散布的编辑大小

发布于 2025-02-09 12:23:32 字数 456 浏览 3 评论 0原文

这是我简单的情节图表的示例：

px.scatter(data_frame=testdf,
       x = 'some_x',
       y = 'some_y',
       size = 'some_size',
       color = 'sth_colorful',
       title = 'stackoverflow',
       range_x = [-10, 1100],
       range_y = [-0.08, 1],
       hover_name = 'sth_i_want_to_check',
       animation_frame = 'year_of_course'
      )

这是非常好的。令我困扰的一件事是，“ some_size”最小值约为20，最大值约为35，因此很难注意到圆圈之间的大小差异。有什么方法可以管理这些直径？我想保留原始值以悬停。

原文

Here's a sample of my simple plotly chart:

px.scatter(data_frame=testdf,
       x = 'some_x',
       y = 'some_y',
       size = 'some_size',
       color = 'sth_colorful',
       title = 'stackoverflow',
       range_x = [-10, 1100],
       range_y = [-0.08, 1],
       hover_name = 'sth_i_want_to_check',
       animation_frame = 'year_of_course'
      )

It is alomost good. One thing that bothers me is that 'some_size' min value is about 20 and max is about 35 so it is hard to notice the size difference between the circles.
Is there a way I can manage the diameter of these? I'd like to keep the original values to appear in a hover.

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后来的我们 2025-02-16 12:23:32

当您将参数size ='Some_size'传递给px.scatter时，这直接确定标记在图上呈现时的大小。

但是，您可以采取的措施是创建一个新列，称为“ display_ize”，带有标记的预期尺寸，并将custydata设置为df [ 'some_size']，因此您可以在HoverTemplate中访问这些值。

之后，您可以循环浏览px.scatter中的所有跟踪，并修改HoverTemplate以显示Some_Size而不是display_size。

例如：

## increase the standard deviation of the size values
## so that the difference between small and large markers is more apparent
testdf["display_size"] = 2*test_df["some_size"]

fig = px.scatter(data_frame=testdf,
       x = 'some_x',
       y = 'some_y',
       size = 'display_size',
       color = 'sth_colorful',
       title = 'stackoverflow',
       range_x = [-10, 1100],
       range_y = [-0.08, 1],
       hover_name = 'sth_i_want_to_check',
       animation_frame = 'year_of_course'
      )

fig.update_traces(customdata=testdf["some_size"])

## replace marker.size in the hovertemplate with your customdata (the actual size values)
for trace in fig.data:
    trace['hovertemplate'] = trace['hovertemplate'].replace('marker.size','customdata')

When you pass the argument size = 'some_size' to px.scatter, this directly determines the size of the markers as they render on the plot.

However, what you can do to get around this is create a new column called "display_size" with your intended sizes for the markers, and set customdata to df['some_size'] so you can access these values in the hovertemplate.

After that, you can loop through all of the traces in your px.scatter and modify the hovertemplate to display some_size instead of display_size.

For example:

## increase the standard deviation of the size values
## so that the difference between small and large markers is more apparent
testdf["display_size"] = 2*test_df["some_size"]

fig = px.scatter(data_frame=testdf,
       x = 'some_x',
       y = 'some_y',
       size = 'display_size',
       color = 'sth_colorful',
       title = 'stackoverflow',
       range_x = [-10, 1100],
       range_y = [-0.08, 1],
       hover_name = 'sth_i_want_to_check',
       animation_frame = 'year_of_course'
      )

fig.update_traces(customdata=testdf["some_size"])

## replace marker.size in the hovertemplate with your customdata (the actual size values)
for trace in fig.data:
    trace['hovertemplate'] = trace['hovertemplate'].replace('marker.size','customdata')

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