如何为具有多个 y 轴的图表设置动画（python）

Posted 2023-02-18

【中文标题】如何为具有多个 y 轴的图表设置动画（python）

【英文标题】：How to animate chart with multiple y axis (python)

【发布时间】：2021-12-18 21:28:22

【问题描述】：

我正在尝试使用辅助 y 轴制作动画情节（目前使用 plotly.express 但对任何其他解决方案开放）。我已经阅读了有关如何使用多个组（Plotly: How to animate a bar chart with multiple groups using plotly express?）为条形图制作动画并在 plotly-express 上制作第二个轴（Plotly: How to plot on secondary y-Axis with plotly express）的不同主题，但是我还没有找到关于如何使用辅助 y 轴制作动画图的任何答案.

这是我的代码

import pandas as pd
import plotly.express as px
df = pd.read_csv("plotly_animation_***.csv")
px.bar(data_frame=df,x="date",y=["A","B","C"],animation_frame="lag",barmode="group")

由于比例问题，我看不到 C 列的条形图

plotly-express 也存在问题，因为我的数据框随着额外的滞后而扩展。我可以在 Tableau 中轻松地做到这一点，但我正在努力保持这个开源。是否有另一种方法可以将函数传递给绘图，当我移动滑块时它会应用额外的滞后？

这是数据

date,A,B,C,lag
8/22/2016,54987,36488,0.3389,0
8/23/2016,91957,73793,0.3389,0
8/24/2016,91957,73793,0.3357,0
8/25/2016,91957,73793,0.3291,0
8/26/2016,91957,73793,0.3295,0
8/29/2016,91957,73793,0.3281,0
8/30/2016,107657,82877,0.3273,0
8/31/2016,107657,82877,0.3247,0
9/1/2016,107657,82877,0.322,0
9/2/2016,107657,82877,0.3266,0
8/22/2016,54987,36488,NA,1
8/23/2016,91957,73793,0.3389,1
8/24/2016,91957,73793,0.3389,1
8/25/2016,91957,73793,0.3357,1
8/26/2016,91957,73793,0.3291,1
8/29/2016,91957,73793,0.3295,1
8/30/2016,107657,82877,0.3281,1
8/31/2016,107657,82877,0.3273,1
9/1/2016,107657,82877,0.3247,1
9/2/2016,107657,82877,0.322,1
9/3/2016,,,0.3266,1
8/22/2016,54987,36488,,2
8/23/2016,91957,73793,,2
8/24/2016,91957,73793,0.3389,2
8/25/2016,91957,73793,0.3389,2
8/26/2016,91957,73793,0.3357,2
8/29/2016,91957,73793,0.3291,2
8/30/2016,107657,82877,0.3295,2
8/31/2016,107657,82877,0.3281,2
9/1/2016,107657,82877,0.3273,2
9/2/2016,107657,82877,0.3247,2
9/3/2016,,,0.322,2
9/4/2016,,,0.3266,2

【参考方案1】：

构建图形后，更新所需的轨迹以使用辅助 y 轴。这需要包括框架内的跟踪以及图形内的跟踪 配置辅助 y 轴

import pandas as pd
import plotly.express as px
import io

data = """date,A,B,C,lag
8/22/2016,54987,36488,0.3389,0
8/23/2016,91957,73793,0.3389,0
8/24/2016,91957,73793,0.3357,0
8/25/2016,91957,73793,0.3291,0
8/26/2016,91957,73793,0.3295,0
8/29/2016,91957,73793,0.3281,0
8/30/2016,107657,82877,0.3273,0
8/31/2016,107657,82877,0.3247,0
9/1/2016,107657,82877,0.322,0
9/2/2016,107657,82877,0.3266,0
8/22/2016,54987,36488,NA,1
8/23/2016,91957,73793,0.3389,1
8/24/2016,91957,73793,0.3389,1
8/25/2016,91957,73793,0.3357,1
8/26/2016,91957,73793,0.3291,1
8/29/2016,91957,73793,0.3295,1
8/30/2016,107657,82877,0.3281,1
8/31/2016,107657,82877,0.3273,1
9/1/2016,107657,82877,0.3247,1
9/2/2016,107657,82877,0.322,1
9/3/2016,,,0.3266,1
8/22/2016,54987,36488,,2
8/23/2016,91957,73793,,2
8/24/2016,91957,73793,0.3389,2
8/25/2016,91957,73793,0.3389,2
8/26/2016,91957,73793,0.3357,2
8/29/2016,91957,73793,0.3291,2
8/30/2016,107657,82877,0.3295,2
8/31/2016,107657,82877,0.3281,2
9/1/2016,107657,82877,0.3273,2
9/2/2016,107657,82877,0.3247,2
9/3/2016,,,0.322,2
9/4/2016,,,0.3266,2"""

df = pd.read_csv(io.StringIO(data))
fig = px.bar(data_frame=df,x="date",y=["A","B","C"],animation_frame="lag",barmode="group")

# update approprate traces to use secondary yaxis
for t in fig.data:
    if t.name=="C": t.update(yaxis="y2")
for f in fig.frames:
    for t in f.data:
        if t.name=="C": t.update(yaxis="y2")

# configure yaxis2 and give it some space
fig.update_layout(yaxis2="overlaying":"y", "side":"right", xaxis="domain":[0,.98])