework.
Over 40 unique charts and limitless customization options exist across statistical, financial, geographic, scientific, and 3-D plot types.
Getting Started
I’ve decided to pull an ice hockey dataset from Kaggle to use as my example.
I loaded the…
