# Naming y-axes fig.update_yaxes(title_text="Main Y - axis ",secondary_y=False) fig.update_yaxes(title_text="secondary Y - axis ",secondary_y=True) 输出: 绘制具有多个 y 轴的条形图 用多个 Y 轴绘制图表 现在,让我们看看如何绘制具有超过 2 个 Y 轴或多个 Y 轴的散点图。步骤同上,在...
y1) ax1.set_ylabel('Y values for exp(-x)') ax1.set_title("Dou
plot_bgcolor 设置x和y轴之间(in-between)的绘图区域的颜色 paper_bgcolor 设置绘制图形的纸张的颜色 xaxis plotly.graph_objects.layout.XAxis实例 或 兼容性的属性的字典 常用属性有 title x轴的坐标轴标签 type 设置轴类型. 默认情况下, plotly尝试通过查看提到axis的traces的数据来确定轴类型 ['-', 'linear'...
双折线图 双Y轴 双坐标系坐标 option = { xAxis: { type: 'category', data: ['Mon...
'Dec'], y = [19,14,22,14,16,19,15,14,10,12,12,16], name = 'Secondary Produ...
y=[19, 14, 22, 14, 16, 19, 15, 14, 10, 12, 12, 16], name='Secondary Product', marker_color='lightsalmon' )) fig.update_layout(barmode='group', xaxis_tickangle=-45) #将x轴标签适当倾斜 fig.show() 1. 2. 3. 4.
return df.dropna()# 创建交互图表def create_plotly_chart(df, period): fig = make_subplots( rows=5, cols=1, shared_xaxes=True, vertical_spacing=0.03, row_heights=[0.5, 0.15, 0.15, 0.15, 0.2], specs=[[{"secondary_y": True}], [{}], [{}], [{}], [...
['cumulative_perc'], name='Cumulative Percentage', yaxis='y2' ) fig = make_subplots(specs=[[{"secondary_y": True}]]) fig.add_trace(trace1) fig.add_trace(trace2,secondary_y=True) fig['layout'].update(height = 600, width = 800, title = title,xaxis=dict( tickangle=-90 )) ...
tds[['claps','fans','title']].iplot(y='claps',mode='lines+markers',secondary_y='fans',secondary_y_title='Fans',xTitle='Date',yTitle='Claps',text='title',title='Fans and Claps over Time') 在这里,我们仅用一行代码做了很多不同的事情: ...
secondary_y = False) # B fig.add_trace(go.Scatter(x= B_error['CloseDate'], y = B_error[err], line_color = 'blue', mode = 'lines+markers', showlegend = True, name = "B", stackgroup = 'one'), row = 2, col = 1, secondary_y = False) fig.update_yaxes(tickprefix = '...