我无法弄清楚如何在plot.ly气泡图中标记特定的气泡。 我希望某些“异常”气泡能够在气泡中写入文本，而不是通过悬停文本。
假设我有这些数据：
import plotly.plotly as py import plotly.graph_objs as go trace0 = go.Scatter( x=[1, 2, 3, 4], y=[10, 11, 12, 13], mode='markers', marker=dict( size=[40, 60, 80, 100], ) ) data = [trace0] py.iplot(data, filename='bubblechart-size')我想只在与（1,10）和（4,13）对应的气泡上添加文字标记。 此外，是否可以控制文本标记的位置？
I am having trouble figuring out how to label specific bubbles in a plot.ly bubble chart. I want certain "outlier" bubbles to have text written inside the bubble instead of via hover text.
Let's say I have this data:
import plotly.plotly as py import plotly.graph_objs as go trace0 = go.Scatter( x=[1, 2, 3, 4], y=[10, 11, 12, 13], mode='markers', marker=dict( size=[40, 60, 80, 100], ) ) data = [trace0] py.iplot(data, filename='bubblechart-size')I'd like to only add text markers on bubbles that correspond to (1,10) and (4,13). Furthermore, is it possible to control the location of text markers?
最满意答案
您可以使用注释来实现此目的。
这允许您在图表上写下您想要的任何文本并将其引用到您的数据中。 您还可以使用位置锚点或通过在x和y数据之上应用其他计算来控制文本的显示位置。 例如：
x_data = [1, 2, 3, 4] y_data = [10, 11, 12, 13] z_data = [40, 60, 80, 100] annotations = [ dict( x=x, y=y, text='' if 4 > x > 1 else z, # Some conditional to define outliers showarrow=False, xanchor='center', # Position of text relative to x axis (left/right/center) yanchor='middle', # Position of text relative to y axis (top/bottom/middle) ) for x, y, z in zip(x_data, y_data, z_data) ] trace0 = go.Scatter( x=x_data, y=y_data, mode='markers', marker=dict( size=z_data, ) ) data = [trace0] layout = go.Layout(annotations=annotations) py.iplot(go.Figure(data=data, layout=layout), filename='bubblechart-size')编辑
如果使用袖扣，那么上面的内容可以略微适应：
bubbles_to_annotate = df[(df['avg_pos'] < 2) | (df['avg_pos'] > 3)] # Some conditional to define outliers annotations = [ dict( x=row['avg_pos'], y=row['avg_neg'], text=row['subreddit'], showarrow=False, xanchor='center', # Position of text relative to x axis (left/right/center) yanchor='middle', # Position of text relative to y axis (top/bottom/middle) ) for _, row in bubbles_to_annotate.iterrows() ] df.iplot(kind='bubble', x='avg_pos', y='avg_neg', size='counts', text='subreddit', xTitle='Average Negative Sentiment', yTitle='Average Positive Sentiment', annotations=annotations, filename='simple-bubble-chart')由于需要条件参数，因此仍需要定义注释。 然后通过annotations将其直接传递给袖扣。
You can achieve this with annotations.
This allows you to write any text you want on the chart and reference it to your data. You can also control where the text appears using position anchors or by applying an additional calculation on top of the x and y data. For example:
x_data = [1, 2, 3, 4] y_data = [10, 11, 12, 13] z_data = [40, 60, 80, 100] annotations = [ dict( x=x, y=y, text='' if 4 > x > 1 else z, # Some conditional to define outliers showarrow=False, xanchor='center', # Position of text relative to x axis (left/right/center) yanchor='middle', # Position of text relative to y axis (top/bottom/middle) ) for x, y, z in zip(x_data, y_data, z_data) ] trace0 = go.Scatter( x=x_data, y=y_data, mode='markers', marker=dict( size=z_data, ) ) data = [trace0] layout = go.Layout(annotations=annotations) py.iplot(go.Figure(data=data, layout=layout), filename='bubblechart-size')Edit
If using cufflinks, then the above can be adapted slightly to:
bubbles_to_annotate = df[(df['avg_pos'] < 2) | (df['avg_pos'] > 3)] # Some conditional to define outliers annotations = [ dict( x=row['avg_pos'], y=row['avg_neg'], text=row['subreddit'], showarrow=False, xanchor='center', # Position of text relative to x axis (left/right/center) yanchor='middle', # Position of text relative to y axis (top/bottom/middle) ) for _, row in bubbles_to_annotate.iterrows() ] df.iplot(kind='bubble', x='avg_pos', y='avg_neg', size='counts', text='subreddit', xTitle='Average Negative Sentiment', yTitle='Average Positive Sentiment', annotations=annotations, filename='simple-bubble-chart')You will still need to define the annotations since you need a conditional argument. Then pass this directly to cufflinks via annotations.
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