深入了解 Plotly 高级技术，附实用代码示例

Understanding Plotly

Plotly is an open-source library in Python for creating interactive charts and dashboards, offering various chart types, including scatter plots, line charts, and bar charts. Its interactivity enables dynamic zooming, panning, and interactive features.

Installation

Before diving into examples, ensure Plotly is installed using the command pip install plotly.

Examples

Example 1: Basic Line Plot using NumPy for sample data and Plotly's go.Scatter to create the line plot.

Example 2: Scatter Plot with Color Gradient using Plotly Express to represent a third dimension through size and color.

Example 3: 3D Surface Plot using NumPy to generate sample data and go.Surface to create the visualization.

Example 4: Animated Line Plot showing how to create animations with a play button and time-updating frames.

Example 5: Bubble Map using Gapminder dataset data with Plotly Express, where bubble size indicates the population of countries.

Example 6: Violin Plot using Plotly Express to show data distribution statistics for daily total bill amounts.

Example 7: Sunburst Chart created with Plotly Express, where hierarchy is defined by the path, and values are represented by segment sizes.

Example 8: Heatmap with Annotations using Plotly Express to visualize a correlation matrix with customizable axis labels and color bar labels.

Example 9: Radar Chart using Plotly's Scatterpolar to represent multiple attributes of a single data point across different categories.

Example 10: Choropleth Map with Plotly Express reflecting each country's GDP per capita through color intensity.

Example 11: Customized Bar Chart with a customized layout, including title, axis labels, and font style.

Example 12: Subplots using Plotly's make_subplots function to create two subplots sharing the same x-axis, with individual traces.

Example 13: Dynamic Dashboard with Dash, HTML, and Dash components to update a scatter plot through a callback based on a slider input.

This HTML content provides a structured summary of the article which discussed various features and functionalities of the Plotly library through multiple examples, beginning with installation instructions and concluding with the creation of dynamic dashboards.