之前学过数据分析课，也看过一点data100，快速过一下

Creating an Interactive Scatter Plot with Plotly Express

Plotly express is closely related to Pandas Plotting, but it is a separate library that provides a high-level interface for creating plots. It is designed to work seamlessly with pandas DataFrames and provides a simple API for creating a wide range of visualizations. Plotly express offers more flexibility and customization options than pandas plotting, making it a powerful tool for creating complex visualizations. Key components: 1. **px.scatter**: Generates a scatter plot to visualize relationships between two numerical variables. 2. Parameters: - **mpg**: Dataset containing car information. - **x='weight'**: X-axis represents car weight. - **y='mpg'**: Y-axis represents miles per gallon. - **color='origin'**: Groups points by car origin. - **size='cylinders'**: Marker size reflects the number of cylinders. - **size_max=12**: Limits marker size. - **hover_data=mpg.columns**: Displays all dataset columns on hover. - **title='MPG vs. Weight by Origin'**: Adds a plot title. - **labels={'weight': 'Weight (lbs)', 'mpg': 'Miles Per Gallon (MPG)'}**: Customizes axis labels. - **width=800, height=600**: Sets plot dimensions.

All the basic plotting functions in pandas and plotly express return Figure objects, which can be further customized using the methods available in the plotly.graph_objects module. We can use update_layout to update some parameters in the figure.

We can also save plots to HTML files, which can be shared and embedded in web applications. This is useful for creating interactive reports and dashboards.

The figure object is made of two key components: - the data and - the layout.

The data is a list of traces, which are the individual plots that make up the figure. The layout is a dictionary that contains information about the appearance of the plot, such as the title, axis labels, and legend.

Using Plotly Graphics Objects

The Graphics objects are a more flexible and powerful interface that allows for fine-grained control over the appearance and behavior of plots. It is suitable for creating complex visualizations and custom layouts.

A Figure Graphic Object is composed of: - Data: A list of traces (e.g., Scatter, Lines, Annotations) - Layout: A dictionary describing the overall layout (e.g., title, axis properties, …)

Visualizing Different Kinds of Data

Now that we have seen the basics of using Plotly, let’s explore how to visualize different kinds of data.

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