在Plotly气泡图中标记特定气泡

您可以通过 annotations 。

这允许您在图表上写入所需的任何文本,并将其引用到数据中。还可以使用位置定位或在x和y数据顶部应用其他计算来控制文本显示的位置。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')

如果使用袖扣,则可以稍微调整上述内容:

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')

您仍然需要定义注释,因为您需要一个条件参数。然后通过将其直接传递给袖扣 annotations