18.3 Plotly for interactive and web-based visualizations
4 min read•Last Updated on July 30, 2024
Plotly is a powerful Python library for creating interactive, web-based visualizations. It offers a wide range of chart types and customization options, allowing you to create stunning, publication-quality graphs that users can interact with directly in their web browsers.
With Plotly, you can easily add interactivity to your visualizations, create animations, and even build dynamic dashboards. This makes it an essential tool for data scientists and analysts who want to create engaging, exploratory data visualizations that can be easily shared and embedded in web pages.
Interactive Plots with Plotly
Creating Plots with Plotly
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Top images from around the web for Creating Plots with Plotly
Interactive plots in R using plotly - Dave Tang's blog View original
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Simplify data visualization in Python with Plotly | Opensource.com View original
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Interactive plots in R using plotly - Dave Tang's blog View original
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Plotly is a Python graphing library used to create interactive, publication-quality graphs
Supports various chart types (line charts, scatter plots, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, and 3D graphs)
Plotly graphs are defined by data, layout and frames parameters
data parameter takes a list of dictionaries specifying the data for each trace
layout parameter configures the visual elements of the graph (title, axes, annotations, shapes, legends)
frames parameter allows for the creation of animated graphs
Line charts are created using the go.Scatter function with mode='lines'
Data should be in a dictionary with keys for x and y values
Example: {'x': [1, 2, 3], 'y': [4, 5, 6]}
Bar charts are created using the go.Bar function
Data should be in a dictionary with keys for x (categorical variables) and y (numerical variables) values